Identification of nonlinear systems with rate saturation

This paper focuses on identification of systems with rate saturation nonlinearity, considering measurement and process noises. A methodology is proposed to estimate the parameters of linear dynamics along with the upper and lower limits of rate saturation, using only system input and output. The methodology consists of four correlative parts which sequentially are choosing sine sweep signal with appropriate amplitude and frequency as input to excite the system sufficiently, designing a Kalman filter based on the constant rate model to obtain rate optimal estimation, suggesting a window scanning and filtrating method which deals with rate estimation to identify rate saturation limits, and applying the bias compensation recursive least squares with valid input and output data filtrated by the estimated rate limits to identify linear dynamics. Simulation results of a position servo system with rate saturation are presented to illustrate the validity of the proposed technique.