Abstract
In this paper, we present a robust observer design for Lipschitz nonlinear systems subject to parametric uncertainties and external disturbance, with its application to state estimation of an induction motor. First, the developed approach combined the differential mean value theorem with sector nonlinearity transformation to reformulate the nonlinearity term in the estimation error dynamics into a convex combination of vertex matrices as quasi-linear parameter varying system. Then by using an extension of H∞ criterion and pole placement technique, less conservative and sufficient stability conditions of the studied observer are derived and cast in terms of linear matrix inequalities (LMIs). Next, the observer gain is computed offline by solving these LMIs through the YALMIP software. Finally, the results of simulation were carried out with three scenarios to demonstrate the efficiency and effectiveness of our technique and to show its superiority in terms of robustness compared to others methods previously reported in some literature.
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The authors would like to thank the Algerian General Direction of Research DGRDT for their financial support and LIAS laboratory of Poitiers, France for its technical support.
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Nacer, M.L., Kherfane, H., Moreau, S. et al. Robust Observer Design for Uncertain Lipschitz Nonlinear Systems Based on Differential Mean Value Theorem: Application to Induction Motors. J Control Autom Electr Syst 32, 132–144 (2021). https://doi.org/10.1007/s40313-020-00658-w
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DOI: https://doi.org/10.1007/s40313-020-00658-w