Adaptive model predictive control for max-plus-linear discrete event input-output systems


Reference:
T.J.J. van den Boom, B. De Schutter, G. Schullerus, and V. Krebs, "Adaptive model predictive control for max-plus-linear discrete event input-output systems," IEE Proceedings - Control Theory and Applications, vol. 151, no. 3, pp. 339-346, May 2004.

Abstract:
Model predictive control (MPC) is a popular controller design technique in the process industry. Conventional MPC uses linear or nonlinear discrete-time models. Recently, we have extended MPC to a class of discrete event systems that can be described by a model that is "linear" in the max-plus algebra. In our previous work we have considered MPC for the time-invariant case. In this paper we consider an adaptive scheme for the time-varying case, based on parameter estimation of input-output models. In a simulation example we show that the combined parameter-estimation/MPC algorithm gives a good closed-loop behavior.


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Bibtex entry:

@article{vanDeS:03-017,
        author={T.J.J. {van den Boom} and B. {De Schutter} and G. Schullerus and V. Krebs},
        title={Adaptive model predictive control for max-plus-linear discrete event input-output systems},
        journal={IEE Proceedings -- Control Theory and Applications},
        volume={151},
        number={3},
        pages={339--346},
        month=may,
        year={2004},
        doi={10.1049/ip-cta:20040440}
        }



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