System Identification of Air Cushion Vehicle Motion Model Based on EKF

Abstract

The motion model of air cushion vehicle is the foundation for analyzing its maneuvering characteristics and design training simulation system. The motion model can be affected by the mutual coupling of multiple factors, is difficult to established. In this paper, the method of estimating the parameters of the nonlinear system by the extend Kalman filter (EKF) is introduced. According to separate modeling method, combined with aerodynamics and hydrodynamics, the model of form-drag (moment), Aerodynamic force (moment), hydrodynamic force (moment), propeller propulsion force (moment), rudder force (moment), and force (moment) generated by side wind gates are generated. The known parameters of LCAC are substituted into the MMG model for Z-shaped simulation test to estimate the feasibility of EKF in identifying the parameters of air cushion vehicle motion model. And the results show that the method can be practical to use in system identification of air cushion vehicle motion model.