Robust Output-Feedback MPC With Integral Action

• Published in: IEEE transactions on automatic control Vol. 55; no. 7; pp. 1531 - 1543
• Main Authors: Løvaas, Christian, Seron, María M, Goodwin, Graham C
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.07.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Computer science; control theory; systems; Control system synthesis; Control theory. Systems; Convergence; Cost function; Design engineering; Disturbances; Dynamical systems; Exact sciences and technology; Integrals; Invariants; Mathematical model; Mathematical models; Model predictive control (MPC); Modelling and identification; Optimal control; Predictive control; Predictive models; Robust control; Robust stability; Robustness; State estimation; Uncertainty; Feedback regulation; Output signal; Modeling; Closed feedback; Robust control; Model predictive control; Control constraint; Model predictive control (MPC); Linear time invariant system; Uncertain system; Imperfect information; Observer; Open loop; System identification; Dynamic model; Output feedback
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2010.2042344

In this paper, we propose a robust output-feedback model predictive control (MPC) design for a class of open-loop stable systems, having non-vanishing output disturbances, hard constraints and linear-time invariant model uncertainty. Integral action is included in the proposed design by utilizing a linear estimator for both the output disturbance and the system state. The main distinction from previous work on robust MPC design (with integral action) is that we establish robust convergence in the face of both imperfect state information and dynamic model uncertainty.