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  • 1.
    Chistiakova, Tatiana
    et al.
    Uppsala university, Uppsala, Sweden.
    Mattsson, Per
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    Carlsson, Bengt
    Uppsala university, Uppsala, Sweden.
    Wigren, Torbjörn
    Ericsson.
    Nonlinear system identification of the dissolved oxygen to effluent ammonia dynamics in an activated sludge process2017In: IFAC-PapersOnLine, ISSN 1045-0823, E-ISSN 1797-318X, Vol. 50, no 1, p. 3917-3922Article in journal (Refereed)
    Abstract [en]

    Aeration of biological reactors in wastewater treatment plants is important to obtain a high removal of soluble organic matter as well as for nitrification but requires a significant use of energy. It is hence of importance to control the aeration rate, for example, by ammonium feedback control. The goal of this paper is to model the dynamics from the set point of an existing dissolved oxygen controller to effluent ammonia using two types of system identification methods for a Hammerstein model, including a newly developed recursive variant. The models are estimated and evaluated using noise corrupted data from a complex mechanistic model (Activated Sludge Model no.1). The performance of the estimated nonlinear models are compared with an estimated linear model and it is shown that the nonlinear models give a significantly better fit to the data. The resulting models may be used for adaptive control (using the recursive Hammerstein variant), gain-scheduling control, L2 stability analysis, and model based fault detection.

  • 2.
    Olsson, Fredrik
    et al.
    Department of Information Technology, Uppsala University, Sweden.
    Halvorsen, Kjartan
    Department of Information Technology, Uppsala University, Sweden; Department of Mecatronics, Tecnológico de Monterrey, Mexico.
    Zachariah, Dave
    Department of Information Technology, Uppsala University, Sweden.
    Mattsson, Per
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.
    Identification of Nonlinear Feedback Mechanisms Operating in Closed Loop using Inertial Sensors2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 473-478Article in journal (Refereed)
    Abstract [en]

    In this paper we study the problem of identifying linear and nonlinear feedback mechanisms, or controllers, operating in closed loop. A recently developed identification method for nonlinear systems, the LAVA method, is used for this purpose. Identification data is obtained from inertial sensors, that provide information about the movement of the system, in the form of linear acceleration and angular velocity measurements. This information is different from the information that is available to the controller to be identified, which makes use of unknown internal sensors instead. We provide two examples, a simulated neuromuscular controller in standing human balance, and a lead-filter controlling a physical position servo using a DC motor. Both linear and nonlinear controllers are used in the examples. We show that the LAVA method is able to identify sparse, parsimonious models of the controllers.

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