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  • 101.
    Blomqvist, Sven
    et al.
    Univ Gävle, Fac Hlth & Occupat Studies, Gävle, Sweden..
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala Univ, Dept Informat Technol, Uppsala, Sweden.;Univ Gävle, Fac Engn & Sustainable Dev, Gävle, Sweden..
    Engstrom, Maria
    Univ Gävle, Fac Hlth & Occupat Studies, Gävle, Sweden..
    Using augmented reality technology for balance training in the older adults: a feasibility pilot study2021In: BMC Geriatrics, ISSN 1471-2318, E-ISSN 1471-2318, Vol. 21, no 1, article id 144Article in journal (Refereed)
    Abstract [en]

    BackgroundImpaired balance leading to falls is common in the older adults, and there is strong evidence that balance training reduces falls and increases independence. Reduced resources in health care will result in fewer people getting help with rehabilitation training. In this regard, the new technology augmented reality (AR) could be helpful. With AR, the older adults can receive help with instructions and get feedback on their progression in balance training. The purpose of this pilot study was to examine the feasibility of using AR-based visual-interactive tools in balance training of the older adults.MethodsSeven older adults (66-88years old) with impaired balance trained under supervision of a physiotherapist twice a week for six weeks using AR-based visual-interactive guidance, which was facilitated through a Microsoft HoloLens holographic display. Afterwards, participants and physiotherapists were interviewed about the new technology and their experience of the training. Also, fear of falling and balance ability were measured before and after training.ResultsFive participants experienced the new technology as positive in terms of increased motivation and feedback. Experiences were mixed regarding the physical and technical aspects of the HoloLens and the design of the HoloLens application. Participants also described issues that needed to be further improved, for example, the training program was difficult and monotonous. Further, the HoloLens hardware was felt to be heavy, the application's menu was difficult to control with different hand manoeuvres, and the calibration took a long time. Suggestions for improvements were described. Results of the balance tests and self-assessment instruments indicated no improvements in balance performance after AR training.ConclusionsThe study showed that training with the new technology is, to some extent, feasible for the older adults, but needs further development. Also, the technology seemed to stimulate increased motivation, which is a prerequisite for adherence to training. However, the new technology and training requires further development and testing in a larger context.

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  • 102.
    Boman, Katarina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Low-angle estimation: Models, methods and bounds2000Licentiate thesis, monograph (Other scientific)
    Abstract [en]

    In this work we study the performance of elevation estimators and lower bounds on the estimation error variance for a low angle target in a smooth sea scenario using an array antenna. The article is structured around some key assumptions on multipath knowledge, signal parameterization and noise covariance, giving the reader a framework in which Maximum Likelihood estimators exploiting different á priori information can be found.

    The crucial factor that determines the estimator accuracy is the multipath modeling, and there are three alternative levels of knowledge that can be used: 1) two unknown target locations 2) the target and its corresponding sea-reflection are related via simple geometry 3) the sea-reflection coefficient is known as a function of grazing angle.

    A compact expression for the Cramér–Rao lower bound is derived, including all special cases of the key assumptions. We prove that the Cramér–Rao bound is highly dependent on the multipath model, while it is the same for the different signal parameterizations and that it is independent of the noise covariance. However, the Cramér–Rao bound is sometimes too optimistic and not achievable. The tighter Barankin bound is derived to predict the threshold behavior seen at low SNR. At high SNR the Barankin bound coincides with the Cramér–Rao bound. Simulations show that the Maximum Likelihood methods are statistically efficient and achieve the theoretical lower bound on error variance, in case of high enough SNR.

    The bounds are also useful tools to design an improved array structure that can give better performance than the standard uniform linear array structure. The influence of the number of sensors and the number of snapshots on the error variance is also studied, showing the rate of improvement with more sensors or snapshots. Finally we discuss the use of multiple frequencies, which is mainly a tool for suppressing ambiguities. We show for which signal models it provides improved performance.

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  • 103. Bouleux, Guillaume
    et al.
    Stoica, Peter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Boyer, Rémy
    An optimal prior knowledge-based DOA estimation method2009In: Proc. 17th European Signal Processing Conference, European Association for Signal Processing , 2009, p. 869-873Conference paper (Refereed)
  • 104. Bouleux, Guillaume
    et al.
    Stoica, Peter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Boyer, Rémy
    Une méthode optimale pour l'estimation des directions d'arrivées basée sur des connaissances a priori2009In: Proc. XXII Colloque GRETSI, 2009, p. 4-Conference paper (Refereed)
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  • 105.
    Bro, Viktor
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Volterra modeling of the human smooth pursuit system in health and disease2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis treats the identification of Volterra models of the human smooth pursuit system from eye-tracking data. Smooth pursuit movements are gaze movements used in tracking of moving targets and controlled by a complex biological network involving the eyes and brain. Because of the neural control of smooth pursuit, these movements are affected by a number of neurological and mental conditions, such as Parkinson's disease. Therefore, by constructing mathematical models of the smooth pursuit system from eye-tracking data of the patient, it may be possible to identify symptoms of the disease and quantify them. While the smooth pursuit dynamics are typically linear in healthy subjects, this is not necessarily true in disease or under influence of drugs. The Volterra model is a classical black-box model for dynamical systems with smooth nonlinearities that does not require much a priori information about the plant and thus suitable for modeling the smooth pursuit system.

