Linear offset-free Model Predictive Control

• Published in: Automatica (Oxford) Vol. 45; no. 10; pp. 2214 - 2222
• Main Authors: Maeder, Urban, Borrelli, Francesco, Morari, Manfred
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-10-2009; Elsevier
• Subjects: Algorithms; Applied sciences; Asymptotic properties; Automation; Computer science; control theory; systems; Control theory. Systems; Exact sciences and technology; Integral control; Internal model principle; Mathematical models; Model predictive control; No offset; Predictive control; Reference tracking; Tracking; Integral control; Model predictive control; No offset; Reference tracking; Keywords; Asymptotic approximation; Model free control; Internal model principle; Modeling
• ISSN: 0005-1098; 1873-2836
• DOI: 10.1016/j.automatica.2009.06.005

This work addresses the problem of offset-free Model Predictive Control (MPC) when tracking an asymptotically constant reference. In the first part, compact and intuitive conditions for offset-free MPC control are introduced by using the arguments of the internal model principle. In the second part, we study the case where the number of measured variables is larger than the number of tracked variables. The plant model is augmented only by as many states as there are tracked variables, and an algorithm which guarantees offset-free tracking is presented. In the last part, offset-free tracking properties for special implementations of MPC schemes are briefly discussed.