Velocity-transformation-based adaptive nonlinear extended state observer strategy for quantized posture-feedback tracking of underactuated surface vehicles with velocity constraints

초록

This paper investigates a quantized-posture-based tracking control strategy for uncertain underactuated surface vehicles (USVs) subject to time-varying velocity constraints. Only quantized measurements of position and heading angle are assumed to be available due to posture quantization. To address velocity constraints without relying on the feasibility conditions of virtual control laws, a USV model incorporating nonlinear velocity transformation is introduced. The core contribution of this paper is a novel adaptive nonlinear extended state observer (ANESO) tailored to the nonlinearly transformed USV model. In contrast to existing extended state observers, the proposed ANESO ensures both the satisfaction of velocity constraints and the estimation of unmeasurable velocities and uncertain nonlinearities. This design enables a robust approach to tackling the challenges posed by quantized feedback and system uncertainties. Building upon the ANESO, an adaptive tracking control strategy is proposed to address two key challenges: the nonlinear coupling of the virtual control variable and the unavailability of direct tracking error measurements between unquantized and desired postures. Adaptive tuning laws, derived using quantized posture feedback, are employed to compensate for unknown nonlinearities and parameter uncertainties resulting from quantization errors. The stability of the resulting ANESO-based quantized output-feedback tracking system is rigorously established using Lyapunov theory and the command-filtered backstepping method, and it is also proven that the velocity constraints are satisfied. Comparative simulation studies validate the effectiveness of the proposed approach, highlighting its advantages over existing methods.

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