Adaptive fuzzy control for multi-input multi-output nonlinear systems with unknown dead-zone inputs |
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Affiliation: | 1. School of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China;2. Tianjin Key Laboratory of Advanced Technology of Electrical Engineering and Energy, Tianjin 300387, China;1. Département génie électrique, Ecole Mohamamdia d’Ingénieurs (EMI), Université Mohammed V Agdal, Rabat, Morocco;2. Laboratoire de Recherche en Economie de l’Energie, Environnement et Ressources, Département d’Economie, University Caddy Ayyad, Marrakech, Morocco;1. Simsoft Computer Technologies, Middle East Technical University, Teknokent Bolgesi, 06800 Ankara, Turkey;2. Microsoft, 1 Microsoft Way, Redmond, WA 98052, United States;3. Computer Engineering, Middle East Technical University, 06800 Ankara, Turkey;1. College of Finance, Nanjing Agricultural University, Nanjing 210095, Jiangsu, China;2. School of Economics and Management, Southeast University, Nanjing 210096, Jiangsu, China;1. College of Mathematics, Physics and Information Engineering, Jiaxing University, Jiaxing 314001, China;2. College of Engineering, Shaoxing University, Shaoxing 312000, China |
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Abstract: | This paper presents an adaptive fuzzy control scheme for a class of uncertain multi-input multi-output (MIMO) nonlinear systems with the nonsymmetric control gain matrix and the unknown dead-zone inputs. In this scheme, fuzzy systems are used to approximate the unknown nonlinear functions and the estimated symmetric gain matrix is decomposed into a product of one diagonal matrix and two orthogonal matrices. Based on the decomposition results, a controller is developed, therefore, the possible controller singularity problem and the parameter initialization condition constraints problem are avoided. In addition, a dynamic robust controller is employed to compensate for the lumped errors. It is proved that all the signals in the proposed closed-loop system are bounded and that the tracking errors converge asymptotically to zero. A simulation example is used to demonstrate the effectiveness of the proposed scheme. |
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Keywords: | Fuzzy control Adaptive control MIMO nonlinear system Matrix decomposition Unknown dead-zone inputs |
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