Composite anti-disturbance control for uncertain Markovian jump systems with actuator saturation based disturbance observer and adaptive neural network |
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| Authors: | Yunliang Wei Guo-Ping Liu Guangdeng Zong Hao Shen |
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| Institution: | 1. School of Mathematical Sciences, Qufu Normal University, Qufu, Shandong 273165, PR China;2. School of Engineering, University of South Wales, Cardiff 1DL, CF37, U.K.;3. CTGT Center, Harbin Institute of Technology, Harbin 150001, China;4. School of Engineering, Qufu Normal University, Rizhao, Shandong 276826, PR China;5. School of Electrical and Information Engineering, Anhui University of Technology, Maanshan 243002, China |
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| Abstract: | This paper studies the problem of composite control for a class of uncertain Markovian jump systems (MJSs) with partial known transition rates, multiple disturbances and actuator saturation. Compared with the existing results, a novel robust composite control scheme is put forward by virtue of adaptive neural network technique. For MJSs, the partial unknown information on transition rates and the actuator saturation influence the design of disturbance observer and the robust H∞ controller. Firstly, without taking account of external disturbances, the network reconstruction error and saturation, a novel robust adaptive control strategy is established to ensure that all the signals of the closed-loop system are asymptotically bounded in mean square. Secondly, the solvability condition for ensuring the robust H∞ performance is given by using a modified adaptive law, where the saturation is treated as a disturbance-like signal. Finally, the simulations for a numerical example and an application example are performed to validate the effectiveness of the proposed results. |
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| Keywords: | Corresponding author at: School of Mathematical Sciences Qufu Normal University Qufu Shandong 273165 PR China |
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