Design of a Data‐Driven Control System Simultaneously Estimating Disturbance Signal Based on M_s Robustness

Abstract

The control system design scheme for improving disturbance response have been proposed in recent years. In general, system identification is required to estimate disturbance, and the control performance depends on an identification accuracy. In contrast, the data-driven control scheme has been proposed in which the control parameters are directly calculated from operational data without system identification. This paper proposes the data-driven control scheme that simultaneously designs a controller and a disturbance estimator. In the proposed scheme, the control parameters are calculated by using the least-squares method. Specifically, the disturbance is suppressed only using the desired reference model, controller and the adjustable parameter γ . Finally, the effectiveness of the proposed scheme is numerically demonstrated.