Abstract
The importance of the obstacle avoidance problem is stressed in [4]. Computation of reachability sets for the obstacle avoidance problem is addressed, for continuous-time systems in [4, 5] and for discrete-time systems in [12]; further results appear in, for instance [2, 17, 18]. 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) [9, 11, 14] 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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Raković, S.V., Mayne, D.Q. (2007). Robust Model Predictive Control for Obstacle Avoidance: Discrete Time Case. In: Findeisen, R., Allgöwer, F., Biegler, L.T. (eds) Assessment and Future Directions of Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences, vol 358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72699-9_52
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DOI: https://doi.org/10.1007/978-3-540-72699-9_52
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