Elucidation of the role of constraints in economic model predictive control

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• 作者：Matthew Ellis^aAuthor Vitae ; Helen Durand^aAuthor Vitae ; Panagiotis D. Christofides ; ^a ; ^b ; ^{pdc@seas.ucla.edu" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Economic model predictive control ; Process economic optimization ; Process control ; Nonlinear systems
• 刊名：Annual Reviews in Control
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：41
• 期：Complete
• 页码：208-217
• 全文大小：723 K

文摘

Economic model predictive control (EMPC) is a predictive feedback control methodology that unifies economic optimization and control. EMPC uses a stage cost that reflects the process/system economics. In general, the stage cost used is not a quadratic stage cost like that typically used in standard tracking model predictive control. In this paper, a brief overview of EMPC methods is provided. In particular, the role of constraints imposed in the optimization problem of EMPC for feasibility, closed-loop stability, and closed-loop performance is explained. Three main types of constraints are considered including terminal equality constraints, terminal region constraints, and constraints designed via Lyapunov-based techniques. The paper closes with a well-known chemical engineering example (a non-isothermal CSTR with a second-order reaction) to illustrate the effectiveness of time-varying operation to improve closed-loop economic performance compared to steady-state operation and to demonstrate the impact of economically motivated constraints on optimal operation.