This paper presents several control methods and realizes the stable tracking for the inverted pendulum system. Based on the advantages of RBF and traditional PID, a novel PID controller based on the RBF neural network supervision control method (PID-RBF) is proposed. This method realizes the adaptive adjustment of the stable tracking signal of the system. Furthermore, an improved PID controller based on RBF neural network supervision control strategy (IPID-RBF) is presented. This control strategy adopts the supervision control method of feed-forward and feedback. The response speed of the system is further improved, and the overshoot of the tracking signal is further reduced. The tracking control simulation of the inverted pendulum system under three different signals is given to illustrate the effectiveness of the proposed method.

中文翻译：

---

倒立摆跟踪控制的神经网络监督控制策略

提出了几种控制方法，实现了倒立摆系统的稳定跟踪。基于RBF和传统PID的优点，提出了一种基于RBF神经网络监督控制方法（PID-RBF）的新型PID控制器。该方法实现了系统稳定跟踪信号的自适应调整。此外，提出了一种基于RBF神经网络监督控制策略（IPID-RBF）的改进型PID控制器。该控制策略采用前馈和反馈的监督控制方法。系统的响应速度进一步提高，跟踪信号的过冲进一步降低。给出了三种不同信号下的倒立摆系统的跟踪控制仿真，说明了该方法的有效性。