基于模糊RBF神经网络的PID及其应用

针对传统的PID控制器参数固定而导致在控制中效果差的问题，提出一种基于模糊RBF神经网络智能PID控制器的设计方法。该方法结合了模糊控制的推理能力强与神经网络学习能力强的特点，将模糊控制与RBF神经网络相结合以在线调整PID控制器参数，整定出一组适合于控制对象的kp, ki, kd参数。将算法运用到电机控制系统的PID参数寻优中，仿真结果表明基于此算法设计的PID控制器改善了电机控制系统的动态性能和稳定性。

PID Controller Based on Fuzzy RBF Neural Network and Its Application

A kind of intelligent 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 applied 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 electro motor control system PID for parameter optimization. The simulation result shows that the PID controller greatly improves dynamic quality of electro control system.