摘要
针对常规PID控制参数整定困难,且受时变、非线性等因素影响而不能达到预期控制效果的实际情况,提出了RBF网络动态辨识的BP神经网络PID参数自整定算法。此算法可实现PID控制参数的在线自整定和优化;同时,将算法应用于伺服控制系统中,以VC++6.0和Matlab为开发和仿真工具,对动态辨识神经网络智能PID参数自整定方法进行仿真研究。仿真结果表明,控制算法鲁棒性强、响应速度快,可用于控制参数时变的非线性系统。
In accordance with the actual conditions of conventional PID control tuning, i.e. difficult to reach expected control effects because of the influence of time varying and non-linearity, the new algorithm based on RBF neural network dynamic identification for PID parameters auto-tuning is proposed. The algorithm implements online auto-tuning and optimization for PID control parameters ; in addition, it has been applied in servo system and simulated with the software tools of VC ＋ ＋ 6.0 and Matlab. The result of simulation indicates that the control algorithm fea- tures high robustness and rapid response speed, it can be used in nonlinear system with time varying parameters.
出处
《自动化仪表》
CAS
北大核心
2011年第2期59-62,共4页
Process Automation Instrumentation
