To address the issue of obstacle avoidance and path following for underactuated ships with model uncertainties and external environmental disturbances, an obstacle avoidance algorithm based on an improved artificial potential field and a path following control method based on finite-time sliding mode control are proposed.

First, 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 unreachable target problem. Considering the relative velocity 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 address the local minima problem. In the path following control design under the obstacle avoidance algorithm, command filtering technology and radial basis function neural network minimum learning parameter (RBFNNMLP) method are used to reduce the computational complexity of the system. A path following controller is designed by combining finite-time sliding mode control. Lyapunov stability analysis proves the system's stability within a finite time.

Simulation comparison results show that under sea wave disturbances, the position error of the designed control algorithm converges within approximately 6 seconds, reaching zero. Moreover, the ship can effectively avoid obstacles and continue to perform path following tasks when encountering unreachable targets and local minima, thereby verifying the effectiveness and robustness of the proposed control algorithm.

The proposed control algorithm provides a reference for further optimization and practical application of obstacle avoidance and path following in underactuated ships.

Existing brittle source identification methods have such problems as their single-perspective approach, disregard for the local and global characteristics of nodes, and insufficient consideration of the loads carried by nodes.

The method proposed herein identifies the inherent brittleness of the ship power system as the root cause of interruption and chain collapse. To establish a brittleness index, the method first considers node degree, eigenvector centrality, node cohesiveness, closeness centrality and brittle electrical betweenness from a brittleness perspective based on complex network theory. The combinatorial intuitionistic fuzzy analytic hierarchy process (IFAHP）and entropy weight method (EWM) with the Nash equilibrium as the coordination objective. The five indexes are then combined through comprehensive assignment to obtain a comprehensive brittleness index. Finally, the proposed brittle source identification method is validated using a typical four-station annular ship grid.

The method identifies four levels of brittle sources based on the network efficiency of different brittleness indexes, and the results demonstrate its ability to identify brittle sources more comprehensively and reasonably.

The results of this study can provide effective guidance for the prevention and control of inter-locking faults in ship power networks.

An adaptive finite-time filtered backstepping sliding mode controller is designed to solve the rudder roll stabilization control problem of underactuated ships in unknown wave disturbance conditions.

First, in order to avoid differential operation for the virtual control law, a first-order filter is introduced to address the problem of differential explosion that affects the backstepping approach. By combining the filtered backstepping technique with adaptive sliding mode control, finite-time convergent control laws for rudder roll stabilization are designed on the basis of the finite-time control theory. Finally, the stability of the heading control subsystem and roll damping subsystem is proven by the Lyapunov stability theory.

The simulation results indicate that the designed controller can realize course tracking and roll damping simultaneously in finite time under different wave disturbance conditions. Compared with backstepping sliding mode control, the designed controller can improve the course-keeping control performance, and the roll reduction rate is increased by 5%.

The proposed method can provide useful references for the rudder roll stabilization control problem of underactuated ships.

In order to solve the problem of an underactuated ship responding slowly to heading changes during rudder roll stabilization (RRS) caused by fixed weight values in model predictive control (MPC), a RRS control method based on the finite time extended states observer (FTESO), fuzzy rules and robust predictive control is proposed.

A fixed speed linear underactuated ship model is established for controller design. The FTESO is used to estimate the ship's motion states and external disturbances. By analyzing the conditions of the ship's course-keeping and heading change, the objective function weights under the two conditions and the fuzzy rules between the states and weights are designed respectively. Robust predictive control is used to solve the multi-objective cooperative control problem with constraints. The closed-loop stability of the proposed control method is then proven theoretically.

According to a numerical simulation of a multi-purpose naval vessel, the proposed control method is compared with a disturbance compensation MPC and disturbance observer enhanced MPC, and is shown to have a higher roll stabilization rate by 5.74% and 0.898 3%, respectively. The response time of the proposed method for a 30° heading change is also reduced by 1.8 s and 7.3 s respectively.

The effectiveness of the proposed method in underactuated ship rolling reduction is proven.

To improve the performance of course tracking and reduce the course errors of an underactuated surface ship, a heading control method based on a finite-time extended state observer (FTESO) and sliding mode control algorithm is studied.

A pre-filter is proposed to reduce the influence of the large rate of speed change when steering. The time-varying sideslip angle is estimated by FTESO, and course error is amended by the estimated sideslip angle in a timely manner. To simplify the design of the controller, external disturbance and internal uncertainty in the yaw direction are estimated by the observer simultaneously, and compensated for in the controller design. Considering input saturation, a sliding mode control law is designed by combining FTESO and a sliding mode surface with an integral term. The stability of the control system is proven by the Lyapunov theory.

The simulation results show that the proposed controller reduces course tracking error and makes it converge to zero in a shorter time.

The results of this study can provide references for the course tracking control design of surface ships.