This study explores the course tracking control problem of unmanned surface vessels (USVs) under the influence of actuator faults and internal and external uncertainties. In the control strategy desig n, we first model the unknown dynamics and use adaptive technology to construct an online appro ximator to compensate for the unknown dynamics of the system. Under the framework of adaptive backstepping, a robust adaptive course tracking control scheme is constructed. This control strategy does not require any prior knowledge of the model in advance. The stability analysis of the theoret ical mathematical derivation of the control strategy was conducted based on Lyapunov stability theo ry. Finally, the effectiveness of the control strategy proposed in this paper was verified through sim ulation.

A robust adaptive control approach is proposed for underactuated surface ship linear path-tracking control system based on the backstepping control method and Lyapunov stability theory. By employing T-S fuzzy system to approximate nonlinear uncertainties of the control system, the proposed scheme is developed by combining “dynamic surface control” (DSC) and “minimal learning parameter” (MLP) techniques. The substantial problems of “explosion of complexity” and “dimension curse” existed in the traditional backstepping technique are circumvented, and it is convenient to implement in applications. In addition, an auxiliary system is developed to deal with the effect of input saturation constraints. The control algorithm avoids the singularity problem of controller and guarantees the stability of the closed-loop system. The tracking error converges to an arbitrarily small neighborhood. Finally, MATLAB simulation results are given from an application case of Dalian Maritime University training ship to demonstrate the effectiveness of the proposed scheme.

This paper presents a dynamic compensation methodology for robust trajectory tracking control of uncertain robot manipulators. To improve tracking performance of the system, a full model-based feedforward compensation with continuous VS-type robust control is developed in this paper(i.e,. robust decentralized adaptive control scheme). Since possible bounds of uncertainties are unknown, the adaptive bounds of the robust control is used to directly estimate the uncertainty bounds(instead of estimating manipulator parameters as in centralized adaptive control0. The global stability and robustness issues of the proposed control algorithm have been investigated extensively and rigorously via a Lyapunov method. The presented control algorithm guarantees that all system responses are uniformly ultimately bounded. Thus, it is shown that the control system is evaluated to be highly robust with respect to significant uncertainties.