基于RBF神经网络的PID自校正控制研究

Research of PID Self-Turning Controller Based on RBF Neural Network

针对传统的自校正PID控制器不能有效的实现工业工程中非线性系统、不确定性系统的在线参数的整定和实时控制作用,提出了一种基于径向基（RBF）神经网络的PID自校正控制方法,并分别用自校正PID控制和基于RBF神经网络的PID自校正控制进行系统仿真实验,仿真结果表明：基于RBF神经网络的PID自校正控制方法可以根据非线性系统、不确定系统对象的变化完成参数的在线动态修正,同时也增强了系统的自适应调整能力。

The setting of on-line parameter and real-time control of the non-linear system and non-determinable system in industrial engineering could not be resolved by means of traditional self-turning PID controller, consequently a new method of PID self-turning control based on RBF neural network was proposed in this paper. PID self-turning control and PID self-turning con- trol based on RBF neural network were used to for system emulation experiment, respectively. The results showed that PID selfturning control based on RBF neural network can achieve on.line dynamic modification of the parameters according to the nonlinear system and the alteration of uncertainty system object. At the same time, the ability of self adapting adjustment was enhanced.