Stability analysis and design of fuzzy control systems
Fuzzy Sets and Systems
Analysis and design of fuzzy control system
Fuzzy Sets and Systems
Fuzzy rules emulated network and its application on nonlinear control systems
Applied Soft Computing
A novel parametric fuzzy CMAC network and its applications
Applied Soft Computing
A genetic-fuzzy approach for mobile robot navigation among moving obstacles
International Journal of Approximate Reasoning
Stable adaptive fuzzy controllers with application to inverted pendulum tracking
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Observer-based adaptive fuzzy-neural control for unknown nonlineardynamical systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Credit assigned CMAC and its application to online learning robust controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive control for uncertain nonlinear systems based on multiple neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive CMAC-based supervisory control for uncertain nonlinear systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust and fast learning for fuzzy cerebellar model articulation controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
RCMAC-Based Adaptive Control for Uncertain Nonlinear Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive fuzzy sliding mode control of nonlinear system
IEEE Transactions on Fuzzy Systems
The adaptive control of nonlinear systems using the Sugeno-type of fuzzy logic
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A Survey on Analysis and Design of Model-Based Fuzzy Control Systems
IEEE Transactions on Fuzzy Systems
Learning convergence of CMAC technique
IEEE Transactions on Neural Networks
Generalizing CMAC architecture and training
IEEE Transactions on Neural Networks
Direct adaptive control of partially known nonlinear systems
IEEE Transactions on Neural Networks
Learning convergence in the cerebellar model articulation controller
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, a novel scheme of incorporating a learning mechanism into previous step supervisory controllers for adaptive fuzzy control is proposed to relax bounds required in the control process. In traditional supervisory adaptive fuzzy control approaches, the use of fuzzy estimators for approximating system functions and a robust supervisory control law are necessary to deal with any possible uncertainties caused in the system. This kind of supervisory controller depends on the robust bounds of system functions so that it can ensure the Lyapunov stability of controlled systems. However, in those approaches, the output may not be able to follow the reference trajectory well if the robust bounds are predicted improperly. In our implementation, CMAC (Cerebellar Model Articulation Controllers) is used as the learning mechanism because of its quick learning capability. Under the Lyapunov stable criterion, the proposed CMAC learning mechanism can improve the output performance and can relax the robust bound limitation so that practical systems can easily be realized. In summary, the proposed approach not only can relax bounds for previous step supervisory controllers in adaptive fuzzy control, but also can significantly improve the control performance of the system.