Adaptive prescribed performance tracking control for underactuated unmanned surface ships with input quantization

This article investigates the preset performance trajectory tracking control problem of underactuated unmanned surface ships with model uncertainty, unknown external environmental disturbances, and input quantization effects. We consider the non-diagonal damping matrix and mass matrix to satisfy the actual dynamics model of underactuated unmanned surface ships. By adding a hysteresis quantizer, the control method proposed in this article effectively reduces the quantization error. Neural networks are employed to approach the unknown environmental disturbance of underactuated unmanned surface ships. Using the error transformation function, the constrained control problem is transformed into an unconstrained one to ensure the preset performance of tracking errors. This paper verifies the superiority and effectiveness of the proposed control method through Lyapunov stability analysis.