Nonlinear system identification using genetic algorithm

This paper presents an evolutionary system identification method for mechatronics systems which include various nonlinearities. In our research, the saturation in power converters and the friction in mechanisms are considered as the nonlinear elements, some of which are generally difficult to detect, and/or identify directly. The proposed method can determine the structure of linear and nonlinear elements of the system simultaneously by genetic algorithm. In the polynomial model by the proposed method, the observable input/output variables express the linear components, and the power series of variables and nonlinear functions express the nonlinear ones. Genetic algorithm is utilized to optimize the combination of these variables. The effectiveness of the proposed method is verified by the experiments using a 2-mass resonant, vibration system