Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Robust decentralized nonlinear controller design for multimachine power systems
Automatica (Journal of IFAC)
An indirect model reference adaptive fuzzy control for SISO Takagi-Sugeno model
Fuzzy Sets and Systems - Modeling and control
Adaptive robust fuzzy control of nonlinear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
H∞ decentralized fuzzy model reference tracking control design for nonlinear interconnected systems
IEEE Transactions on Fuzzy Systems
Brief Robust tracking control for nonlinear MIMO systems via fuzzy approaches
Automatica (Journal of IFAC)
Decentralized H∞ filter design for discrete-time interconnected fuzzy systems
IEEE Transactions on Fuzzy Systems
Interval type 2 hierarchical FNN with the H-infinity condition for MIMO non-affine systems
Applied Soft Computing
Decentralized adaptive tracking control of nonaffine nonlinear large-scale systems with time delays
Information Sciences: an International Journal
Interaction analysis and loop pairing for MIMO processes described by T--S fuzzy models
Fuzzy Sets and Systems
State observer based dynamic fuzzy logic system for a class of SISO nonlinear systems
International Journal of Automation and Computing
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This paper describes an adaptive fuzzy control strategy for decentralized control for a class of interconnected nonlinear systems with MIMO subsystems. An adaptive robust tracking control schemes based on fuzzy basis function approach is developed such that all the states and signals are bounded. In addition, each subsystem is able to adaptively compensate for disturbances and interconnections with unknown bounds. The resultant adaptive fuzzy decentralized control with multi-controller architecture guarantees stability and convergence of the output errors to zero asymptotically by local output-feedback. An extensive application example of a three-machine power system is discussed in detail to verify the effectiveness of the proposed algorithm.