Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard  Constraints

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Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard
Constraints

ZHOU Lifang; SHAO Zhijiang

Institute of Systems Engineering, Control Science and Engineering Department, Zhejiang
University, Hangzhou,310027, China

Received:1900-01-01 Revised:1900-01-01 Online:2003-10-28 Published:2003-10-28
Contact: ZHOU Lifang

具有软硬约束的混合权系数最小二乘稳定预测控制算法

周立芳; 邵之江

Institute of Systems Engineering, Control Science and Engineering Department, Zhejiang
University, Hangzhou,310027, China

通讯作者: 周立芳

Abstract

Abstract: Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic
programming (QP) method, has the advantages of reducing the computer burden, quick
calculation speed and dealing with the case in which the optimization is infeasible. But it
can only deal with soft constraints. In order to deal with hard constraints and guarantee
feasibility, an improved algorithm is proposed by recalculating the setpoint according to
the hard constraints before calculating the manipulated variable and MWLS algorithm is used
to satisfy the requirement of soft constraints for the system with the input constraints
and output constraints. The algorithm can not only guarantee stability of the system and
zero steady state error, but also satisfy the hard constraints of input and output
variables. The simulation results show the improved algorithm is feasible and effective.

Key words: mixed-weight least-squares, predictive control, soft constraints, hard constraints, feasibility

摘要： Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic
programming (QP) method, has the advantages of reducing the computer burden, quick
calculation speed and dealing with the case in which the optimization is infeasible. But it
can only deal with soft constraints. In order to deal with hard constraints and guarantee
feasibility, an improved algorithm is proposed by recalculating the setpoint according to
the hard constraints before calculating the manipulated variable and MWLS algorithm is used
to satisfy the requirement of soft constraints for the system with the input constraints
and output constraints. The algorithm can not only guarantee stability of the system and
zero steady state error, but also satisfy the hard constraints of input and output
variables. The simulation results show the improved algorithm is feasible and effective.

关键词: mixed-weight least-squares;predictive control;soft constraints;hard constraints; feasibility

ZHOU Lifang, SHAO Zhijiang. Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard
Constraints[J]. .

周立芳, 邵之江. 具有软硬约束的混合权系数最小二乘稳定预测控制算法[J]. CIESC Journal.

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