A Dynamic Mode Decomposition Based Data-Driven Tracking Control for Discrete-time Linear Systems

This paper focuses on data-driven tracking control of discrete-time linear systems. The desired reference for the output to track is generated by a dynamic system. First, we develop a dynamic mode decomposition-based data parameterization of the reference dynamics. Then, we present an internal model-based data-driven state feedback controller that can solve the tracking problem. A distinguishing feature of our result is that our designed controller is independent of the priori dynamics that generate the desired reference. A simulation example is also presented to show the efficiency of our data-driven tracking control design.