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Periodic Set Invariance as a Tool for Constrained Reference Tracking

Abstract : This paper explores the concept of periodic invariance and its use for trajectory tracking problems subject to state and input constraints, offering important computational advantages. In principle, traditional techniques based on receding horizon optimization are computationally expensive due to long prediction and optimization horizons, and number of control and state constraints in a constrained control problem. Their complexity is further affected by additional constraints needed to ensure recursive feasibility via a controllable invariant set. Practically, such invariant sets are difficult to obtain off-line and use them on-line. To overcome this problem, this paper suggests to employ periodic invariant sets as a simple set-theoretic tool for constrained reference tracking problems.
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Contributor : Martin Soyer Connect in order to contact the contributor
Submitted on : Thursday, January 14, 2021 - 3:15:00 PM
Last modification on : Sunday, June 26, 2022 - 2:28:33 AM
Long-term archiving on: : Thursday, April 15, 2021 - 7:06:16 PM


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  • HAL Id : hal-02899420, version 1


Martin Soyer, Sorin Olaru, Konstantinos Ampountolas, Sheila Scialanga, Zhou Fang. Periodic Set Invariance as a Tool for Constrained Reference Tracking. IFAC World Congress, Jul 2020, Berlin (virtual), Germany. ⟨hal-02899420⟩



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