Punctuated equilibria: a parallel genetic algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach
Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Explicit Parallelism of Genetic Algorithms through Population Structures
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
A multiple Lyapunov function approach to stabilization of fuzzy control systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Tuning of the structure and parameters of a neural network using an improved genetic algorithm
IEEE Transactions on Neural Networks
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In this paper, we propose a practical robust fuzzy control design scheme that achieves optimal tracking performance and requires limited accuracy in the plant model. The plant is identified as a fuzzy combination of Takagi-Sugeno type linear models, and the fuzzy controller is optimized by genetic algorithms according to both the tracking performance and the attenuation level. The procedure applies the lately proposed idea of the fuzzy Lyapunov function that is less conservative then the traditional Lyapunov function candidate approach, and ensures H∞ robust tracking. The effectiveness of the proposed scheme is demonstrated by the fuzzy tracking control of an uncertain chaotic system with external disturbance.