Adaptive Control of Positioning Systems With Hysteresis Based on Magnetic Shape Memory Alloys

This paper considers a control strategy for systems affected by time-varying hysteretic phenomena, such as those observed in magnetic shape memory alloys subject to temperature variations. The proposed controller is based on a scheme that combines feedforward cancellation of the hysteresis using a modified Prandtl-Ishlinskii inverse model with a closed-loop control law designed to address the cancellation errors. Both the inverse hysteresis model and the closed-loop law feature adjustable parameters that are adapted online by means of learning laws based on Lyapunov design tools. The effectiveness of the proposed approach is confirmed by experiments on a prototypical micrometric positioning system containing a bar of MSMA as main actuating element.