Adaptive Parameter Identification of Maritime Autonomous Surface Ships with Exponential Convergence

Abstract

This paper is concerned with the parameter identification of maritime autonomous surface ships (MASS) with fully unknown coefficients. An adaptive parameter identification method is proposed for an MASS to identify its model without the condition of the persistence of excitation (PE). Specifically, a composite adaptive update law is developed based on an integral filtering regression equation. By using this method, only the initial excitation (IE) condition is needed to assure the estimation convergence. A salient feature of the proposed method is that the acceleration information is totally not needed and only measured linear velocities and yaw rate are used for identification. Then, the stability of the online parameter identification method is proved by Lyapunov stability analysis, and the estimation errors exponentially converge to zero. Simulation results demonstrate the effectiveness of the proposed adaptive parameter identification method for the MASS.