Adaptive prescribed performance tracking control for underactuated unmanned surface ships with input quantization
Abstract
This article investigates the preset performance trajectory tracking control problem of underactuated unmanned sur-face ships with model uncertainty, unknown external environmental disturbances, and input quantization effects. Weconsider the non-diagonal damping matrix and mass matrix to satisfy the actual dynamics model of underactuatedunmanned surface ships. By adding a hysteresis quantizer, the control method proposed in this article effectivelyreduces the quantization error. Neural networks are employed to approach the unknown environmental disturbanceof underactuated unmanned surface ships. Using the error transformation function, the constrained control problemis transformed into an unconstrained one to ensure the preset performance of tracking errors. This paper verifies thesuperiority and effectiveness of the proposed control method through Lyapunov stability analysis
