Identification of linear time-varying dynamic systems based on the WKB method

Abstract This work proposes a new parameter identification method based on the Wentzel-Kramers-Brillouin (WKB) approximation for slow linear time-varying (LTV) dynamic systems. The considered time period is divided into series of short windows. In each window, assumption “short linearly varying” parameters employed, and nonlinear optimization problem solved using WKB results LTV system. A search algorithm developed to find optimal solution. process, only one type response signal (displacement, velocity or acceleration) required. Thus, numerical differentiation integration measured signal, which leads truncation cumulative errors in noise environment, avoided. accuracy robustness are validated by applying it particular system with stiffness.