摘要
灰色预测PID控制系统的核心是其反馈回路上的灰色预测器,其建模精度与控制系统行为数据的变化速率有关.对于惯性较大的被控对象或采样周期较短的控制系统,控制系统的行为数据变化缓慢,基于这些数据直接进行灰色建模预测的精度不高.针对这个问题,本文提出了基于强化缓冲算子的灰色预测PID控制新方法.通过对控制系统的行为数据序列进行强化缓冲算子作用,获得控制系统行为数据的强化缓冲算子作用序列,对其进行灰色建模和预测,实现灰色预测PID控制.仿真研究结果表明,在相同的PID控制参数下,本文提出的控制方法的控制精度明显优于传统的灰色预测PID控制和经典PID控制,获得了理想的控制效果.
The kernel of grey prediction PID control system is the grey predictor in its feedback loop, and its modeling precision is relevant to the variation rate of the control system behavior data. For large inertia controlled objects or short sampling period control systems, the behavior data of the control system changes slowly, so the prediction by direct grey modeling based on these data is of low precision. In allusion to this problem, a new grey prediction PID control method based on strengthening buffer operator was proposed. Through the functioning of strengthening buffer operator on the behavior data sequence of the control system, a strengthening buffer operator functioning sequence of the control system behavior data was obtained and, then the grey modeling and prediction were carried out to realize grey prediction PID control. The simulation results show that with the same PID control parameters, by using the control method proposed in the paper, the desired control effect can be achieved and its control precision is obviously superior to that of the traditional grey prediction PID control and classical PID control.
出处
《上海理工大学学报》
CAS
北大核心
2012年第4期327-332,共6页
Journal of University of Shanghai For Science and Technology
基金
国家自然科学基金资助项目(50975179)
上海市教委科研创新资助项目(11ZZ136)
上海市科委地方院校计划项目(08110511600)
关键词
强化缓冲算子
灰色预测
PID控制
仿真
行为数据
Simulation buffer operator grey predictiom PID control simulation behavior data
作者简介
朱坚民（1968-）．男。教授．研究方向：机电系统的智能测控、生物医学信号的传感检测等E—mail：jmzhu6688@163．com
