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期刊名称: IEEE Transactions on Fuzzy Systems
Volume:23    Issue:4        Page:1228-1241
ISSN:1063-6706

Observer-Based Adaptive Fuzzy Tracking Control of MIMO Stochastic Nonlinear Systems With Unknown Control Directions and Unknown Dead Zones期刊论文

作者: Yongming Li Shaocheng Tong Tieshan Li
DOI:10.1109/TFUZZ.2014.2348017

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页码: 1228-1241
被引频次: 284
出版者: IEEE,IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC,The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
期刊名称: IEEE Transactions on Fuzzy Systems
ISSN: 1063-6706
卷期: Volume:23    Issue:4
语言: English
摘要: In this paper, an adaptive fuzzy backstepping output-feedback tracking control approach is proposed for a class of multi-input and multi-output (MIMO) stochastic nonlinear systems. The MIMO stochastic nonlinear systems under study are assumed to possess unstructured uncertainties, unknown dead-zones, and unknown control directions. By using a linear state transformation, the unknown control coefficients and the unknown slopes characteristic of the dead-zones are lumped together, and the original system is transformed to a new system on which the control design becomes feasible. Fuzzy logic systems are used to approximate the unstructured uncertainties, and a fuzzy state observer is designed to estimate the unmeasured states. By introducing a special Nussbaum gain function into the backstepping control design, a stable adaptive fuzzy output-feedback tracking control scheme is developed. The main features of the proposed adaptive control approach are that it can guarantee the stability of the closed-loop system, and the tracking errors converge to a small neighborhood of zero. Moreover, it can solve the problems of unknown control direction, unknown dead-zone, and unmeasured states simultaneously. Two simulation examples are provided to show the effectiveness of the proposed approach.
相关主题: Fuzzy logic, Observers, Adaptive systems, Backstepping, Control design, Nonlinear systems, NEURAL-CONTROL, DELAY SYSTEMS, OUTPUT-FEEDBACK CONTROL, DESIGN, BACKSTEPPING CONTROL, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, Adaptive output-feedback tracking control, ENGINEERING, ELECTRICAL & ELECTRONIC, unknown control directions, DYNAMIC SURFACE CONTROL, unknown dead-zones, fuzzy logic systems (FLS), multi-input multi-output (MIMO) stochastic nonlinear systems, MIMO (control systems), Nonlinear dynamics, Control systems, Stochasticity, Tracking control, Dynamical systems, Adaptive control systems,

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