Data-driven Quantized Control of Unknown Linear Systems with Uncertainties

Abstract

In this paper, we propose a quantized stabilization method for unknown discrete-time linear systems with uncertainty. In previous studies, the coarsest logarithmic quantizer design has been given for unknown linear systems using direct data-driven control method. However, in real linear systems, the closed-loop system may become unstable due to the perturbation of the system parameters caused by changes in the environment or aging. In this paper, we extend the logarithmic quantizer design for linear systems with uncertainty to take account of such uncertainties, which may not be reflected in the original system data. We illustrate the effectiveness of the method through numerical simulations.