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Adaptive control design for MIMO switched nonlinear systems with full state constraints
Author(s) -
Chen Aiqing,
Liu Lei,
Liu YanJun
Publication year - 2019
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.3051
Subject(s) - backstepping , control theory (sociology) , bounded function , nonlinear system , fuzzy logic , mimo , controller (irrigation) , mathematics , lyapunov function , fuzzy control system , adaptive control , tracking error , state (computer science) , computer science , control (management) , algorithm , artificial intelligence , physics , quantum mechanics , beamforming , mathematical analysis , statistics , agronomy , biology
Summary This paper presents an adaptive fuzzy control approach of multiple‐input–multiple‐output (MIMO) switched uncertain systems, which involve time‐varying full state constraints (TFSCs) and unknown disturbances. In the design procedure, the fuzzy logic systems are adopted to approximate the unknown functions in the systems. The adaptive fuzzy controller is set up by backstepping technique. According to the tangent barrier Lyapunov function (BLF‐Tan), a novel adaptive MIMO switched nonlinear control algorithm is designed. Under the rule of arbitrary switchings and the proposed control laws, it is demonstrated that all signals in the resulted system are semiglobally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of zero with TFSCs. Furthermore, the simulation example validates the effectiveness of presented control strategy.