Path following of under-actuated ships based on backstepping and predictive control method

Area of Science:

• Marine engineering
• Control systems theory
• Robotics

Background:

• Under-actuated ships face challenges in path following due to sideslip angles from disturbances.
• Accurate state estimation is crucial for effective control of ship heading and motion.

Purpose of the Study:

• To develop an advanced control strategy for under-actuated ship path following.
• To enhance heading control accuracy and optimize rudder movements.
• To mitigate the impact of external disturbances and internal uncertainties on ship navigation.

Main Methods:

• A nonlinear observer within a backstepping approach converts path following to heading control.
• Model Predictive Control (MPC) is employed for heading control and rudder optimization.
• Linear Extended State Observer (LESO) technology estimates unmeasured states like yaw rate and disturbances.
• An inverse tangent function is used for smooth reference heading angle switching to minimize rudder amplitude.

Main Results:

• The integrated control system effectively manages sideslip angles and improves path-following accuracy.
• LESO enhances the accuracy of the MPC controller by estimating critical states and disturbances.
• The inverse tangent function successfully reduces rudder amplitude during waypoint transitions.
• Simulation experiments validate the robustness and reliability of the proposed control design.

Conclusions:

• The proposed backstepping approach combined with MPC and LESO offers a robust solution for under-actuated ship path following.
• The method effectively addresses challenges posed by external disturbances and internal uncertainties.
• The strategy optimizes rudder control, leading to more efficient and stable ship navigation.