Optimally robust H∞ polynomial fuzzy controller design using quantum-inspired evolutionary algorithm
| Autor: | Yu-Chia Huang, Gwo-Ruey Yu, Chih-Yung Cheng |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Fitness function Computer science Evolutionary algorithm Explained sum of squares 02 engineering and technology Optimal control Fuzzy logic Computer Science Applications Theoretical Computer Science Stability conditions 020901 industrial engineering & automation Discrete time and continuous time Control and Systems Engineering Robustness (computer science) Control theory 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing |
| Zdroj: | International Journal of Systems Science. 49:2601-2617 |
| ISSN: | 1464-5319 0020-7721 |
| DOI: | 10.1080/00207721.2018.1506522 |
| Popis: | This paper proposes an optimally robust H∞ polynomial fuzzy controller design using quantum-inspired evolutionary algorithm (QEA) for continuous/discrete time polynomial fuzzy systems with model uncertainties and external disturbances. To improve control performance, QEA is adopted to evolve optimal control gains with a fitness function that is defined by performance requirements. The stability and robustness of the control system are then guaranteed by the proposed robust H∞ stability conditions, which are formed by the sum of squares (SOS) method. By using the principle of copositivity, novel relaxed SOS-based stability conditions are derived to reduce the conservativeness of solving SOS-based stability conditions, while the feasible solution space is broadened. Four numerical examples demonstrate the effectiveness of the proposed approaches. |
| Databáze: | OpenAIRE |
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