    The contribution of this thesis is mainly covered by the four appended papers. Papers I–III treat the problem of reducing the number of parameters in Volterra models with the kernels parametrized in Laguerre functional basis (Volterra–Laguerre models), when utilizing them to capture the signal form of smooth pursuit movements. Specifically, a Volterra–Laguerre model is obtained by means of sparse estimation and principal component analysis in Paper I, and a Wiener model approach is used in Paper II. In Paper III, the same model as in Paper I is considered to examine the feasibility of smooth pursuit eye tracking for biometric purposes. Paper IV is concerned with a Volterra–Laguerre model that includes an explicit time delay. An approach to the joint estimation of the time delay and the finite-dimensional part of the Volterra model is proposed and applied to time-delay compensation in eye-tracking data.

    List of papers
    1. Constrained SPICE in Volterra–Laguerre modeling of human smooth pursuit
    Open this publication in new window or tab >>Constrained SPICE in Volterra–Laguerre modeling of human smooth pursuit
    2017 (English)In: Proc. 1st Conference on Control Technology and Applications, IEEE, 2017, p. 13-18Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    IEEE, 2017
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:uu:diva-334955 (URN)10.1109/CCTA.2017.8062433 (DOI)000426981500003 ()978-1-5090-2182-6 (ISBN)
    Conference
    CCTA 2017, August 27–30, Mauna Lani, HI
    Funder
    Vinnova
    Available from: 2017-10-09 Created: 2017-11-29 Last updated: 2021-12-07Bibliographically approved
    2. Nonlinear dynamics of the human smooth pursuit system in health and disease: Model structure and parameter estimation
    Open this publication in new window or tab >>Nonlinear dynamics of the human smooth pursuit system in health and disease: Model structure and parameter estimation
    2017 (English)In: Proc. 56th Conference on Decision and Control, IEEE, 2017, p. 4692-4697Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    IEEE, 2017
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:uu:diva-334957 (URN)10.1109/CDC.2017.8264352 (DOI)000424696904084 ()978-1-5090-2873-3 (ISBN)
    Conference
    CDC 2017, December 12–15, Melbourne, Australia
    Funder
    Vinnova
    Available from: 2018-01-23 Created: 2017-11-29 Last updated: 2021-12-07Bibliographically approved
    3. Modeling of human smooth pursuit by sparse Volterra models with functionally dependent parameters
    Open this publication in new window or tab >>Modeling of human smooth pursuit by sparse Volterra models with functionally dependent parameters
    2020 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 103, article id 104606Article in journal (Refereed) Published
    Abstract [en]

    This paper deals with the identification of Volterra models that capture the dynamics of smooth pursuit eye movements recorded by an eye tracker. The framework is motivated by neurological applications but can also be useful in biometrics. In healthy subjects, ocular dynamics are predominantly linear, while neurological conditions inflict nonlinearity on smooth pursuit eye movements. Besides overparameterization, Volterra models may also exhibit functional dependence among the model coefficients. A combination of sparse estimation and Principal Component Analysis is shown to be instrumental in estimating parsimonious Volterra models from eye-tracking data. The efficacy of the approach is demonstrated on experimental data collected from Parkinsonian patients as well as healthy controls.

    Place, publisher, year, edition, pages
    Elsevier BV, 2020
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:uu:diva-385940 (URN)10.1016/j.conengprac.2020.104606 (DOI)000579812900014 ()
    Funder
    Vinnova
    Available from: 2020-08-21 Created: 2019-06-18 Last updated: 2021-12-07Bibliographically approved
    4. Identification of continuous Volterra models with explicit time delay through series of Laguerre functions
    Open this publication in new window or tab >>Identification of continuous Volterra models with explicit time delay through series of Laguerre functions
    2019 (English)In: Proc. 58th IEEE Conference on Decision and Control, IEEE, 2019, p. 5641-5646Conference paper, Published paper (Refereed)
    Abstract [en]

    The problem of estimating nonlinear time-delay dynamics captured by continuous Volterra models from input-output data is treated. The delayed Volterra kernels are seen as impulse responses of linear time-invariant systems with time delay. Analytical expressions for the Laguerre series, where the Laguerre coefficients of the finite-dimensional part are admixed with the terms due to the delay, are provided. By utilizing the linearity of Volterra-Laguerre models in the unknown parameters, the model is estimated by a nonlinear least-squares method. An application of the proposed approach to the problem of Volterra modelling of the human smooth pursuit system from eye-tracking data is provided. The proposed approach demonstrates consistently accurate performance on both simulated and experimental data.

