Hysteresis is a nonlinearity exhibited by a wide class of smart materials, such as piezoelectrics and shape memory alloys, and it presents challenges in the control of smart material-actuated systems (for example, piezo-based nanopositioning systems). Existing methods for hysteresis compensation typically require an explicit model of the hysteresis, which tends to be high-dimensional operators and entails significant complexity in model identification and inversion. In this paper a novel hysteresis compensation method based on extended-high-gain observers and dynamic inversion is presented, which does not assume any specific hysteresis model. An extended high-gain observer is used to estimate the hysteresis output as well as other unknown dynamics of the system model, and then dynamic inversion is implemented to cancel the effect of hysteresis. With a mild assumption on the system and the input nonlinearity, the analysis of the closed-loop system under output feedback shows fast performance recovery to the trajectories of a target system, and that the tracking error converges exponentially to zero. Simulation results are presented to support the efficacy of the proposed approach.
- Dynamic Systems and Control Division
Hysteresis Compensation Using Extended High-Gain Observer and Dynamic Inversion
Chowdhury, D, Al-Nadawi, YK, & Tan, X. "Hysteresis Compensation Using Extended High-Gain Observer and Dynamic Inversion." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems. Atlanta, Georgia, USA. September 30–October 3, 2018. V002T24A005. ASME. https://doi.org/10.1115/DSCC2018-9082
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