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A performance optimization algorithm for controller reconfiguration in fault tolerant distributed model predictive control

delete2015-10-01
delete25
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OA
AI
A
Alexey Zakharov *
Z
Zattoni, Elena
M
Miao Yu
S
Sirkka‐Liisa Jämsä‐Jounela
DOI:10.1016/j.jprocont.2015.07.006delete
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Abstract

Abstract

En 中文
This paper presents a performance optimization algorithm for controller reconfiguration in fault tolerant distributed model predictive control for large-scale systems. After the fault has been detected and diagnosed, several controller reconfigurations are proposed as candidate corrective actions for fault compensation. The solution of a set of constrained optimization problems with different actuator and setpoint reconfigurations is derived by means of an original approach, exploiting the information on the active constraints in the non-faulty subsystems. Thus, the global optimization problem is split into two optimization subproblems, which enable the online computational burden to be greatly reduced. Subsequently, the performances of different candidate controller reconfigurations are compared, and the better performing one is selected and then implemented to compensate the fault effects. Efficacy of the proposed approach has been shown by applying it to the benzene alkylation process, which is a benchmark process in distributed model predictive control. (C) 2015 Elsevier Ltd. All rights reserved.
Keywords:
Distributed model predictive control
Fault tolerant control
Controller reconfiguration
Constrained optimization
Alkylation of benzene
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Journal

Journal of Process Control cover
Journal of Process Control
IF:
3.9
Papers:
3.4K
Citations:
7.3K

Organization

A
Aalto University
Scholars:
1.6W
Papers: 1.5W
Citations: 2.1W
U
University of Bologna
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4.5W
Papers: 3.8W
Citations: 4.1W