摘要
针对交流调速传统控制调速过程中往往会出现转速波动大和超调量等问题,无法满足控制系统的高性能要求,提出了一种自适应神经网络PID控制算法,应用反向传播人工神经网络理论,对于系统模型参数未知的情况下,使用两个人工神经网络分别进行控制系统在线辨识与PID控制器参数在线调整。经与PID控制对比进行了试验验证,表明本控制算法能让系统在很短的时间内调整出优良的控制参数,能够很好的跟踪负载变化,动态响应快,速度跟随准确,具有很强的自适应性和鲁棒性。
The adjustable speed of motor might has the disadvantages of overshoot, speed fluctuation large, unstability and so on, which cannot meet the need of high performance. This paper presents a self-tuning PID controller based on the neural network theories. There are two multilayer neural networks within the self-tuning PID controller, one for system identification for unknown controlled systems, and the other for the PID gains determination. Back-propagation method is adopted to perform both the neural networks training. The results of simulation show that the neural based PID control scheme can tune suitable PID gains within a short period, and it is with better robust adjustability, faster dynamic response and speed following accurately to load variation.
出处
《变频器世界》
2014年第1期67-72,共6页
The World of Inverters
基金
湖北工程学院科研资助项目(Z2013010)
