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Fuzzy descriptor tracking control with guaranteed L∞ error-bound for robot manipulators

Abstract : This paper is concerned with the nonlinear tracking control design for robot manipulators. In spite of the rich literature in the field, the problem has not yet been addressed adequately due to the lack of an effective control design. Using a descriptor fuzzy model-based framework, we propose a new approach to design a feedback-feedforward control scheme for robot manipulators in a general form. The goal is to guarantee a small level of an [Formula: see text] gain specification to improve the tracking performance while significantly reducing the numerical complexity for real-time implementation. Based on Lyapunov stability arguments, the control design is formulated as a convex optimization problem involving linear matrix inequalities. Numerical experiments performed with a high-fidelity manipulator benchmark model, embedded in the Simscape Multibody TM environment, demonstrate the effectiveness of the proposed control solution over existing standard approaches.
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Submitted on : Monday, January 17, 2022 - 8:30:19 AM
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Tran Anh-Tu Nguyen, Antoine Dequidt, van Anh Nguyen Thi, Laurent Vermeiren, Michel Dambrine. Fuzzy descriptor tracking control with guaranteed L∞ error-bound for robot manipulators. Transactions of the Institute of Measurement and Control, SAGE Publications, 2021, 43 (6), pp.1404-1415. ⟨10.1177/0142331220979262⟩. ⟨hal-03527996⟩



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