Abstract

This paper presents an adaptive fuzzy backstepping control method that incorporates the dynamic equilibrium state (DES) theory to carry out path tracking for underactuated ships in presence of parameter variations and external disturbances induced by wind, wave and current. First, the optimal DES reference trajectories are designed for the sway displacement and the yaw angle. Then, by combining the DES theory with backstepping technology and using fuzzy logic systems to approximate unknown nonlinear functions in the system, a robust adaptive fuzzy controller is designed to track the prescribed trajectories. Theoretical analysis and simulation results show that the proposed method performs path tracking of underactuated ships with high precision, eliminates the influence of the uncertainties, and guarantees global stability and robustness of the system.

Highlights

  • In recent years, the design of the trajectory tracking and the path following controllers for underactuated ships is one of the hot issues in many offshore applications.[1]

  • The present paper firstly reports about the ship tracking control based on the dynamic equilibrium state (DES) theory

  • An adaptive fuzzy backstepping control approach based on the DES theory is proposed for path tracking of the underactuated ships

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Summary

Introduction

The design of the trajectory tracking and the path following controllers for underactuated ships is one of the hot issues in many offshore applications.[1]. Wang et al [8-10] addressed a kind of nonlinear tracking design methods based on the DES theory, which are established on the concept of the DES asymptotic stability. Adaptive fuzzy control has been an effective control method for the uncertain nonlinear systems.[12,13,14,15,16,17]. This paper combines the DES tracking approach with adaptive fuzzy backstepping control method to obtain the desired path tracking of underactuated ships in presence of parameters variations and external disturbances caused by wind, wave and current.

The DES theory
Problem statement
Backstepping control based on the DES
Apative fuzzy control
Simulation results
Conclusions
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