Parameter identification of composite J-A hysteresis model based on Grey Wolf Optimization

When using the J-A hysteresis model to analyze the hysteresis loop, the focus is to accurately identify the five key parameters that need to be defined, but the parameter identification is found to be difficult during the analysis. This paper proposes to introduce the Grey Wolf Optimization (GWO) into the parameter identification of the J-A hysteresis model. The GWO has the advantages of clear logic, simple structure and strong optimization ability.