Stability analysis and design of fuzzy control systems
Fuzzy Sets and Systems
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Nonlinear control design: geometric, adaptive and robust
Nonlinear control design: geometric, adaptive and robust
Essentials of Fuzzy Modeling and Control
Essentials of Fuzzy Modeling and Control
New approaches on H∞ control of T--S fuzzy systems with interval time-varying delay
Fuzzy Sets and Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach
IEEE Transactions on Fuzzy Systems
Stabilizing controller design for uncertain nonlinear systems using fuzzy models
IEEE Transactions on Fuzzy Systems
Analysis and synthesis of nonlinear time-delay systems via fuzzy control approach
IEEE Transactions on Fuzzy Systems
Mixed H2/H∞ fuzzy output feedback control design for nonlinear dynamic systems: an LMI approach
IEEE Transactions on Fuzzy Systems
Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model
IEEE Transactions on Fuzzy Systems
H∞ fuzzy output feedback control design for nonlinear systems: an LMI approach
IEEE Transactions on Fuzzy Systems
Delay-Dependent Robust Control for T–S Fuzzy Systems With Time Delay
IEEE Transactions on Fuzzy Systems
Robust H∞ Control for Uncertain Takagi–Sugeno Fuzzy Systems With Interval Time-Varying Delay
IEEE Transactions on Fuzzy Systems
H∞ output tracking fuzzy control for nonlinear systems with time-varying delay
Applied Soft Computing
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This paper studies H∞ fuzzy output tracking control problem for delayed nonlinear systems using Takagi-Sugeno fuzzy modeling. The H∞ performance has been achieved using Fuzzy Performance Evaluator FPE and the sufficient conditions are presented in terms of delay dependent Linear Matrix Inequalities LMIs. The delay interval is decomposed into multiple equidistant subintervals and Lyapunov-Krasovskii functionals LKFs are constructed on these intervals to obtain the conditions. Thereby the formulated model traces the given nonlinear dynamical system exactly to a T-S fuzzy model with very less error bound approaching zero asymptotically. Finally, with numerical open and closed loop tests on continuous stirred tank reactors CSTR model reveal that the method proposed in this study is more effective.