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Robust Model Predictive Control for Obstacle Avoidance: Discrete Time Case


Sasa V. Rakovic, D. Mayne

Lecture Notes in Control and Information Sciences (LNCIS), vol. 358, pp. 617-627, Assessment and Future Directions of Nonlinear Model Predictive Control. Editors: Rolf Findeisen, Frank Allgöwer and Lorenz T. Biegler

The obstacle avoidance problem is inherently non–convex. Most existing results are developed for the deterministic case when external disturbances are not present. The main purpose of this paper is to demonstrate that the obstacle avoidance problem in the discrete time setup has considerable structure even when disturbances are present. We extend the robust model predictive schemes using tubes (sequences of sets of states) to address the robust obstacle avoidance problem and provide a mixed integer programming algorithm for robust control of constrained linear systems that are required to avoid specified obstacles. The resultant robust optimal control problem that is solved on–line has marginally increased complexity compared with that required for model predictive control for obstacle avoidance in the deterministic case.


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% Autogenerated BibTeX entry
@Article { RakMay:2007:IFA_3032,
    author={Sasa V. Rakovic and D. Mayne},
    title={{Robust Model Predictive Control for Obstacle Avoidance:
	  Discrete Time Case}},
    journal={Lecture Notes in Control and Information Sciences (LNCIS)},
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