Adaptive control: stability, convergence, and robustness
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Neural networks for control systems: a survey
Automatica (Journal of IFAC)
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
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Information Sciences—Informatics and Computer Science: An International Journal
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Information Sciences: an International Journal
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IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
IEEE Transactions on Fuzzy Systems
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
Adaptive control of a class of nonlinear systems with nonlinearly parameterized fuzzy approximators
IEEE Transactions on Fuzzy Systems
Modeling, identification, and control of a class of nonlinear systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Supervisory recurrent fuzzy neural network control of wing rock for slender delta wings
IEEE Transactions on Fuzzy Systems
Pseudoerror-based self-organizing neuro-fuzzy system
IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Fuzzy Systems
Adaptive Synchronization of Uncertain Chaotic Systems Based on T–S Fuzzy Model
IEEE Transactions on Fuzzy Systems
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IEEE Transactions on Neural Networks
Direct adaptive controller for nonaffine nonlinear systems using self-structuring neural networks
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
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This paper proposes a self-organizing adaptive fuzzy neural control (SAFNC) for the synchronization of uncertain chaotic systems with random-varying parameters. The proposed SAFNC system is composed of a computation controller and a robust controller. The computation controller containing a self-organizing fuzzy neural network (SOFNN) identifier is the principle controller. The SOFNN identifier is used to online estimate the compound uncertainties with the structure and parameter learning phases of fuzzy neural network (FNN), simultaneously. The structure-learning phase consists of the growing of membership functions, the splitting of fuzzy rules and the pruning of fuzzy rules, and thus the SOFNN identifier can avoid the time-consuming trial-and-error tuning procedure for determining the network structure of fuzzy neural network. The robust controller is used to attenuate the effects of the approximation error so that the synchronization of chaotic systems is achieved. All the parameter learning algorithms are derived based on the Lyapunov stability theorem to ensure network convergence as well as stable synchronization performance. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper.