Introduction to Grey system theory
The Journal of Grey System
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Fuzzy controllers as gain scheduling approximators
Fuzzy Sets and Systems - Special issue on methods for data analysis in classificatin and control
Real-valued genetic algorithms for fuzzy grey prediction system
Fuzzy Sets and Systems
Optimal design of fuzzy sliding-mode control: a comparative study
Fuzzy Sets and Systems
Genetic Algorithms and Manufacturing Systems Design
Genetic Algorithms and Manufacturing Systems Design
Optimal Grey-Fuzzy Gain-Scheduler Design Using Taguchi-HGA Method
Journal of Intelligent and Robotic Systems
Hybrid methods using genetic algorithms for global optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The hybrid grey-based models for temperature prediction
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Optimal Grey-Fuzzy Gain-Scheduler Design Using Taguchi-HGA Method
Journal of Intelligent and Robotic Systems
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In this paper, the grey-fuzzy-gain-scheduling (GFGS) control scheme is proposed for making a nonlinear autonomous system to track a reference trajectory. The GFGS control scheme consists of two parts: the grey predictor and the fuzzy gain scheduling controller. An optimal combined method, i.e., Taguchi-hierarchical-genetic-algorithm (Taguchi-HGA), is presented in this paper to search for the optimal control parameters of both the grey predictor and the fuzzy gain scheduling controller (i.e., the sample size and grey constants of the grey predictor, the centers of the fuzzy regions, the left spread and the right spread of the membership functions, and the weighting matrices in the performance index of the linear quadratic regulator method) for guaranteeing stability and obtaining an optimal control performance. Computer simulations of a two-link robot arm example are performed to verify the effectiveness of the optimal GFGS control scheme designed by the Taguchi-HGA and to show that the optimal GFGS control scheme is superior to the existing optimal FGS (fuzzy-gain-scheduling) control scheme.