Suboptimal model predictive control of hybrid systems based on mode-switching constraints
Document typeConference report
PublisherIEEE Press. Institute of Electrical and Electronics Engineers
Rights accessOpen Access
Model predictive control (MPC) is recognized as a very versatile and effective way of controlling constrained hybrid dynamical systems in closed-loop. The main drawback of hybrid MPC is the heavy computation burden of the associated on-line mixed-integer optimization. Explicit MPC solutions overcome such a problem by rewriting the control law in piecewise affine form, but are limited to relatively simple hybrid control problem setups. This paper presents an alternative approach for reducing the complexity of computations by suitably constraining the mode sequence over the prediction horizon, so that on-line optimization is solved more quickly. While tracking performance of the feedback loop may be affected because of the suboptimality of the approach, closedloop stability is guaranteed. The effectiveness of the method is demonstrated by an example.
CitationIngimundarson, A.; Ocampo-Martinez, C.; Bemporad, A. Suboptimal model predictive control of hybrid systems based on mode-switching constraints. A: IEEE Conference on Decision & Control. "46th IEEE Conference on Decision and Control". New Orleans, LA: IEEE Press. Institute of Electrical and Electronics Engineers, 2007, p. 5264-5269.