    Place, publisher, year, edition, pages
    IEEE, 2019
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:uu:diva-385943 (URN)10.1109/CDC40024.2019.9029789 (DOI)000560779005034 ()978-1-7281-1398-2 (ISBN)
    Conference
    CDC 2019, December 11–13, Nice, France
    Available from: 2020-03-12 Created: 2019-06-18 Last updated: 2021-12-07Bibliographically approved
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  • 106.
    Bro, Viktor
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Medvedev, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Constrained SPICE in Volterra–Laguerre modeling of human smooth pursuit2017In: Proc. 1st Conference on Control Technology and Applications, IEEE, 2017, p. 13-18Conference paper (Refereed)
    Download full text (pdf)
    fulltext
  • 107.
    Bro, Viktor
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Medvedev, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Continuous and discrete Volterra-Laguerre models with  delay for modeling of smooth pursuit eye movements2023In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 70, no 1, p. 97-104Article in journal (Refereed)
    Abstract [en]

    The mathematical modeling of the human smooth pursuit system from eye-tracking data is considered. Recently developed algorithms for the estimation of Volterra-Laguerre (VL) models with explicit time delay are applied in continuous and discrete time formulations to experimental data collected from Parkinsonian patients in different medication states and healthy controls. The discrete VL model with an explicit time delay and the method for its estimation are first introduced in this paper. The estimated parameters of a second-order VL model are shown to capture the ocular dynamics both in health and disease. The possibility of including the estimated time delay, along with the VL kernel parameters, into the set of the model parameters is explored. The results obtained in continuous VL modeling are compared with those in discrete time to discern the effects due to the sampling enforced by the eye tracker used for data acquisition.

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  • 108.
    Bro, Viktor
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Medvedev, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Identification of continuous Volterra models with explicit time delay through series of Laguerre functions2019In: Proc. 58th IEEE Conference on Decision and Control, IEEE, 2019, p. 5641-5646Conference paper (Refereed)
    Abstract [en]

    The problem of estimating nonlinear time-delay dynamics captured by continuous Volterra models from input-output data is treated. The delayed Volterra kernels are seen as impulse responses of linear time-invariant systems with time delay. Analytical expressions for the Laguerre series, where the Laguerre coefficients of the finite-dimensional part are admixed with the terms due to the delay, are provided. By utilizing the linearity of Volterra-Laguerre models in the unknown parameters, the model is estimated by a nonlinear least-squares method. An application of the proposed approach to the problem of Volterra modelling of the human smooth pursuit system from eye-tracking data is provided. The proposed approach demonstrates consistently accurate performance on both simulated and experimental data.

  • 109.
    Bro, Viktor
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Medvedev, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Modeling of human smooth pursuit by sparse Volterra models with functionally dependent parameters2020In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 103, article id 104606Article in journal (Refereed)
    Abstract [en]

    This paper deals with the identification of Volterra models that capture the dynamics of smooth pursuit eye movements recorded by an eye tracker. The framework is motivated by neurological applications but can also be useful in biometrics. In healthy subjects, ocular dynamics are predominantly linear, while neurological conditions inflict nonlinearity on smooth pursuit eye movements. Besides overparameterization, Volterra models may also exhibit functional dependence among the model coefficients. A combination of sparse estimation and Principal Component Analysis is shown to be instrumental in estimating parsimonious Volterra models from eye-tracking data. The efficacy of the approach is demonstrated on experimental data collected from Parkinsonian patients as well as healthy controls.

  • 110.
    Bro, Viktor
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Medvedev, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Nonlinear dynamics of the human smooth pursuit system in health and disease: Model structure and parameter estimation2017In: Proc. 56th Conference on Decision and Control, IEEE, 2017, p. 4692-4697Conference paper (Refereed)
    Download full text (pdf)
    fulltext
  • 111.
    Bro, Viktor
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Medvedev, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Ushirobira, Rosane
    Continuous and Discrete Volterra-Laguerre Models with Explicit Time DelayIn: Automatica, ISSN 0005-1098, E-ISSN 1873-2836Article in journal (Refereed)
    Abstract [en]

    This paper solves the problem of estimating the time delay in a smooth nonlinear system modeled by a Volterra model (VM), along with the delay-free dynamics captured by the convolution operators. VMs with explicit time delay, whose convolution  kernels  are represented as series of Laguerre functions,  are considered in continuous and discrete-time. Since a VM with a time delay is linear in the kernel parameters, the proposed modeling approach, on the one hand, allows for the use of efficient linear sparse estimation techniques and, on the other hand, extends the  applicability of Volterra-Laguerre models (VLM) to a broader class of  nonlinear systems. Hinging on recent progress in Laguerre domain modeling of linear time-delay systems, analytical expressions for the projections of  kernels with a delayed argument on the Laguerre basis are obtained, featuring special kinds of polynomials that arise due to the presence of time delay. The mathematical modeling problem of the human smooth pursuit system from eye-tracking data illustrates the practical utility of the acquired theoretical results.

