基于RBFNN整定的PID控制在柔性摆跟踪控制中的应用研究

本文提出了一种基于径向基函数神经网络（RBFNN）整定的PID控制策略，并将其应用于柔性倒立摆的跟踪控制。该方法通过神经网络辨识获取柔性摆的Jacobian信息，采用梯度下降法自适应调整PID的控制参数。仿真结果表明，与传统的PID控制效果相比，该控制方法响应速度快、超调量小，较好地解决了PID控制方法中参数整定困难的问题，实现了对柔性摆的有效跟踪控制。

RBFNN tuning based application of PID control in tracking control of flexible joint inverted pendulum

We present a radial basis function neural network (RBFNN)tuning based PID control strategy.It is then applied to the tracking control of flexible joint inverted pendulum. It acquires Jacobian information of flexible joint inverted pendulum by the identification of neural network,and adaptively adjusts PID control parameters by gradient descent method.Simulation results show that the method has rapid response and small overshoot, as compared with other conventional PID control methods. It better solves the difficulty inparameters tuning of PID control method,and implements effective tracking and control over flexible joint inverted pendulum.