Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Computing and Applications
A neuro-fuzzy controller for speed control of a permanent magnet synchronous motor drive
Expert Systems with Applications: An International Journal
An expert system based on wavelet decomposition and neural network for modeling Chua's circuit
Expert Systems with Applications: An International Journal
Zero-order TSK-type fuzzy system learning using a two-phase swarm intelligence algorithm
Fuzzy Sets and Systems
CMAC-based neuro-fuzzy approach for complex system modeling
Neurocomputing
A growing and pruning method for radial basis function networks
IEEE Transactions on Neural Networks
Radial basis function networks with hybrid learning for system identification with outliers
Applied Soft Computing
Radial basis function neural network-based adaptive critic control of induction motors
Applied Soft Computing
Adaptive dynamic RBF neural controller design for a class of nonlinear systems
Applied Soft Computing
Neural–Fuzzy Gap Control for a Current/Voltage-Controlled 1/4-Vehicle MagLev System
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Fuzzy Systems
Supervisory recurrent fuzzy neural network control of wing rock for slender delta wings
IEEE Transactions on Fuzzy Systems
A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation
IEEE Transactions on Neural Networks
Observer-based direct adaptive fuzzy-neural control for nonaffine nonlinear systems
IEEE Transactions on Neural Networks
Self-Organizing Adaptive Fuzzy Neural Control for a Class of Nonlinear Systems
IEEE Transactions on Neural Networks
A high speed railway control system based on the fuzzy control method
Expert Systems with Applications: An International Journal
Linear and sigmoidal fuzzy cognitive maps: An analysis of fixed points
Applied Soft Computing
Review Article: Applications of neuro fuzzy systems: A brief review and future outline
Applied Soft Computing
| Hi-index | 0.00 |
Many published papers show that a TSK-type fuzzy system provides more powerful representation than a Mamdani-type fuzzy system. Radial basis function (RBF) network has a similar feature to the fuzzy system. As this result, this article proposes a dynamic TSK-type RBF-based neural-fuzzy (DTRN) system, in which the learning algorithm not only online generates and prunes the fuzzy rules but also online adjusts the parameters. Then, a supervisory adaptive dynamic RBF-based neural-fuzzy control (SADRNC) system which is composed of a DTRN controller and a supervisory compensator is proposed. The DTRN controller is designed to online estimate an ideal controller based on the gradient descent method, and the supervisory compensator is designed to eliminate the effect of the approximation error introduced by the DTRN controller upon the system stability in the Lyapunov sense. Finally, the proposed SADRNC system is applied to control a chaotic system and an inverted pendulum to illustrate its effectiveness. The stability of the proposed SADRNC scheme is proved analytically and its effectiveness has been shown through some simulations.