Optimal Design of PDC Controllers for Time-Varying TS-Fuzzy-Model-Based Time-Delay Systems

Hsu, Ming-Ren; Ho, Wen-Hsien; Chou, Jyh–Horng

doi:10.1109/fuzzy.2007.4295493

Cited by 1 publication

(1 citation statement)

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“…To the best of our knowledge, no studies have proposed designs for time-varying TS fuzzy model–based time-delay control systems with quadratic optimal PDC controllers. Even though the authors have previously obtained the preliminary research results (Hsu et al, 2007), the optimal design algorithm is incomplete. Therefore, this issue is still worth to further study in both completeness and depth for the optimal design algorithm.…”

Section: Introductionmentioning

confidence: 99%

Optimal parallel-distributed-compensation controller design for a class of time-varying Takagi–Sugeno fuzzy model–based time-delay systems by using the orthogonal function approach–assisted genetic algorithm

Chou

Hsu

2020

Journal of Vibration and Control

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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.

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Section: Introductionmentioning

confidence: 99%