单机架炉卷轧机监控AGC控制算法的研究

为解决单机架炉卷轧机监控AGC 的大时滞和控制精度问题，针对常规PID 不能自我进化的缺点，本文采用BP 神经网络对PID 控制器进行参数自整定，并将该智能控制器与Smith 预估器结合对AGC 系统进行监控，既解决了自我进化问题，也克服了时滞，通过仿真分析和现场验证，其收敛速度和鲁棒性明显改善。
关键词：炉卷轧机；监控AGC；智能PID；Smith 预估器
Abstract: Considered the general PID can’t improve itself, a BP neural network PID is proposed to improve the control precision and large time deday of monitor AGC of a Steckel rolling mill. And then the intelligent PID and Smith prediction control machine are combined to minitor the AGC system so that the self-learning capability and time delay of the system evidently improved. It was proved that the robustness and convergence rate of the system
is obviously improved by simulation and implement experiment.
Key words: Steckel mill; monitor AGC; intelligent PID; smith prediction control machine