DocumentCode :
2792488
Title :
Multivariable model predictive control for integrating processes with input constraints
Author :
Zhu, Nana ; Zhou, Lifang ; Li, Jianfeng
Author_Institution :
Dept. of Control Sci. & Eng., Zhejiang Univ., Hangzhou, China
fYear :
2009
fDate :
17-19 June 2009
Firstpage :
3471
Lastpage :
3476
Abstract :
The model predictive control (MPC) strategy with input constraints may lead to infeasibility of the control algorithm in short term and degradation of the control performance. For the control of integrating processes, the system input constraints will be possible to come into conflict with the constraints caused by zeroing the integrating modes of the system at the end of the control horizon. In order to deal with this problem and increase the feasibility, the effect of setpoint on feasibility is studied for multivariable model predictive control of integrating processes in this paper. An improved algorithm is proposed by recalculating the setpoints according to the hard constraints before calculating the manipulated variable. The simulation results verify the efficiency and feasibility.
Keywords :
constraint theory; multivariable control systems; predictive control; hard constraint; integrating process; multivariable model predictive control; system input constraint; Adaptive control; Control systems; Degradation; Electrical equipment industry; Industrial control; Prediction algorithms; Predictive control; Predictive models; Programmable control; Steady-state; Input constraints; Integrating processes; Model predictive control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
Type :
conf
DOI :
10.1109/CCDC.2009.5192429
Filename :
5192429
Link To Document :
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