  • 112.
    Bro, Viktor
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Medvedev, Alexander
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Ushirobira, Rosane
    Univ Lille, CNRS, INRIA, UMR 9189 CRIStAL, F-59000 Lille, France..
    Laguerre-domain Modeling and Identification of Linear Discrete-time Delay Systems2020In: IFAC PapersOnline, ELSEVIER , 2020, Vol. 53, no 2, p. 939-944Conference paper (Refereed)
    Abstract [en]

    A closed-form Laguerre-domain representation of discrete linear time-invariant systems with constant input time delay is derived. It is shown to be useful in a I-2 -> I-2 system identification setup (with I-2 denoting square-summables signals) often arising in biomedical applications, where the experimental protocol does not allow for persistent excitation of the system dynamics. The utility of the proposed system representation is demonstrated on a problem of drug kinetics estimation from clinical data.

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  • 113.
    Brus, Linda
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Convergence Analysis of a Recursive Identification Algorithm for Nonlinear ODE Models with a Restricted Black-box Parameterization2007In: 46th IEEE Conference on Decision and Control Proceedings, 2007Conference paper (Refereed)
    Abstract [en]

    A convergence analysis is performed for a recursive prediction error method based on a restricted black-box parameterization. Sufficient conditions to obtain convergence to a minimum of the criterion function are formulated. This proves that convergence to the true parameter vector is possible. The analysis exploits averaging analysis using an associated ordinary differential equation.

  • 114.
    Brus, Linda
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Nonlinear Identification and Control with Solar Energy Applications2008Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Nonlinear systems occur in industrial processes, economical systems, biotechnology and in many other areas. The thesis treats methods for system identification and control of such nonlinear systems, and applies the proposed methods to a solar heating/cooling plant.

    Two applications, an anaerobic digestion process and a domestic solar heating system are first used to illustrate properties of an existing nonlinear recursive prediction error identification algorithm. In both cases, the accuracy of the obtained nonlinear black-box models are comparable to the results of application specific grey-box models. Next a convergence analysis is performed, where conditions for convergence are formulated. The results, together with the examples, indicate the need of a method for providing initial parameters for the nonlinear prediction error algorithm. Such a method is then suggested and shown to increase the usefulness of the prediction error algorithm, significantly decreasing the risk for convergence to suboptimal minimum points.

    Next, the thesis treats model based control of systems with input signal dependent time delays. The approach taken is to develop a controller for systems with constant time delays, and embed it by input signal dependent resampling; the resampling acting as an interface between the system and the controller.

    Finally a solar collector field for combined cooling and heating of office buildings is used to illustrate the system identification and control strategies discussed earlier in the thesis, the control objective being to control the solar collector output temperature. The system has nonlinear dynamic behavior and large flow dependent time delays. The simulated evaluation using measured disturbances confirm that the controller works as intended. A significant reduction of the impact of variations in solar radiation on the collector outlet temperature is achieved, though the limited control range of the system itself prevents full exploitation of the proposed feedforward control. The methods and results contribute to a better utilization of solar power.

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  • 115.
    Brus, Linda
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. Systemteknik.
    Nonlinear identification of a solar heating system2005In: Proceedings of the 2005 IEEE International Conference on Control Application, 2005, p. 1491-1497Conference paper (Refereed)
    Abstract [en]

    The use of solar heating systems is a way of exploiting the clean and free energy from the sun. To optimize the energy gain from such a system, where the main input, the solar insolation, is an uncontrollable variable, good models of the system dynamics are required. Identification methods are often either highly specialized for the application or require an extensive amount of data, especially when the dynamics studied are nonlinear. This paper shows that by application of a new recursive system identification technique, a small scale solar heating system can be modeled with very little data, without having to tailor the model structure to the application.

  • 116.
    Brus, Linda
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. Systemteknik.
    Nonlinear Identification of a Solar Heating System2005Report (Other scientific)
    Abstract [en]

    The use of solar heating systems is a way of exploiting the clean and free energy from the sun. To optimize the energy gain from such a system, where the main input, the solar insolation, is an uncontrollable variable, good models of the system dynamics are required. Identification methods are often either highly specialized for the application or require an extensive amount of data, especially when the dynamics studied are nonlinear. This paper shows that by application of a new recursive system identification technique, a small scale solar heating system can be modeled with very little data, without having to tailor the model structure to the application.

