Output feedback robust model predictive control with unmeasurable model parameters and bounded disturbance

Baocang Ding; Hongguang Pan

doi:10.1016/j.cjche.2016.05.041

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Output feedback robust model predictive control with unmeasurable model parameters and bounded disturbance

Process Systems Engineering and Process Safety | Updated：2026-01-06

- Output feedback robust model predictive control with unmeasurable model parameters and bounded disturbance
- Chinese Journal of Chemical Engineering Vol. 24, Issue 10, Pages: 1431-1441(2016)
- Affiliations：
  
  Ministry of Education Key Lab For Intelligent Networks and Network Security, Department of Automation, School of Electronic and Information Engineering, Xi'an Jiaotong University,Xi'an,China,710049
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2016.05.041
  CLC：
- Published：2016
- Accepted：
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Baocang Ding, Hongguang Pan. Output feedback robust model predictive control with unmeasurable model parameters and bounded disturbance[J]. , 2016, 24(10): 1431-1441.
DOI：

Baocang Ding, Hongguang Pan. Output feedback robust model predictive control with unmeasurable model parameters and bounded disturbance[J]. , 2016, 24(10): 1431-1441. DOI： 10.1016/j.cjche.2016.05.041.

摘要

Abstract

The output feedback model predictive control (MPC)

for a linear parameter varying (LPV) process system including unmeasurable model parameters and disturbance (all lying in known polytopes)

is considered. Some previously developed tools

including the norm-bounding technique for relaxing the disturbance-related constraint handling

the dynamic output feedback law

the notion of quadratic boundedness for specifying the closed-loop stability

and the ellipsoidal state estimation error bound for guaranteeing the recursive feasibility

are merged in the control design. Some previous approaches are shown to be the special cases. An example of continuous stirred tank reactor (CSTR) is given to show the effectiveness of the proposed approaches.

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