A composite adaptive tracking controller for dynamically positioned surface vessels with only position measurements

Abstract

This work presents an alternative solution to the tracking control of dynamically positioned surface vessels having uncertainties associated with their dynamical model while using only vessel’s position measurements. Specifically, a surrogate state filter in conjunction with a composite parameter estimation algorithm is applied to ensure semi-global asymptotic convergence of the states of the vessel to their respective desired values. As opposed to its solely gradient based counterparts, the proposed algorithm utilizes an update law that is composed of a gradient update law driven by position tracking error and a least squares update law driven by the prediction error. This enables the proposed controller to compensate for the model uncertainties in a relatively shorter period of time. Rigorous analysis based on Lyapunov type approaches are applied in order to ensure the stability and boundedness of the closed loop system. Comparative simulations performed on the model of a surface vessel are presented in order to illustrate the tracking, and parameter estimation performance of the proposed controller/adaptation algorithm.