  • 117.
    Brus, Linda
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. Systemteknik.
    Nonlinear Identification of an Anaerobic Digestion Process2005Report (Other scientific)
    Abstract [en]

    Anaerobic digestion in bioreactors is an important technology for environmental friendly treatment of organic waste. To optimize and control such processes accurate dynamic models of the process are needed. Unfortunately, modeling of anaerobic digestion often results in high order nonlinear models with many unknown parameters, a fact that complicates controller design. This paper attempts to circumvent this problem, by application of new recursive system identification techniques, thereby radically reducing the degree of the models and the number of parameters. Experiments show that a second order nonlinear model is sufficient for accurate modeling of the system.

  • 118.
    Brus, Linda
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. Systemteknik.
    Nonlinear identification of an anaerobic digestion process2005In: Proceedings of the 2005 IEEE International Conference on Control Applications, 2005, p. 137-142Conference paper (Refereed)
    Abstract [en]

    Anaerobic digestion in bioreactors is an important technology for environmental friendly treatment of organic waste. To optimize and control such processes accurate dynamic models of the process are needed. Unfortunately, modeling of anaerobic digestion often results in high order nonlinear models with many unknown parameters, a fact that complicates controller design. This paper attempts to circumvent this problem, by application of new recursive system identification techniques, thereby radically reducing the degree of the models and the number of parameters. Experiments show that a second order nonlinear model is sufficient for accurate modeling of the system.

  • 119.
    Brus, Linda
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Recursive black-box identification of nonlinear state-space ODE models2006Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Nonlinear system identification methods is a topic that has been gaining interest over the last years. One reason is the many application areas in controller design and system development. However, the problem of modeling nonlinear systems is complex and finding a general method that can be used for many different applications is difficult.

    This thesis treats recursive identification methods for identification of systems that can be described by nonlinear ordinary differential equations. The general model structure enables application to a wide range of processes. It is also suitable for usage in combination with many nonlinear controller design methods.

    The first two papers of the thesis illustrates how a recursive prediction error method (RPEM) can be used for identification of an anaerobic digestion process and a solar heating system. In the former case the model complexity is significantly reduced compared to a semi-physical model of the system, without loosing much in model performance. In the latter case it is shown that it is possible to reach convergence even for a small data set, and that the resulting model is of comparable quality as a previously published grey-box model of the same system.

    The third paper consists of a convergence analysis of the studied RPEM. The analysis exploits averaging analysis using an associated ordinary differential equation, and formulates conditions for convergence to a minimum of the criterion function. Convergence to a true parameter set is also illustrated by an example.

    The fourth, and last, paper of this thesis addresses the problem of finding suitable initial parameters e.g. for the RPEM. With a potentially non-convex criterion function the choice of initial parameters becomes decisive for whether the algorithm converges to the global optimum, or a local one. The suggested initialization algorithm is a Kalman filter based method. Experiments using a simulated example show that the Kalman based method can, under beneficial circumstances, be used for initialization of the RPEM. The result is further supported by successful identification experiments of a laboratory scale cascaded tanks process, where the Kalman based method was used for initialization.

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  • 120.
    Brus, Linda
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Constrained ODE modeling and Kalman filtering for recursive identification of nonlinear systems2006Conference paper (Refereed)
  • 121.
    Brus, Linda
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Carlsson, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Initialization of a nonlinear identification algorithm applied to laboratory plant data2008In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 16, no 4, p. 708-716Article in journal (Refereed)
  • 122.
    Brus, Linda
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Carlsson, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Kalman filtering for black-box identification of nonlinear ODE models2006In: Proc. Reglermöte, 2006Conference paper (Other academic)
  • 123. Brus, Linda
    et al.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Zambrano, Darine
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Feedforward model predictive control of a non-linear solar collector plant with varying delays2010In: IET Control Theory and Applications, ISSN 1751-8644, Vol. 4, no 8, p. 1421-1435Article in journal (Refereed)
  • 124. Brus, Linda
    et al.
    Zambrano, Darine
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Black-box identification of solar collector dynamics with variant time delay2010In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 18, no 10, p. 1133-1146Article in journal (Refereed)
  • 125.
    Bydell, Sofie
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Extension of the Benchmark Simulation Model no. 2 with a model for chemical precipitation of phosphorus2013Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    At present, there are more than 2000 wastewater treatments plants (WWTPs) in Sweden. Emissions of nitrogen and phosphorus from these, do contribute to the eutrophication of the Baltic Sea and watercourses on a daily basis. To reduce emissions of phosphorus, the Swedish approach has for the last 50 years been to use chemical precipitation.

    Today, software is used to test and evaluate different strategies in WWTPs, this in order to improve the operation and get a holistic view over the process. One model that can be used to achieve a holistic view is the Benchmark Simulation Model No. 2 (BSM2). In order to get a software like BSM2 to best mirror the reality, it is important that the model well describes the actual process. Today, BSM2 does not take the load of phosphorus into account, which, if it was included in the model, would describe the process better.

    In this master thesis, the author has investigated the possibility of extending the BSM2 model, to include phosphorus and chemical precipitation. Thereafter the results from simulations in BSM2 were compared with measurements from Henriksdals WWTP in Stockholm.

