基于PID神经网络的非线性系统辨识与控制

针对工业控制领域中非线性系统采用传统的控制方法不能达到满意的控制效果,提出一种基于P ID神经网络的控制方案,以对其进行辨识和控制。将P ID神经网络引入控制系统中,既具有常规P ID控制结构简单、参数物理意义明确等优点,同时又具有神经网络的并行结构和学习记忆功能及非线性映射能力。仿真结果表明:该控制系统响应速度快、超调量小、稳态精度高,能够快速跟踪系统输出并进行有效控制,且具有一定的自适应性和鲁棒性,满足实时控制的要求。

Identification and Control in Nonlinear System Based on PID Neural Network

A control scheme based on PID neural network(PIDNN) is proposed to identify and control the nonlinear system for which traditional control methods can't acquire satisfying result.The PIDNN is a new type of dynamic feed-forward neural network which blends the PID control strategy into neural networks,so it has the merit of general PID controller for its simple construction and definite physical meaning of parameters,and also has the parallel structure,self-learning function and nonlinear mapping capability of neural network.The results of simulation show that the system has properties of low overshoot,quick response and good steady accuracy,and the controller can quickly track and effectively control the output of system with good adaptability and robustness and meet the need of real-time control.