Adaptive control: stability, convergence, and robustness
Adaptive control: stability, convergence, and robustness
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Nonlinear and Optimal Control Systems
Nonlinear and Optimal Control Systems
Information Sciences—Informatics and Computer Science: An International Journal
Integrated fuzzy modeling and adaptive control for nonlinear systems
Information Sciences: an International Journal
Impulsive control and synchronization of Chua's oscillators
Mathematics and Computers in Simulation
Intelligent adaptive control for MIMO uncertain nonlinear systems
Expert Systems with Applications: An International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems
IEEE Transactions on Fuzzy Systems
Design for Self-Organizing Fuzzy Neural Networks Based on Genetic Algorithms
IEEE Transactions on Fuzzy Systems
Adaptive Synchronization of Uncertain Chaotic Systems Based on T–S Fuzzy Model
IEEE Transactions on Fuzzy Systems
Direct adaptive controller for nonaffine nonlinear systems using self-structuring neural networks
IEEE Transactions on Neural Networks
Self-Organizing Adaptive Fuzzy Neural Control for a Class of Nonlinear Systems
IEEE Transactions on Neural Networks
Fire-rule-based direct adaptive type-2 fuzzy H∞ tracking control
Engineering Applications of Artificial Intelligence
Self-adaptive interval type-2 neural fuzzy network control for PMLSM drives
Expert Systems with Applications: An International Journal
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This paper presents a novel quadratic optimal neural fuzzy control for synchronization of uncertain chaotic systems via H^~ approach. In the proposed algorithm, a self-constructing neural fuzzy network (SCNFN) is developed with both structure and parameter learning phases, so that the number of fuzzy rules and network parameters can be adaptively determined. Based on the SCNFN, an uncertainty observer is first introduced to watch compound system uncertainties. Subsequently, an optimal NFN-based controller is designed to overcome the effects of unstructured uncertainty and approximation error by integrating the NFN identifier, linear optimal control and H^~ approach as a whole. The adaptive tuning laws of network parameters are derived in the sense of quadratic stability technique and Lyapunov synthesis approach to ensure the network convergence and H^~ synchronization performance. The merits of the proposed control scheme are not only that the conservative estimation of NFN approximation error bound is avoided but also that a suitable-sized neural structure is found to sufficiently approximate the system uncertainties. Simulation results are provided to verify the effectiveness and robustness of the proposed control method.