具有状态观测器的广义动态矩阵控制在板带轧机位置伺服系统中的应用  被引量:1

APPLICATION OF GENERALIZED DYNAMIC MATRIX CONTROL WITH STATE OBSERVER IN POSITION SERVO SYSTEM OF STRIP MILL

在线阅读下载全文

作  者:王益群[1] 孙孟辉[1] 张伟[1] 刘建[1] 

机构地区:[1]燕山大学机械工程学院,秦皇岛066004

出  处:《机械工程学报》2007年第9期2-6,共5页Journal of Mechanical Engineering

基  金:国家自然科学基金(60474044);河北省自然科学基金(E200400022)资助项目。

摘  要:板带轧机的构成是复杂的,其控制系统日益精密化和智能化,但是目前广泛应用于现场的比例积分微分(PID)控制策略,由于鲁棒性较差,难以满足进一步提高板带轧机控制精度的要求。针对板带轧机位置伺服系统,应用广义动态矩阵控制理论,设计预测控制器,并采用滚动优化、反馈校正的控制策略。构造状态观测器,使控制系统具有带观测器的状态反馈形式,不断地修正预测模型,增强了系统的鲁棒性。所研究控制算法基于系统的阶跃响应,具有较强的稳定性和鲁棒性。提出上述控制策略的计算机控制实现方法,仿真研究结果表明该方法远比目前带钢生产中广为采用的PID控制策略优越,具有智能性且易于实现。The structure of the strip mill is complicated, and its control system becomes more and more precise and intellective. But the PID control strategy, being comprehensively used in the locale, is difficult to satisfy the request of improving the control precision of the strip mill, because the robust is not very well. So the generalized dynamic matrix control was applied to de- sign the predictive controllers in position servo system of strip mill, and strategy of the receding-horizon optimization, and the feedback correction were adopted. The state observer was contructed, which made the control system have the state feedback form with the observer, and strengthened the robust of the system by correcting the predictive model. The control algorithm has the strong stability and the robust, based on the system step response. At the same time, the realization strategy of the com- puter control was provided. The method is easy to be realized and has intelligent capability. The simulation result indicates that the control effect using the presented method is better than that using the traditional PID control which is comprehensively used in the strip production.

关 键 词:广义动态矩阵控制 板带轧机 位置伺服系统 状态观测器 

分 类 号:TG334.9[金属学及工艺—金属压力加工] TP273[自动化与计算机技术—检测技术与自动化装置]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象