Identification of Inverted Pendulum System Using Frequency Domain Maximum Likelihood Estimation

Abstract

This paper explores the method of establishing dynamic model of inverted pendulum based on system identification. The maximum likelihood method in frequency domain is innovatively applied to identify the model parameters of the inverted pendulum system(IPS). The frequency domain maximum likelihood (ML) method is used to resolve the output error(OE) model with transient term for the system transfer function between the output state variables and the input variable. Finally, the parameters are identified using the frequency domain ML method and compared with the time-domain weighted least square method. Under the condition with only measured data, the experiment of a single inverted pendulum system with random time-varying control signal as excitation signal is designed. The numerical results show that the frequency domain ML method is effective in the identification of the inverted pendulum system.