摘要
双层结构预测控制是指先进行设定值优化、再进行设定值跟踪的预测控制.在已有的双层结构动态矩阵控制的基础上,本文给出基于状态空间模型的双层结构预测控制算法.该算法基于干扰模型和新定义的开环预测值,给出了新的开环预测模块.该开环预测模块采用Kalman滤波方法得到操作变量、被控变量的开环动、稳态预测值.基于这些开环预测值,稳态目标计算模块的基本原理同双层结构动态矩阵控制,但是具体细节上遵循状态空间方法.动态控制模块基于稳态目标计算提供的操作变量、被控变量的稳态目标(设定值),采用二次规划算法计算控制作用.仿真算例证实了该算法的有效性.
The so-called double-layered model predictive control（MPC） performs firstly the setpoint optimization,then the setpoint tracking. Based-on the existing double-layered dynamic matrix control, this paper gives an algorithm for double-layered MPC based on the state-space model. Based on the disturbance model and the newly defined open-loop predictions, this algorithm proposes a new open-loop prediction module. This open-loop prediction module adopts the Kalman filter to obtain the open-loop dynamic/steady-state predictions of manipulated/controlled variables（MVs/CVs）. Based on these open-loop predictions, the steady-state target calculation（SSTC） module is the same as in double-layered dynamic matrix control, but its details obey the state-space method. Based on the steady-state targets（setpoints） of MVs/CVs provided by SSTC, the dynamic control module computes the control moves by solving the quadratic programming. The numerical example verifies the effectiveness of the proposed algorithm.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2017年第1期69-76,共8页
Control Theory & Applications
基金
国家高技术研究发展计划("863"计划)项目(2014AA041802)
国家自然科学基金项目(61573269)
陕西省自然科学基金项目(2016JM6049)资助~~
关键词
预测控制
状态空间
KALMAN滤波
设定值优化
双层结构
model predictive control（MPC）
state-space
Kalman filter
setpoint optimization
double-layered structure
