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 feed-forward 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 on-line by means of learning laws based on Lyapunov design tools. The effectiveness of the proposed approach is confirmed by experiments on a prototypical micro-metric positioning system containing a bar of magnetic shape memory alloy as main actuating element.