Data-Driven Adaptive Tracking Control of Piezoelectric-Actuated Motion Stage Using a Multi-Factor Objective Function

This brief proposes a modified data-driven adaptive tracking control (MDDATC) scheme for a piezoelectric-actuated motion stage (PAMS) via the full form dynamic linearization (FFDL) technique and a multi-factor objective function. First, the FFDL method is employed to build a data model for the PAMS. Then, to improve the transient performance of the PAMS, a novel multi-factor objective function is proposed to obtain the control law. Specifically, the multi-factor objective function consists of the tracking error, change rate of the tracking error, and forward difference of the control law. In addition, the theoretical analysis is provided to guarantee that the closed-loop system is semi-globally uniformly ultimately bounded. Finally, comparative experiments conducted on the PAMS are presented to demonstrate the effectiveness of the proposed MDDATC scheme.