Experimental Study on a Hybrid Control Method using Neural Networks with Particle Swarm Optimization
説明
Artificial intelligence (AI) is widely applied in industrial products and innovations. In control engineering, the application of AI opened a novel area of intelligent control. Since then the famous algorithms of AI, such as Neural Network (NN) and Genetic Algorithm (GA) have been being researched, developed and applied for various control applications. Alone with optimization algorithms introduced in intelligent control, more and more hybrid methods have been developed. In this research, we introduce a hybrid intelligent method, based on NN combined with Particle Swarm Optimization (PSO), to the auto-tuning of variable gain PID control in real-time environment. The proposed method is with simple structure and capable to improve the control performance of traditional PID control. The proposed method was applied to a nonlinear actuator, Ultrasonic Motor (USM) for confirming the control performance and the effectiveness of it. The method is studied based on experimental results.
収録刊行物
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- The Proceedings of the 4th International Conference on Industrial Application Engineering 2016
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The Proceedings of the 4th International Conference on Industrial Application Engineering 2016 25-29, 2016-01-01
The Institute of Industrial Applications Engineers