Improved Takagi–Sugeno fuzzy model-based control of flexible joint robot via Hybrid-Taguchi genetic algorithm

Author(s):  
P. Nikdel ◽  
M. Hosseinpour ◽  
M.A. Badamchizadeh ◽  
M.A. Akbari
2020 ◽  
pp. 107754632093690
Author(s):  
Fu-I Chou ◽  
Ming-Ren Hsu ◽  
Wen-Hsien Ho

This study proposes a method of designing quadratic optimal fuzzy parallel-distributed-compensation controllers for a class of time-varying Takagi–Sugeno fuzzy model–based time-delay control systems used to solve the finite-horizon optimal control problem. The proposed method fuses the orthogonal function approach and the improved hybrid Taguchi-genetic algorithm. The Taguchi-genetic algorithm only requires algebraic computation to perform the algorithm used to solve time-varying Takagi–Sugeno fuzzy model–based time-delay feedback dynamic equations. The fuzzy parallel-distributed-compensation controller design problem is simplified by using the Taguchi-genetic algorithm to transform the static parameter optimization problem into an algebraic equation. The static optimization problem can then be solved easily by using the improved hybrid Taguchi-genetic algorithm to find the quadratic optimal parallel-distributed-compensation controllers of the time-varying Takagi–Sugeno fuzzy model–based time-delay control systems. The applicability of the proposed integrative method is demonstrated in a real-world design problem.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 71628-71641 ◽  
Author(s):  
Xin Tang ◽  
Donghong Ning ◽  
Haiping Du ◽  
Weihua Li ◽  
Yibo Gao ◽  
...  

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