Characterization and computation of control invariant sets within target regions for linear impulsive control systems
Ignacio Sanchez, Christophe Louembet, Marcelo Actis, Alejandro H., Gonzalez

TL;DR
This paper develops a novel approach to characterize and compute control invariant sets for linear impulsive systems within target regions, enabling effective zone tracking with a set-based model predictive controller.
Contribution
It introduces a non-conservative, polynomial positivity-based method for exact and approximate invariant set computation tailored to impulsive systems with rational eigenvalues.
Findings
Explicit impulsive invariant sets enable zone tracking.
Proposed MPC ensures asymptotic convergence within target zones.
Method applicable to systems with rational eigenvalues.
Abstract
Linear impulsively controlled systems are suitable to describe a venue of real-life problems, going from disease treatment to aerospace guidance. The main characteristic of such systems is that they remain uncontrolled for certain periods of time. As a consequence, punctual equilibria characterizations outside the origin are no longer useful, and the whole concept of equilibrium and its natural extension, the controlled invariant sets, needs to be redefined. Also, an exact characterization of the admissible states, i.e., states such that their uncontrolled evolution between impulse times remain within a predefined set, is required. An approach to such tasks -- based on the Markov-Lukasz theorem -- is presented, providing a tractable and non-conservative characterization, emerging from polynomial positivity that has application to systems with rational eigenvalues. This is in turn the…
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Taxonomy
TopicsAdvanced Control Systems Optimization · Control Systems and Identification · Stability and Control of Uncertain Systems
