Modified Sine Cosine Algorithm for Identification of Liquid Slosh based on Continuous-time Hammerstein Model

Abstract

Abstract This paper presents the identification of liquid slosh plant using the Hammerstein model based on modified Sine Cosine Algorithm (mSCA). A remote car that carries a container of liquid is considered as a liquid slosh experimental rig. In contrast to other research works, this paper considers a piece-wise affine function in a nonlinear function of the Hammerstein model, which is more generalized function. Moreover, a continuous-time transfer function is utilized in the Hammerstein model, which is more suitable to represent a real system. The mSCA method is used to tune both coefficients in the nonlinear function and the transfer function of the Hammerstein model such that the error between the identified output and the real experimental output is minimized. The effectiveness of the proposed framework is assessed in terms of the convergence curve response, output response, and the stability of the identified model through the pole-zero map. The results show that the mSCA based method is able to produce a Hammerstein model that yields identified output response closes to the real experimental slosh output with 82.12 % improvement of sum of quadratic error.