摘要
火电厂钢球磨煤机的负荷对象具有大滞后、慢时变、强非线性等复杂特性,采用常规控制方法难以获得满意的控制效果,文章提出了基于灰色预测模型的自抗扰负荷控制方法,它把灰色预测模型与自抗扰控制结合起来,在常规的自抗扰控制中加入灰色预测模型的控制方法,并且控制系统的参数采用自适应遗传算法进行优化;仿真结果表明这种控制方法系统响应快、超调小、鲁棒性好、抗干扰能力强,可以有效解决大滞后、非线性及适应性等问题。
The load object of ball mill in thermal power plant has the complex traits with large time--delay, slow time--varying, strongly nonlinear, etc. It is difficult to obtain satisfactory control performanee using conventional control methods. In this paper, the active disturb- anee rejection control method based on gray prediction model was introduced to load control. In this control system, gray prediction model and disturbance rejection were combined, gray prediction model was added to conventional disturbance rejection control, and the parameters of control system were optimized bY adaptive genetic algorithm. The simulation results show that the control method has fast response, small overshoot, good robustness, strong anti--interference ability, it can effectively solve the large time--delay, nonlinear and adaptive prob- lems.
出处
《计算机测量与控制》
CSCD
北大核心
2011年第9期2147-2150,2156,共5页
Computer Measurement &Control
基金
上海市教委重点学科建设项目(J51301)
关键词
球磨机负荷
灰色预测模型
自抗扰控制
自适应遗传算法
PID控制
ball mill load
gray prediction model
active disturbance rejection control, adaptive genetic algorithm
PID control.