Faleschini, Michelangelo (University La Sapienza, Rome), Cristofaro, Andrea (Sapienza University of Rome)

Data-Driven Control Design and Input Allocation for Strongly Redundant LPV Systems

Scheduled for presentation during the Regular Session "Linear systems" (WeCA), Wednesday, June 11, 2025, 16:50−17:10,

33rd Mediterranean Conference on Control and Automation, June 10-13, 2025, Tangier, Morocco

This information is tentative and subject to change. Compiled on May 9, 2025

Abstract

In this paper, a new data-driven input allocation procedure is proposed for strongly input redundant systems, generalizing a recent data-based representation result for LTI systems. This algorithm assumes a Linear Parameter Varying (LPV) structure to implicitly model the unknown system using only collected input-state data, and directly computes the null space basis of the input matrix for a linear dynamic input allocator. A complete data-driven LPV control and allocation scheme are then presented implementing a recent semidefinite LPV control program for quadratic stabilization. Finally, this scheme is tested in simulation on a overactuated marine vessel system, along with an analysis of its practical usage and performance evaluation.