A New Data-Driven Approach of Reference Shaping

In this paper, we propose a data-driven method of reference shaping to improve the tracking performance of uncertain linear systems. The proposed method can be implemented on a system based on its input-output data; the finite-time L2-norm of the tracking error, estimated using the data, can be minimized. Moreover, the proposed algorithm can be extended for cases where the control inputs are constrained owing to actuation limits. The effectiveness of the proposed method is demonstrated through a numerical simulation and an experiment conducted using the cart system.