Work

Improved Quasi-Min-Max MPC for Constrained LPV Systems via Nonlinearly Parameterized State Feedback Control

Year: 2024

Type: conference-paper

Abstract: We consider the regulation problem of linear parameter varying systems with input and state constraints. It is assumed that the time-varying parameters are available at the current time, but their future behavior is unknown and contained in a polytopic set. The aim is to design a new stabilizing quasi-min-max MPC algorithm via a nonlinearly parameterized state feedback control law. It is shown that the use of such a control law leads to less conservative results compared to those derived from linearly parameterized state feedback control laws. At each time instant, a convex semi-definite optimization problem is required to solved. Two numerical examples, including a non-quadratically stabilizable system, are given with comparison to earlier solutions from the literature to illustrate the effectiveness of the proposed approaches.

Source: Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes

DOI: 10.1109/cdc56724.2024.10886262

Authors: Jin Yan, Hoai-Nam Nguyen, Nel Samama

Institutions: Institut Polytechnique de Paris, Télécom SudParis, Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux

Language: English

Topic: Advanced Control Systems Optimization

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4402384356

FWCI: 1.376

Cites: 18

Cited by: 2

Related to: 10