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

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.