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Study on PID Controller Based on Fuzzy RBF Neural Network in Rolling Mill Hydraulic AGC System

机译:基于模糊RBF神经网络在轧机液压AGC系统中PID控制器的研究

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A kind of PID controller based on fuzzy RBF neural network is proposed to the problem that traditional PID controller is difficult to achieve good control effect because of the fixed parameters. This method includes the reasoning ability of fuzzy control and study ability of neural network. Fuzzy control and RBF neural network are combined in order to adjust the parameters of PID online to a group of kp, ki and kd, which is matching the plant best. Simultaneously the algorithm is applied to rolling mill hydraulic AGC system for PID controller parameter optimization. The simulation result shows that the PID controller greatly improves the dynamic performance and stable performance of the hydraulic AGC system.
机译:一种基于模糊RBF神经网络的PID控制器被提出给传统PID控制器难以实现由于固定参数难以实现良好的控制效果的问题。该方法包括神经网络模糊控制和研究能力的推理能力。组合模糊控制和RBF神经网络才能调整PID的参数,以一组KP,KI和KD,其与植物相匹配。同时该算法应用于用于PID控制器参数优化的轧机液压AGC系统。仿真结果表明,PID控制器大大提高了液压AGC系统的动态性能和稳定性能。

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