Dual extended state observer-based course tracking control of unmanned surface vehicles with signal quantization

This paper investigates adaptive course tracking control of unmanned surface vehicles (USVs) with state and input quantization. Considering the characteristics of ship rudder servo systems, a nonlinear third-order response model is established. A control law is designed using the backstepping approach and combined with dynamic surface control to reduce the computational complexity associated with virtual control laws. Furthermore, a dual extended state observer (ESO) architecture is developed to simultaneously estimate the matched and mismatched disturbances in the ship course tracking control system. A uniform quantizer is employed for the system states and control inputs, thereby reducing the frequency of control execution and effectively addressing the communication constraints encountered by USVs during maritime operations. Lyapunov stability analysis shows that the closed-loop system is stable and that all signals remain bounded. Finally, simulation results verify the effectiveness and practical applicability of the proposed adaptive quantized control strategy.