A stability approach to fuzzy control design for nonlinear systems
Fuzzy Sets and Systems
Theory of the fuzzy controller
Fuzzy Sets and Systems
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Direct adaptive interval type-2 fuzzy control of multivariable nonlinear systems
Engineering Applications of Artificial Intelligence
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Engineering Applications of Artificial Intelligence
Type-2 FLCs: A New Generation of Fuzzy Controllers
IEEE Computational Intelligence Magazine
Type-2 Fuzzy Sets and Systems: An Overview [corrected reprint]
IEEE Computational Intelligence Magazine - Corrected Reprint
Adaptive hybrid intelligent control for uncertain nonlinear dynamical systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach
IEEE Transactions on Fuzzy Systems
Interval type-2 fuzzy logic systems: theory and design
IEEE Transactions on Fuzzy Systems
Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Stable adaptive fuzzy control of nonlinear systems
IEEE Transactions on Fuzzy Systems
Stable neural-network-based adaptive control for sampled-data nonlinear systems
IEEE Transactions on Neural Networks
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
IEEE Transactions on Neural Networks
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In this paper, an adaptive interval type-2 fuzzy controller is proposed for a class of unknown nonlinear discrete-time systems with training data corrupted by noise or rule uncertainties involving external disturbances. Adaptive interval type-2 fuzzy control scheme and control approach are incorporated to implement the main objective of controlling the plant to track a reference trajectory. The Laypunov stability theorem has been used to testify the asymptotic stability of the whole system and the free parameters of the adaptive fuzzy controller can be tuned on-line by an output feedback control law and adaptive laws. The overall adaptive scheme guarantees the global stability of the resulting closed-loop system in the sense that all signals involved are uniformly bounded. The simulation example is given to confirm validity and tracking performance of the advocated design methodology.