2024/10/01 by Tanay Kumar, Kumar, Tanay, Raktim Bhattacharya +1 · 1 citation
Engineering · Physics and Astronomy · #Control and Stability of Dynamical Systems #FOS: Electrical engineering #FOS: Mathematics #Iterative Learning Control Systems #Model Reduction and Neural Networks #Optimization and Control (math.OC) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2410.01118
openalex publication_date 2024/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper addresses the sparse actuation problem for nonlinear systems represented in the Linear Parameter-Varying (LPV) form. We propose a convex optimization framework that concurrently determines actuator magnitude limits and the state-feedback law that guarantees a user-specified closed-loop performance in the H2/H_∞ sense. We also demonstrate that sparse actuation is achieved when the actuator magnitude-limits are minimized in the l1 sense. This is the first paper that addresses this problem for LPV systems. The formulation is demonstrated in a vibration control problem for a flexible wing.