Disturbance observer based adaptive trajectory tracking control for Unmanned Surface Vehicle with input and state quantization

This paper explores the disturbance observer based adaptive trajectory tracking control strategy of Unmanned Surface Vehicle with input and state quantization. To devise the controller without prior knowledge of quantization parameters, a linear analytical model of input quantization is introduced, facilitating adaptive parameter estimation. Estimations of external disturbances and quantized states are obtained through the application of a disturbance observer. Additionally, the control law is constructed using a combination of backstepping control and dynamic surface techniques. By leveraging Lyapunov stability theory, this paper demonstrates the stability of the trajectory tracking control system for Unmanned Surface Vehicle with input and state quantization, as well as the boundedness of errors between quantized and non-quantized variables within the closed-loop control system. Finally, the effectiveness of the proposed tracking approach is validated through comprehensive simulation experiments.