    The results showed that a model, after some simplifications, for phosphorus and chemical precipitation could be included in BSM2. The model uses primary precipitation. Precipitation chemical was added with assistance of a PI controller. Generally the results showed that the model had potential to describe the total flow of phosphorus in the WWTP. In measurements from Henriksdal the average total phosphorus effluent from primary and secondary sedimentation were 3.97 and 0.43 mg/l, respectively. From a steady state simulation in BSM2 the values were ​​4.26 and 0.44 mg/l and the average values ​​of a dynamic simulation 3.96 and 0.46 mg/l.

    Although the average values of total phosphorus matches quite well, it was found difficult to simulate the different fractions of phosphorus effluent from the secondary sedimentation. In order to better evaluate the results and how the simplifications of the model affects them, more measurements need to be done and a comparison with the results received from the BSM2 needs to be carried out. Also an adjustment of parameters in BSM2 must be done, this to achieve a better compliance with the given plant.

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    SofieBydell
  • 126.
    Bånkestad, Maria
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. RISE Research Institutes of Sweden.
    Sjölund, Jens
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Taghia, Jalil
    Schön, Thomas B.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Artificial Intelligence.
    Variational Elliptical Processes2023In: Transactions on Machine Learning Research, E-ISSN 2835-8856Article in journal (Refereed)
    Abstract [en]

    We present elliptical processes—a family of non-parametric probabilistic models that subsumes Gaussian processes and Student's t processes. This generalization includes a range of new heavy-tailed behaviors while retaining computational tractability. Elliptical processes are based on a representation of elliptical distributions as a continuous mixture of Gaussian distributions. We parameterize this mixture distribution as a spline normalizing flow, which we train using variational inference. The proposed form of the variational posterior enables a sparse variational elliptical process applicable to large-scale problems. We highlight advantages compared to Gaussian processes through regression and classification experiments. Elliptical processes can supersede Gaussian processes in several settings, including cases where the likelihood is non-Gaussian or when accurate tail modeling is essential.

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    Fulltext
  • 127.
    Caiado, Daniela V.
    et al.
    IST/INESC-ID.
    Lemos, Joao M.
    IST/INESC-ID, Lisbon, Portugal.
    Costa, Bertinho A.
    IST/INESC-ID, Lisbon, Portugal.
    Martins da Silva, Margarida
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Mendonça, Teresa
    Departamento de Matematica, Faculdade de Ciencias, Universidade do Porto, Porto, Portugal.
    Design of depth of anesthesia controllers in the presence of model uncertainty2013In: Proc. 21st Mediterranean Conference on Control and Automation, 2013, p. 213-218Conference paper (Refereed)
  • 128.
    Calafat, Francisco M.
    et al.
    Natl Oceanog Ctr, Joseph Proudman Bldg,6 Brownlow St, Liverpool L3 5DA, Merseyside, England.
    Wahl, Thomas
    Univ Cent Florida, Natl Ctr Integrated Coastal Res, 12800 Pegasus Dr,Suite 211, Orlando, FL 32816 USA;Univ Cent Florida, Dept Civil Environm & Construct Engn, 12800 Pegasus Dr,Suite 211, Orlando, FL 32816 USA.
    Lindsten, Fredrik
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Williams, Joanne
    Natl Oceanog Ctr, Joseph Proudman Bldg,6 Brownlow St, Liverpool L3 5DA, Merseyside, England.
    Frajka-Williams, Eleanor
    Univ Southampton, Ocean & Earth Sci, European Way, Southampton SO14 3ZH, Hants, England.
    Coherent modulation of the sea-level annual cycle in the United States by Atlantic Rossby waves2018In: Nature Communications, E-ISSN 2041-1723, Vol. 9, article id 2571Article in journal (Refereed)
    Abstract [en]

    Changes in the sea-level annual cycle (SLAC) can have profound impacts on coastal areas, including increased flooding risk and ecosystem alteration, yet little is known about the magnitude and drivers of such changes. Here we show, using novel Bayesian methods, that there are significant decadal fluctuations in the amplitude of the SLAC along the United States Gulf and Southeast coasts, including an extreme event in 2008-2009 that is likely (probability = 68%) unprecedented in the tide-gauge record. Such fluctuations are coherent along the coast but decoupled from deep-ocean changes. Through the use of numerical and analytical ocean models, we show that the primary driver of these fluctuations involves incident Rossby waves that generate fast western-boundary waves. These Rossby waves project onto the basin-wide upper mid-ocean transport (top 1000 m) leading to a link with the SLAC, wherein larger SLAC amplitudes coincide with enhanced transport variability.

