Robust adaptive backstepping design for course-keeping control of ship with parameter uncertainty and input saturation

Control of an Unmanned Surface Vehicle With Uncertain Displacement and Drag

“…Skjetne et al used adaptive control to determine the added mass hydrodynamic coefficients while performing free-running maneuvering experiments in [36] to create a nonlinear maneuvering model suited to either tracking or dynamic positioning control. The methods behind backstepping and adaptive control were combined in [23], using a Nomoto-like steering model that neglected the coupling of yaw rate with sway velocity commonly found in USVs. A recent method of handling uncertain displacement and drag terms is presented in [4], where model predictive control is used to stabilize the vehicle's course under large mass variations upwards of 50%.…”

Output feedback adaptive control for autopilot design of an unmanned surface vehicle

“…Advent of sophisticated controllers for autopilot design contributes for the vehicle to carry out tasks with reduced manpower, adequate economy, sufficient reliability, and optimum performance [1], There has been a number of results in the recent decades focused on autopilot design. In [2], a fuzzy PID autopilot is proposed for surface vessels, In [3], a sliding mode con troller based on simple sliding surface is developed for ship autopilot In [4], a robust adaptive backstepping controller for autopilot control of ship with parameter uncertainty is reported. In [5], the adaptive fuzzy control and dynamic surface control method are combined to perform the tasks of autopilot for marine vehicles, In [6], a ship autopilot control system which consists of the bang-bang controller and the fuzzy neural controller is developed, In [7], a neural network (NN) based adaptive autopilot for marine applications is proposed.…”

“…Consider a state observer based nominal control law as follows (4) where kl > 0, k2 > 0, k3 > 0; R is the regulated output command signal; {f and f are the observer estimate of .1jJ and r-, which are given by where � = (f -1jJ, klo > 0 and k20 > O.…”

“…Theorem 1: Consider an unmanned surface vehicle with the dynamics (I), choose the control law (8) with the nominal feedback control component given by (4) and the adaptive feedback control component given by (9), the state observer (5), and the iterative update law (10). Then for bounded initial condition, there exist appropriate design parameters such that all error signals in the system are uniformly ultimately bounded.…”

Ship Steering Control Based on Quantum Neural Network

“…In addition, the controller parameters are required adjustments in varying conditions, which are time consuming and may not achieve accurate control performance. To solve the issues and obtain better performance, various advanced control strategies have been proposed for the steering control of the ship in recent years, such as adaptive steering control strategy [6][7][8], steering control strategy based on fuzzy logic algorithm [9,10], steering controller based on Backstepping controller design method [11][12][13], and adaptive backstepping method [14,15].…”