Identification of Hysteresis in Dynamic Systems

Hysteresis is a phenomenology commonly encountered in a wide variety of engineering and science disciplines, including solid mechanics, electromagnetism and aerodynamics. Most studies tackling hysteresis identification in the technical literature follow white-box approaches, i.e. they rely on the assumption that measured data obey a specific hysteretic model. Such an assumption may be a hard requirement to handle in real applications, since hysteresis is a highly individualistic nonlinear behaviour.


In this research, a black-box approach based on nonlinear state-space models is adopted to identify hysteresis in dynamic systems. This approach is shown to provide a general framework to hysteresis identification, featuring flexibility and parsimony of representation. Nonlinear model terms are constructed as a multivariate polynomial in the state variables, and parameter estimation is performed by minimising weighted least-squares cost functions. Different technical issues are also addressed, including the reduction of parameters through tensor transformations.

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