Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter
1School of Automation Sciences and Electrical Engineering, Beihang University, XueYuan Road NO.37, Haidian District, Beijing 100191, China. zhangzhen@buaa.edu.cn.
Sensors (Basel, Switzerland)
|February 11, 2016
Summary
A new generalized play operator (GPO)-based adaptive filter accurately models rate-dependent hysteresis in smart actuators. This novel method outperforms traditional filters for giant magnetostrictive actuators.
Area of Science:
- Control Systems Engineering
- Nonlinear Dynamics
- Materials Science
Background:
- Smart actuators exhibit rate-dependent hysteresis, a complex nonlinear behavior that challenges accurate modeling.
- Existing models often struggle to capture the dynamic and rate-sensitive nature of hysteresis in actuators.
- Accurate modeling is crucial for precise control and performance optimization of smart actuators.
Purpose of the Study:
- To propose and evaluate a novel generalized play operator-based (GPO-based) nonlinear adaptive filter.
- To model the rate-dependent hysteresis nonlinearity specifically in smart actuators.
- To compare the performance of the proposed GPO-based filter against other adaptive filtering techniques and a phenomenological model.
Main Methods:
- Development of a GPO-based nonlinear adaptive filter using a tapped delay line and generalized play operators.
- Application of the least-mean-square (LMS) algorithm for adaptive weight adjustment.
- Comparative analysis with Volterra filters, backlash filters, linear adaptive filters, and the rate-dependent generalized Prandtl-Ishlinskii (RDGPI) model.
- Experimental application to model the rate-dependent hysteresis of a giant magnetostrictive actuator (GMA).
Main Results:
- The GPO-based adaptive filter demonstrated superior accuracy in modeling rate-dependent hysteresis compared to other methods.
- The proposed filter effectively captured the nonlinear dynamics of the giant magnetostrictive actuator.
- The GPO-based approach provided a more accurate and effective description of rate-dependent hysteresis.
Conclusions:
- The novel GPO-based nonlinear adaptive filter is a highly effective tool for modeling rate-dependent hysteresis in smart actuators.
- This method offers significant improvements over existing adaptive filtering techniques for complex nonlinear systems.
- The GPO-based filter shows great promise for enhancing the control and performance of actuators exhibiting hysteresis.
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