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    fulltext
  • 129. Carlemalm, Catharina
    et al.
    Halvarsson, Susanne
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wahlberg, Bo
    Algorithms for time delay estimation using a low complexity exhaustive search1999In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 44, no 5, p. 1031-1037Article in journal (Refereed)
  • 130.
    Carlsson, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    On keeping the average of an effluent concentration below a limit2022Conference paper (Refereed)
  • 131.
    Carlsson, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Resource efficient operation of a class of wastewater treatment processes2010In: Proc. 2nd IWA Water and Energy Conference, International Water Association , 2010, p. 96-97Conference paper (Refereed)
  • 132.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Diehl, Stefan
    Zambrano, Jesús
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Analyses of Activated Sludge Processes Consisting of a Plug-Flow Reactor and a Non-ideal Settler2015In: Proc. 9th IWA Symposium on Systems Analysis and Integrated Assessment, 2015Conference paper (Other academic)
    Abstract [en]

    An activated sludge process (ASP) consisting of a plug-flow reactor (PFR) and a non-ideal settler is modelled and analysed. One soluble substrate component and one particulate biomass are assumed. The biomass growth rate is described by a Monod function. The settler model includes hindered settling and compression. A model describing the steady-state behaviour of the ASP is derived which constrains the settler to work with a fixed sludge blanket height in the thickening zone. The model provides new understanding for these types of ASPs and may be used for novel design schemes. The numerical example suggests that the steady-state solutions of the ASP give a one-parameter family of solutions, where the parameter is the recycle ratio r.

  • 133.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Maixa, Mikel
    DIAMOND: AdvanceD data management and InformAtics for the optimuM operatiON anD control of WWTPs2013In: 11th IWA conference on Instrumentation, Control and Automation, 2013Conference paper (Refereed)
    Abstract [en]

    This paper introduces a recently begun and very promising project on data management in wastewater treatment plants (WWTPs). The current lack of appropriate data management tools is clearly limiting broader implementation and efficient use of new sensors, monitoring systems and process controllers in WWTPs. The present project addresses the design, development, implementation and validation of a new advanced data management platform. This paper introduces the aims of the project and the proposed technical solution, summarises the project’s current status, progress made and working plan and provides general information about the project.

  • 134.
    Carlsson, Bengt
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. DEPARTMENT OF SYSTEMS AND CONTROL.
    Milocco, RH
    A simple strategy for controlling the nitrate concentration in an activated sludge process using external carbon flow rate2001In: LATIN AMERICAN APPLIED RESEARCH, ISSN 0327-0793, Vol. 31, no 2, p. 115-120Article in journal (Refereed)
    Abstract [en]

    Biological nitrogen removal in an activated sludge process is obtained by two biological processes; nitrification and denitrification. Denitrifing bacteria need an anoxic environment and access to an organic energy source in order to convert nitrate to ni

  • 135.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Molin, Hanna
    Lindblom, Eric
    Jeppsson, Ulf
    Saagi, Ramesh
    Process Monitoring And Fault Detection Using A Soft Sensor For The Return Activated Sludge Flow Rate2022Conference paper (Refereed)
  • 136.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Nygren, Johannes
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Increasing the number of DO sensors for aeration control in wastewater treatment: how much is gained?2013In: 11th IWA conference on Instrumentation, Control and Automation, 2013Conference paper (Refereed)
  • 137.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Olsson, Gustaf
    Instrumentation, Control and Automation in wastewater—from London 1973 to Narbonne 20132013In: 11th IWA conference on Instrumentation, Control and Automation, 2013Conference paper (Refereed)
    Abstract [en]

    Key developments of instrumentation, control and automation (ICA) applications in wastewater systems during the past 40 years are highlighted in this paper. From the first ICA conference in 1973 through to today there has been a tremendous increase in the understanding of the processes, instrumentation, computer systems and control theory. Still many developments have not been addressed here, such as sewer control, drinking water treatment and water distribution control. It is the hope that this short review can stimulate new attempts to more effectively apply control and automation in water systems in the coming years.

  • 138.
    Carlsson, Bengt
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. SYSTEMS AND CONTROL.
    Rehnström, A
    Control of an activatedsludge process with nutrient removal - A benchmark study2002In: Water, Science and Technology, Vol. 45, no 4-5, p. 135-142Article in journal (Refereed)
  • 139.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    On-line identification of the dissolved oxygen dynamics in an activated sludge process1993Conference paper (Refereed)
  • 140.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    On-line identification of the dissolved oxygen dynamics in an activated sludge process1992Report (Other academic)
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    fulltext
  • 141.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Zambrano, Jesús
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Analysis of simple bioreactor models: A comparison between Monod and Contois kinetics2014In: Proc. IWA Conference on Activated Sludge – 100 Years and Counting, IWA Publishing, 2014Conference paper (Refereed)
    Abstract [en]

    In this paper, an analysis of simple bioreactors in series is presented. The bioreactors are analysed for growth kinetics of the biomass described by a Monod and a Contois function. In particular, it is studied how the effluent substrate concentration is depending on the influent substrate concentration during steady state. It is shown that by going from one to two bioreactors in series completely changes the process behaviour when the growth kinetics is described by a Monod function. It is also shown that a bioreactor described by Contois kinetics has a completely different behaviour compared with the Monod case.

