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Simultaneous Estimation of State and Unknown Input with Hinfinity Guarantee on Error-Bounds for Fuzzy Descriptor Systems

Abstract : This paper proposes a new l_infty observer design for fuzzy descriptor systems with unknown inputs. The descriptor form is treated using a singular redundancy system representation. To keep the consistency of the resulting fuzzy observer structure, we make use of a virtual variable playing the role of the one-step ahead state estimate. As a result, the observer gain can be constructed with free-structure decision variables to reduce the design conservatism. Using a fuzzy-basis-dependent Lyapunov function, the observer design is reformulated as a convex optimization problem with a single line search parameter. In particular, the error bounds of both the state and the unknown input estimations can be minimized through the guaranteed l_infty performance level. The effectiveness of the our result is demonstrated with a challenging application on robot manipulators.
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https://hal-uphf.archives-ouvertes.fr/hal-03467577
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Submitted on : Monday, December 6, 2021 - 3:44:59 PM
Last modification on : Sunday, June 26, 2022 - 3:23:00 AM

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  • HAL Id : hal-03467577, version 1

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Tran Anh-Tu Nguyen, Thierry-Marie Guerra, Victor Campos. Simultaneous Estimation of State and Unknown Input with Hinfinity Guarantee on Error-Bounds for Fuzzy Descriptor Systems. 58th Conference on Decision and Control, Dec 2019, Nice, France. ⟨hal-03467577⟩

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