【摘要】 针对球杆系统定位控制问题,基于BP神经网络设计了BP神经网络控制器和BP神经网络PID参数自整定两种智能控制器.完成了两种控制器的网络结构与实现方法,并在Simulink环境中仿真.仿真结果显示出BP神经网络PID参数自整定控制器的稳定性优于BP神经网络控制器,将BP神经网络PID参数自整定控制器算法移植到GBB1004球杆系统,实现了对该系统的控制.实验结果显示,该控制器响应快,有一定的抗干扰能力,获得系统调节时间小于16s,稳态误差小于1cm.更多还原

【Abstract】 Aimed at the position control for ball-beam system,two intelligent controllers are designed based on the BP neural network.One is a BP neural network controller,and the other is a BP neural network self-tuning PID parameter controller.The structure of neural network and implementation are fulfilled.The simulated results in Simulink environment show that the BP neural network controller with the self-tuning PID parameter is more stable than the BP neural network,so this algorithm is transplanted to GBB1004 ball-beam system and control to this system has been implemented.The experimental results show that the respond of BP neural network controller with the self-tuning PID parameter is fast and also there is more anti-interference ability.The time that system reachs stable is less than 16 s and the steady state error is less than 1 cm.更多还原