1. Robust H∞ proportional-integral observer-based controller for uncertain LPV system
- Author
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Didier Theilliol, Manh-Hung Do, Damien Koenig, GIPSA - Safe, Controlled and Monitored Systems (GIPSA-SAFE), GIPSA Pôle Automatique et Diagnostic (GIPSA-PAD), Grenoble Images Parole Signal Automatique (GIPSA-lab), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Grenoble Alpes (UGA), Centre de Recherche en Automatique de Nancy (CRAN), and Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
0209 industrial biotechnology ,Integrated design ,Lemma (mathematics) ,Observer (quantum physics) ,Computer Networks and Communications ,Computer science ,Applied Mathematics ,Linear matrix inequality ,02 engineering and technology ,Fault (power engineering) ,[SPI.AUTO]Engineering Sciences [physics]/Automatic ,020901 industrial engineering & automation ,Control and Systems Engineering ,Control theory ,Signal Processing ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Observer based ,Majorization - Abstract
International audience; The main contribution of this paper is a robust integrated design of proportional - integral (PI) observer and state-feedback controller for uncertain linear parameter-varying (LPV) system. In this design, both fault estimation and robust feedback stabilization are developed. Moreover, since the state-feedback controller is derived from the PI observer, the loop transfer recovery (LTR) properties can be designed to maximize the closed-loop performance. Meanwhile, the PI observer and controller gains are simultaneously obtained from a linear matrix inequality (LMI), which is inferred from estimation errors, Young equality and majorization lemma implementation. Finally, its application to a vehicle suspension platform is presented to highlight the performances of the developed method.
- Published
- 2020
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