摘要
考虑到实际工业过程中存在各种约束,基于模型预测最小方差控制器的设计原理,提出了一种带约束模型预测控制(MPC)性能评价方法。最小方差控制器的最优预测输出采用控制增量进行预测,目标函数采用最优预测输出和控制增量加权的二次型形式,通过求解二次规划(QP)问题获取最优控制律。该方法不仅考虑了控制输入和输出约束,而且考虑了控制增量约束,因此能够更真实地反映模型预测控制系统的性能。在Wood-Berry二元精馏塔上的仿真研究验证了该方法的有效性。
Considering various constraints in the practical industry process, the perform- ance assessment of MPC with constraints was presented based on the design principle of the model-based predictive minimum variance controller. The control increments are used to predict the optimal predictive outputs of the minimum variance controller. The objective optimization function employs quadratic form of optimal predicted outputs and control increments weighted, and then it obtains the optimal control law through solving the quadratic programming （QP） problem. This approach not only takes the constraints of control inputs and outputs into consideration but also covers the factor of the con- straints of the control increments, which made it reflect the performance, of the model predictive control system more authentically. The simulation example on the Wood-Ber- ry binary distillation column illustrated the validity of the method.
出处
《青岛科技大学学报（自然科学版）》
CAS
北大核心
2012年第5期520-524,共5页
Journal of Qingdao University of Science and Technology:Natural Science Edition
基金
国家自然科学基金项目(51104175)
山东省自然科学基金项目(ZR2011FM014)
关键词
模型预测控制
最小方差基准
性能评价
约束
二次规划
model predictive control, minimum variance benchmark, performance as-sessment, constraints, quadratic program
