This paper develops a robust self-triggered control algorithm for time-varying and uncertain systems with constraints based on reachability analysis. The resulting piecewise constant control inputs achieve communication reduction and guarantee constraint satisfactions. In the particular case when there is no uncertainty, we propose a control design with minimum number of samplings over finite time horizon. Furthermore, when the plant is linear and the constraints are polyhedral, we prove that the previous algorithms can be reformulated as computationally tractable mixed integer linear programs. The method is compared with the robust self-triggered model predictive control in a numerical example and applied to a robot motion planning problem with temporal constraints. ; QC 20190913
Robust self-triggered control for time-varying and uncertain constrained systems via reachability analysis
2019-01-01
Scopus 2-s2.0-85068268315
Article (Journal)
Electronic Resource
English
DDC: | 629 |
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