Hysteresis is a nonlinear characteristic ubiquitously exhibited by smart material sensors and actuators, such as piezoelectric actuators, shape memory alloys, and ionic polymer metal composite (IPMC) sensors. The Prandtl-Ishlinskii (PI) operator is widely used to describe hysteresis of smart material systems, due to its simple structure and the existence of analytical inverse. A PI operator consists of a weighted superposition of play (backlash) operators. While adaptive estimation of  the weights for PI operators has been reported in the literature, rigorous analysis of parameter convergence is lacking. In this paper, we establish persistent excitation and thus parameter convergence for adaptive weight estimation under a rather modest condition on the input to the PI operator. The analysis is further supported via simulation, where a recursive least square (RLS) method is adopted for parameter estimation.


Adaptive Parameter Estimation With Convergence Analysis for the Prandtl-Ishlinskii Hysteresis Operator

Division / Sponsors: 
Dynamic Systems & Control (DSCD)

Paper Proceedings: https://asmedigitalcollection.asme.org/DSCC/DSCC2020/volume/84270

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