Quasi-min-max output-feedback model predictive control for LPV systems with input saturation

• Published in: International journal of control, automation, and systems Vol. 15; no. 3; pp. 1069 - 1076
• Main Authors: Kim, Tae-Hyoung, Lee, Ho-Woon
• Format: Journal Article
• Language: English
• Published: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.06.2017; Springer Nature B.V; 제어·로봇·시스템학회
• Subjects: Closed loop systems; Constraint modelling; Control; Control stability; Effectiveness; Engineering; Feedback control systems; Input output; Linear programming; Mechatronics; Output feedback; Predictive control; Regular Papers; Robotics; Robust control; Studies; 제어계측공학; model predictive control; Constrained systems; linear parameter varying systems; linear matrix inequality; quasi-min-max optimization
• ISSN: 1598-6446; 2005-4092
• DOI: 10.1007/s12555-016-0378-y

In the research field of model predictive control (MPC), an output-feedback-type MPC method is consistently required for controlling a wide range of constrained systems. In this paper, we propose a two-stage control strategy for polytopic linear parameter varying (LPV) systems subject to input constraints. This strategy consists of a modified quasi-min-max output-feedback MPC method and a novel terminal output-feedback robust control technique. The proposed control mechanism involves the system states to be first controlled via the MPC method to be driven into a prescribed neighborhood of the origin, and then, the terminal output-feedback robust control method guaranteeing the input constraints is applied to make such states converge to the origin. It is also verified that our control method guarantees the closed-loop stability and feasibility in the presence of model uncertainties and input constraints. Finally, a numerical example is given to demonstrate its effectiveness.