Neural Prescribed Performance Control for Uncertain Marine Surface Vessels without Accurate Initial Errors

Abstract

This paper deals with the problems concerned with the trajectory tracking control with prescribed performance for marine surface vessels without velocity measurements in uncertain dynamical environments, in the presence of parametric uncertainties, unknown disturbances, and unknown dead-zone. First, only the ship position and heading measurements are available and a high-gain observer is used to estimate the unmeasurable velocities. Second, by utilizing the prescribed performance control, the prescribed tracking control performance can be ensured, while the requirement for the initial error is removed via the preprocessing. At last, based on neural network approximation in combination with backstepping and Lyapunov synthesis, a robust adaptive neural control scheme is developed to handle the uncertainties and input dead-zone characteristics. Under the designed adaptive controller for marine surface vessels, all the signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB), and the prescribed transient and steady tracking control performance is guaranteed. Simulation studies are performed to demonstrate the effectiveness of the proposed method.

Event-Triggered Finite-Time Tracking Control of Unmanned Surface Vessel Using Neural Network Prescribed Performance

“…Various elegant control strategies and disturbance observers (DOs) have been presented for the USVs' motion control to make up the unmodeled dynamics of USVs and antidisturbances in working environments [8][9][10][11][12][13][14][15][16][17]. In [9], the path-following (PF) issue of USV was investigated under the actuator saturation and general disturbance uncertainty.…”

“…The feedforward control loop compensated for the external disturbance provided by the disturbance observer, promoting the anti-USV's interference efficiency. A robust adaptive neural control method was presented in [14] using the neural network estimation, combined with backstepping and Lyapunov-based approaches.…”

Robust neural network‐based tracking control for unmanned surface vessels under deferred asymmetric constraints

“…Actually, some accidents may occur to the USV if the constraint conditions are violated, including straying off course, running against the obstacles, and equipment failure. At present, there are two popular solutions for state constraints, the one is the prescribed performance control, [5][6][7][8][9] and the other one is the barrier Lyapunov function (BLF) method. Compared with the prescribed performance control, BLF has many advantages.…”

Observer-based adaptive fuzzy prescribed performance control for intelligent ship autopilot

“…For navigation manoeuvring control design, the tracking error is only required to converge to a small residual set, while practical applications often require a certain specified performance. In Si and Dong (2017), the problem of the tracking control with predefined performance for marine surface vessels was solved. In Dai et al (2016), based on an error transformation function, the constrained tracking control of marine surface vessel was transformed into the stabilization of an unconstrained system.…”