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On real-time robust model predictive control


M.N. Zeilinger, D. M. Raimondo, A. Domahidi, M. Morari, C.N. Jones

Automatica, vol. 50, no. 3, pp. 683694

High-speed applications impose a hard real-time constraint on the solution of a model predictive control (MPC) problem, which generally prevents the computation of the optimal control input. As a result, in most MPC implementations guarantees on feasibility and stability are sacrificed in order to achieve a realtime setting. In this paper we develop a real-time MPC approach for linear systems that provides these guarantees for arbitrary time constraints, allowing one to trade off computation time vs. performance. Stability is guaranteed by means of a constraint, enforcing that the resulting suboptimal MPC cost is a Lyapunov function. The key is then to guarantee feasibility in real-time, which is achieved by the proposed algorithm through a warm-starting technique in combination with robust MPC design. We address both regulation and tracking of piecewise constant references. As a main contribution of this paper, a new warm-start procedure together with a Lyapunov function for real-time tracking is presented. In addition to providing strong theoretical guarantees, the proposed method can be implemented at high sampling rates. Simulation examples demonstrate the effectiveness of the real-time scheme and show that computation times in the millisecond range can be achieved.


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title = "On real-time robust model predictive control ",
journal = "Automatica ",
volume = "50",
number = "3",
pages = "683 - 694",
year = "2014",
note = "",
issn = "0005-1098",
doi = "",
url = "",
author = "Melanie N. Zeilinger and Davide M. Raimondo and Alexander Domahidi and Manfred Morari and Colin N. Jones",
keywords = "Real-time model predictive control",
keywords = "Linear systems",
keywords = "Optimal control "
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