神经网络与PID结合的直流调速系统自适应控制

提出一种将神经网络理论结合传统PID控制机理 ,构成单神经元PID控制器 ,并应用于直流调速系统。通过在线边学习边控制的方式 ,解决了传统PID的不足 ,实现了调速系统的快速过程实时在线控制要求。仿真结果表明 ,这控制方法具有良好的自适性 ,且系统鲁棒性优于传统双闭环控制。

Self-adaptive Control Based on Neural Networks and PID for Direct Current Governor Seytems

Control mechanism which based on the theory of neural networks and traditional PID is present single neurons PID controller is constituded.And it is applied to the direct current governor systems. Through the way of learning and controlling on line, to solve the insufficiency of traditional PID and to fulfill the requirement of rapid real\|time on line process control for governor system. The results of the emulation show that this control with good self\|adaptive. and the robust of the system is better than that of the traditional double\|closed\|loop control systems.