Nonlinear hysteretic parameter identification using improved artificial bee colony algorithm

Abstract

Hysteresis is a common phenomenon arising in many engineering applications. It describes a memory-based relation between the restoring force and the displacement. Identification of the hysteretic parameters is central to practical application of the hysteretic models. To proceed so, a noteworthy thing is that the hysteretic models are often complex and non-differentiable so that getting the gradients is never straightforward and therefore, the swarm-based algorithm is often preferable to inverse hysteretic parameter identification. Along these lines, an improved artificial bee colony algorithm is developed in this paper for general hysteretic parameter identification. On the one hand, several hysteretic models along with the extensions to tackle the degradation and pinching behaviours are considered and how to model a structure with hysteretic components is also elaborated. As a result, the governing equation for the direct problem is established. On the other hand, the differential evolution mechanism is introduced to improve the original artificial bee colony algorithm. Numerical examples are conducted to testify the feasibility and accuracy of the proposed method in nonlinear hysteretic parameter identification.