Work

Parameter-Dependent Robust Control Invariant Sets for LPV Systems With Bounded Parameter-Variation Rate

Year: 2024

Type: article

Abstract: Real-time measurements of the scheduling parameter oflinear parameter-varying(LPV) systems enable the synthesis ofrobust control invariant(RCI) sets and parameter-dependent controllers inducing invariance. We present a method to synthesizeparameter-dependent RCI(PD-RCI) sets for LPV systems with bounded parameter variation, in which invariance is induced using PD-vertex control laws. The PD-RCI sets are parameterized asconfiguration-constrainedpolytopes that admit a joint parameterization of their facets and vertices. The proposed sets and associated control laws are computed by solving a single semidefinite programming problem. Through numerical examples, we demonstrate that the proposed method outperforms state-of-the-art methods for synthesizing PD-RCI sets, both with respect to conservativeness and computational load.

Source: IEEE Transactions on Automatic Control

DOI: 10.1109/tac.2024.3454528

Authors: Sampath Kumar Mulagaleti, Manas Mejari, Alberto Bemporad

Institutions: University of Trento, University of Applied Sciences and Arts of Southern Switzerland, Dalle Molle Institute for Artificial Intelligence Research, Università della Svizzera italiana, IMT School for Advanced Studies Lucca

Language: English

Topic: Advanced Control Systems Optimization

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: Hasler Stiftung

OpenAlex ID: W4402209030

FWCI: 0.942

Cites: 33

Cited by: 7

Related to: 10