A Robust Data-Driven Controller Design Methodology With Applications to Particle Accelerator Power Converters

Abstract

A new data-driven approach using the frequency response function (FRF) of a system is proposed for designing robust-fixed structure digital controllers for particle accelerators’ power converters. This design method ensures that the dynamics of a system are captured and avoid the problem of unmodeled dynamics associated with parametric models. The $H_{\infty }$ robust performance condition can be represented by a set of convex constraints with respect to the parameters of a two degree of freedom RST controller. This controller is robust with respect to the frequency-dependent uncertainties of the FRF. A convex optimization algorithm is implemented to obtain the controller parameters. The effectiveness of the method is illustrated by considering two case studies that require robust controllers for achieving the desired performance.