Multi-objective nonlinear model predictive control through switching cost functions and its applications to chemical processes

Defeng He; Shiming Yu; Li Yu

doi:10.1016/j.cjche.2015.07.005

Your Location：

Home >

Browse articles >

Multi-objective nonlinear model predictive control through switching cost functions and its applications to chemical processes

过程系统工程与过程安全 | Updated：2026-01-06

- Multi-objective nonlinear model predictive control through switching cost functions and its applications to chemical processes
- Chinese Journal of Chemical Engineering Vol. 23, Issue 10, Pages: 1662-1669(2015)
- Affiliations：
  
  College of Information Engineering, Zhejiang University of Technology,Hangzhou,China,310023
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2015.07.005
  CLC：
- Published：2015
- Accepted：
Scan QR Code
Defeng He, Shiming Yu, Li Yu. Multi-objective nonlinear model predictive control through switching cost functions and its applications to chemical processes[J]. Chin.J.Chem.Eng., 2015, 23(10): 1662-1669.
DOI：

Defeng He, Shiming Yu, Li Yu. Multi-objective nonlinear model predictive control through switching cost functions and its applications to chemical processes[J]. Chin.J.Chem.Eng., 2015, 23(10): 1662-1669. DOI： 10.1016/j.cjche.2015.07.005.

摘要

Abstract

This paper proposes a switching multi-objective model predictive control (MOMPC) algorithm for constrained nonlinear continuous-time process systems. Different cost functions to be minimized inMPC are switched to satisfy different performance criteria imposed at different sampling times. In order to ensure recursive feasibility of the switching MOMPC and stability of the resulted closed-loop system

the dual-mode control method is used to design the switching MOMPC controller. In this method

a local control law with some free-parameters is constructed using the control Lyapunov function technique to enlarge the terminal state set of MOMPC. The correction termis computed if the states are out of the terminal set and the free-parameters of the local control laware computed if the states are in the terminal set. The recursive feasibility of the MOMPC and stability of the resulted closed-loop system are established in the presence of constraints and arbitrary switches between cost functions. Finally

implementation of the switching MOMPC controller is demonstrated with a chemical process example for the continuous stirred tank reactor.

关键词

Keywords

references

Views

244

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system

Robust particle filtering-based nonlinear model predictive control: Application to PEMFC process

A fuzzy compensation-Koopman model predictive control design for pressure regulation in proten exchange membrane electrolyzer

Composition control and temperature inferential control of dividing wall column based on model predictive control and PI strategies

Just-in-time learning based integrated MPC-ILC control for batch processes

Related Author

Shan Liu

Wenqi Zhong

Li Sun

Xi Chen

Rafal Madonski

Lei Xie

Qi Zhang

Fanda Pan

Related Institution

Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwise

School of Energy and Environment, Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University

Institute of Intelligence Science and Engineering, Shenzhen Polytechnic University

Technical Center of Zhejiang China Tobacco Industrial Co. Ltd.

BYD Automobile Industry Co., Ltd.

⁰