Hybrid multi-observer for improving estimation performance (Elena Petri, Université de Lorraine)

Systems & Control Seminar

• Thursday 22.06.2023, 10:30
• Room A247, Building 3403, Appelstr. 11

Abstract

Various methods are nowadays available to design observers for broad classes of systems, where the primary focus is on establishing the convergence of the estimated states. Nevertheless, the question of the tuning of the observer to achieve satisfactory estimation performance remains largely open. In this context, we present a general design framework for the online tuning of the observer gains. Our starting point is a robust nominal observer designed for a general nonlinear system, for which an input-to-state stability property can be established. Our goal is then to improve the performance of this nominal observer. We present for this purpose a new hybrid multi-observer scheme, whose great flexibility can be exploited to enforce various desirable properties, e.g., fast convergence and good sensitivity to measurement noise. We prove that an input-to-state stability property also holds for the proposed scheme and, importantly, we ensure that the estimation performance in terms of a quadratic cost is (strictly) improved. We illustrate the efficiency of the approach in improving the performance of a given high-gain observer in a numerical example. Moreover, we apply the proposed technique for the state estimation of an electrochemical lithium-ion battery, for which good estimation performance is extremely important.

Biographical information

Elena Petri is a PhD student in control engineering at CRAN, Université de Lorraine, CNRS, Nancy, France, under the supervision of Romain Postoyan (CRAN, CNRS, Université de Lorraine, France), Dragan Nesic (University of Melbourne, Australia) and Daniele Astolfi (LAGEPP, CNRS, Université Lyon 1, France). She received the bachelor degree in mechanics and mechatronics engineering and the master degree in mechatronics engineering from the University of Padova, Italy, in 2017 and 2020, respectively. Her research interests include observers, nonlinear systems and hybrid systems.