  • 142.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Zambrano, Jesús
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Fault detection and isolation of sensors in aeration control systems2016In: Water Science and Technology, ISSN 0273-1223, E-ISSN 1996-9732, Vol. 73, no 3, p. 648-653Article in journal (Refereed)
    Abstract [en]

    In this paper, we consider the problem of fault detection (FD) and isolation in the aeration system of an activated sludge process. For this study, the dissolved oxygen in each aerated zone is assumed to be controlled automatically. As the basis for an FD method we use the ratio of air flow rates into different zones. The method is evaluated in two scenarios: using the Benchmark Simulation Model no. 1 (BSM1) by Monte Carlo simulations and using data from a wastewater treatment plant. The FD method shows good results for a correct and early FD and isolation.

  • 143.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Zambrano, Jesús
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Fault detection and isolation of sensors in aeration control systems2014In: Proc. IWA World Water Congress: 2014, IWA Publishing, 2014Conference paper (Refereed)
    Abstract [en]

    In this paper, we consider the problem of fault detection and isolation in the aeration system of an activated sludge process. The purpose is to detect and localize possible faults in dissolved oxygen and air flow sensors. The dissolved oxygen in each aerated zone is assumed to be controlled automatically. As the basis for a fault detection algorithm we use the ratio of air flow rates into different zones. The method is evaluated in two scenarios: using the Benchmark Simulation Model nº 1 by Monte Carlo simulations, and using data from a wastewater treatment plant. The fault detection method shows good results for a correct and early fault detection and isolation.

  • 144.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Zambrano, Jesús
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Fault detection of sensors in aeration control systems: the airflow ratio method2013In: 11th IWA conference on Instrumentation, Control and Automation, 2013Conference paper (Refereed)
    Abstract [en]

    A fault detection method, ARM, has been proposed for detection of faults in DOsensors in a serie of aerated zones. The DO in each zone is assumed to be controlled. In a simulation study, ARM shows promising results for correct and early fault detection. Eventually, it will not be possible to distinguish between a fault in a DOsensor and in air flow rate sensor. In this study, we have, for simplicity, used KLa as a measure of the air flow rate. In practice an air flow rate sensor should be used. An interesting alternative is to use the air valve position instead of the airflow rate.

  • 145.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Åmand, Linda
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Long-term evaluation of full-scale ammonium control in three large WWTPs2013In: 11th IWA conference on Instrumentation, Control and Automation, 2013Conference paper (Refereed)
  • 146.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Åmand, Linda
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Parameter scheduling in ammonium feedback control2013In: 11th IWA conference on Instrumentation, Control and Automation, 2013Conference paper (Refereed)
    Abstract [en]

    Parameter scheduling is a method to change controller settings depending on the process state. This study investigates the feasibility for parameter scheduling in a number of ammonium feedback strategies to improve disturbance rejection during peak load events. The controllers investigated by simulation are fast ammonium control, floating ammonium control and a moving average controller. A controller similar to the floating ammonium controller is also tested in a full-scale plant. The scheduling changes the upper bound on the DO set-point or the controller gain and integral time when effluent ammonium reaches a specified level. By this scheduling strategy the average ammonium concentration is decreased by up to 9%. The moving average controller showed the most promising results, but the results depend on the dissolved oxygen half saturation constant.

  • 147.
    Carlsson, Bengt
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.
    Åmand, Linda
    Arnell, Magnus
    Jeppsson, Ulf
    The story of Gustaf – from the early days to his emeritus adventures2022In: Celebrating passion for Water, Science and Technology: Festschrift in Honour of Gustaf Olsson / [ed] Wolfgang Rauch; Pernille Ingildsen, IWA Publishing, 2022, p. 43-53Chapter in book (Refereed)
  • 148. Carotenuto, Vincenzo
    et al.
    De Maio, Antonio
    Orlando, Danilo
    Stoica, Peter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Model order selection rules for covariance structure classification in radar2017In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 20, p. 5305-5317Article in journal (Refereed)
  • 149. Carotenuto, Vincenzo
    et al.
    De Maio, Antonio
    Orlando, Danilo
    Stoica, Peter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Radar detection architecture based on interference covariance structure classification2019In: IEEE Transactions on Aerospace and Electronic Systems, ISSN 0018-9251, E-ISSN 1557-9603, Vol. 55, no 2, p. 607-618Article in journal (Refereed)
  • 150. Cea, Mauricio G.
    et al.
    Goodwin, Graham C.
    Wigren, Torbjörn
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Model predictive zooming power control in future cellular systems under coarse quantization2012In: Proc. 76th Vehicular Technology Conference, Piscataway, NJ: IEEE, 2012Conference paper (Refereed)
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