Nonlinear adaptive parameter estimation algorithms for hysteresis models of magnetostrictive actuators

James M. Nealis; Ralph C. Smith

doi:10.1117/12.475222

10 July 2002 Nonlinear adaptive parameter estimation algorithms for hysteresis models of magnetostrictive actuators

James M. Nealis, Ralph C. Smith

Proceedings Volume 4693, Smart Structures and Materials 2002: Modeling, Signal Processing, and Control; (2002) https://doi.org/10.1117/12.475222
Event: SPIE's 9th Annual International Symposium on Smart Structures and Materials, 2002, San Diego, California, United States

Abstract

Increased control demands in applications including high speed milling and hybrid motor design have led to the utilization of magnetostrictive transducers operating in hysteretic and nonlinear regimes. To achieve the high performance capabilities of these transducers, models and control laws must accommodate the nonlinear dynamics in a manner which is robust and facilitates real-time implementation. This necessitates the development of models and control algorithms which utilize known physics to the degree possible, are low order, and are easily updated to accommodate changing operating conditions such as temperature. We consider here the development of nonlinear adaptive identification for low order, energy-based models. We illustrate the techniques in the context of magnetostrictive transducers but they are sufficiently general to be employed for a number of commonly used smart materials. The performance of the identification algorithm is illustrated through numerical examples.

Citation Download Citation

James M. Nealis and Ralph C. Smith "Nonlinear adaptive parameter estimation algorithms for hysteresis models of magnetostrictive actuators", Proc. SPIE 4693, Smart Structures and Materials 2002: Modeling, Signal Processing, and Control, (10 July 2002); https://doi.org/10.1117/12.475222

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