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Proactive fault‐tolerant model predictive control
Author(s) -
Lao Liangfeng,
Ellis Matthew,
Christofides Panagiotis D.
Publication year - 2013
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.14074
Subject(s) - control reconfiguration , fault tolerance , model predictive control , robustness (evolution) , context (archaeology) , actuator , control engineering , control theory (sociology) , process control , fault (geology) , process (computing) , fault detection and isolation , engineering , computer science , control system , controller (irrigation) , stuck at fault , control (management) , reliability engineering , artificial intelligence , embedded system , chemistry , biology , operating system , paleontology , biochemistry , agronomy , seismology , electrical engineering , gene , geology
Fault‐tolerant control methods have been extensively researched over the last 10 years in the context of chemical process control applications, and provide a natural framework for integrating process monitoring and control aspects in a way that not only fault detection and isolation but also control system reconfiguration is achieved in the event of a process or actuator fault. But almost all the efforts are focused on the reactive fault‐tolerant control. As another way for fault‐tolerant control, proactive fault‐tolerant control has been a popular topic in the communication systems and aerospace control systems communities for the last 10 years. At this point, no work has been done on proactive fault‐tolerant control within the context of chemical process control. Motivated by this, a proactive fault‐tolerant Lyapunov‐based model predictive controller (LMPC) that can effectively deal with an incipient control actuator fault is proposed. This approach to proactive fault‐tolerant control combines the unique stability and robustness properties of LMPC as well as explicitly accounting for incipient control actuator faults in the formulation of the MPC. Our theoretical results are applied to a chemical process example, and different scenaria were simulated to demonstrate that the proposed proactive fault‐tolerant model predictive control method can achieve practical stability and efficiently deal with a control actuator fault. © 2013 American Institute of Chemical Engineers AIChE J , 59: 2810–2820, 2013