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On Maximum Stability Margin Design of Nonlinear Uncertain Systems: Fuzzy Control Approach
Author(s) -
Tseng ChungShi,
Chen BorSen,
Uang HueyJian
Publication year - 2001
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1111/j.1934-6093.2001.tb00058.x
Subject(s) - control theory (sociology) , fuzzy logic , nonlinear system , fuzzy control system , mathematics , margin (machine learning) , parameterized complexity , linear matrix inequality , mathematical optimization , stability (learning theory) , convex optimization , computer science , regular polygon , control (management) , algorithm , artificial intelligence , physics , geometry , quantum mechanics , machine learning
This paper studies the maximum stability margin design for nonlinear uncertain systems using fuzzy control. First, the Takagi and Sugeno fuzzy model is employed to approximate a nonlinear uncertain system. Next, based on the fuzzy model, the maximum stability margin for a nonlinear uncertain system is studied to achieve as much tolerance of plant uncertainties as possible using a fuzzy control method. In the proposed fuzzy control method, the maximum stability margin design problem is parameterized in terms of a corresponding generalized eigenvalue problem (GEVP). For the case where state variables are unavailable, a fuzzy observer‐based control scheme is also proposed to deal with the maximum stability margin for nonlinear uncertain systems. Using a suboptimal approach, we characterize the maximum stability margin via fuzzy observer‐based control in terms of a linear matrix inequality problem (LMIP). The GEVP and LMIP can be solved very efficiently via convex optimization techniques. Simulation examples are given to illustrate the design procedure of the proposed method.