Objective Aiming at the the issue of obstacle avoidance and path following for underactuated ships with model uncertainties and external environmental disturbances, an obstacle avoidance algorithm based on improved artificial potential field and a path following control method based on finite-time sliding mode control are proposed.
Method Firstly, based on the principles of the artificial potential field method, the traditional repulsive force function of the artificial potential field is modified to overcome the issues of unreachable targets problem. Considering the relative velocity relationship between ships and obstacles in dynamic environments, relative velocity repulsion is introduced to enhance obstacle avoidance safety, and simulated annealing algorithm is further optimized to addressing the local minima problem. In the control design of path following under obstacle avoidance algorithm, command filtering technology and radial basis function neural network minimum learning parameter method (RBFNNMLP) are used to reduce the computational complexity of the system, and a path following controller was designed by combining finite-time sliding mode control. Lyapunov stability analysis proves the system's stability within a finite time.
Results Simulation comparison results show that under sea wave disturbances, the position error of the designed control algorithm converges in about 6 seconds, with the error converging to zero. Moreover, the ship can effectively avoid obstacles and continue to perform path following tasks when encountering unreachable targets and local minima, verifying the effectiveness and robustness of the proposed control algorithm.
Conclusion The proposed control algorithm can serve as a reference for further optimization and practical application of obstacle avoidance and path following for underactuated ships.
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