Designing Fuzzy Net Controllers using Genetic Algorithms
نویسندگان
چکیده
As control system tasks become more demanding, more robust controller design methodologies are needed. A Genetic Algorithm (GA) optimizer, which utilizes natural evolution strategies, o ers a promising technology that supports optimization of the parameters of fuzzy logic and other parameterized non-linear controllers. This paper shows how GAs can e ectively and e ciently optimize the performance of fuzzy net controllers employing high performance simulation to reduce the design cycle time from hours to minutes. Our results demonstrate the robustness of a GA-based Computer-Aided System Design methodology for rapid prototyping of control systems.
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Designing Fuzzy Net Controllers using GA Optimization
As plant speci cations become complicated, more robust controller design methodologies are needed. A Genetic Algorithm optimizer, which utilizes natural evolution strategies, o ers a promising technology that supports optimization of the parameters of fuzzy logic and other parameterized non-linear controllers. This paper shows how GAs can e ectively and e ciently optimize the performance of par...
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