Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Fuzzy adaptive control of multivariable nonlinear systems
Fuzzy Sets and Systems
Fuzzy adaptive output feedback control for MIMO nonlinear systems
Fuzzy Sets and Systems
Observer-based adaptive fuzzy-neural control for unknown nonlineardynamical systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Output tracking and regulation of nonlinear system based onTakagi-Sugeno fuzzy model
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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
Stable adaptive control using fuzzy systems and neural networks
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Interval type-2 fuzzy logic systems: theory and design
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
Nonlinear adaptive trajectory tracking using dynamic neural networks
IEEE Transactions on Neural Networks
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Synchronization of uncertain chaotic systems based on adaptive type-2 fuzzy sliding mode control
Engineering Applications of Artificial Intelligence
Review: Industrial applications of type-2 fuzzy sets and systems: A concise review
Computers in Industry
Information Sciences: an International Journal
Fire-rule-based direct adaptive type-2 fuzzy H∞ tracking control
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
Adaptive H8 Fuzzy Control for a Class of Uncertain Discrete-Time Nonlinear Systems
International Journal of Artificial Life Research
Exact inversion of decomposable interval type-2 fuzzy logic systems
International Journal of Approximate Reasoning
System Identification Based on Dynamical Training for Recurrent Interval Type-2 Fuzzy Neural Network
International Journal of Fuzzy System Applications
Overview of Type-2 Fuzzy Logic Systems
International Journal of Fuzzy System Applications
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A fuzzy logic controller equipped with a training algorithm is developed such that the H∞ tracking performance should be satisfied for a model-free nonlinear multiple-input multiple-output (MIMO) system, with external disturbances. Due to universal approximation theorem, fuzzy control provides nonlinear controller, i.e., fuzzy logic controllers, to perform the unknown nonlinear control actions and the tracking error, because of the matching error and external disturbance is attenuated to arbitrary desired level by using H∞ tracking design technique. In this paper, a new direct adaptive interval type-2 fuzzy controller is developed to handle the training data corrupted by noise or rule uncertainties for nonlinear MIMO systems involving external disturbances. Therefore, linguistic fuzzy control rules can be directly incorporated into the controller and combine the H∞ attenuation technique. Simulation results show that the interval type-2 fuzzy logic system can handle unpredicted internal disturbance, data uncertainties, very well, but the adaptive type-1 fuzzy controller must spend more control effort in order to deal with noisy training data. Furthermore, the adaptive interval type-2 fuzzy controller can perform successful control and guarantee the global stability of the resulting closed-loop system and the tracking performance can be achieved.