This paper proposes a method for the online parameter identification of nonlinear ship motion systems. First, the motion system of a ship is nonlinear, and in the course of sailing, the motion parameters of the ship will change with the change of the motion state of the ship and the sailing environment. To achieve the effect of real-time identification, we adopted an online receding horizon identification method. Second, identification parameters are the essential elements in the navigation control of intelligent merchant ships, and high-precision identification results can achieve better control effects. Therefore, we used an unscented Kalman filter (UKF) that has simpler mathematical structure and higher feedback efficiency than other identification algorithms listed in this paper, such as extended the Kalman filter, Kalman filtering and Ordinary Least Squares, as the identification scheme design algorithm, which is applied to ship motion system identification. Then, to solve the problem of significant identification errors in complex environments, we design a navigation identification framework combining a UKF and rolling wavelet denoising to realize the effect of the online identification of ships. Finally, a Korea Research Institute of Ships and Ocean Engineering (KRISO) Container Ship (KCS) was used for a self-navigation model experiment and data collection. The collected data and identification data were compared and analyzed. By comparing different identification algorithms before and after denoising, it was verified that the UKF algorithm proposed in this paper is superior relative to other traditional algorithms in identifying ship motion systems.

In recent years, ship motion control has been used in unmanned merchant ships. It is a key issue in the sailing performance and navigation cost of unmanned vessels. The merchant ship trajectory and attitude are always generated from the response mechanism for ship motion which uses one rudder and one propeller as the actuator. Therefore, it is a typical underactuated ship. However, there is not a specialized control test platform for unmanned merchant ships, in particular container ships. A precise merchant ship motion control platform is crucial; its computing power and motion attitude monitoring are difficult to solve by ship-borne computers. To solve this problem, a new free-running ship motion control platform is proposed, which realizes ship attitude monitoring and various motion control experiments. The proposed platform is novel as it embeds all the control elements in the ship motion model, which successfully solves the precise control of the ship motion control experiment with linear or nonlinear dynamics. In this paper, the design scheme of the ship motion control platform is first presented. Then, the operating principle of the platform is shown, and the adaptive model of the ship plane motion is selected. A series of free-running model experiments and simulations are conducted to test performance of the new platform. To this end, the proposed platform can meet the requirements.

Trajectory tracking control of unmanned surface vessels (USVs) has become a popular topic. Regarding the problem of ship collision avoidance encountered in trajectory tracking, more attention needs to be paid to the algorithm application, namely the characteristics of flexibility and accessibility. Thus, a fusion framework of field theoretical planning and a model predictive control (MPC) algorithm is proposed in this paper to obtain a realizable collision-free tracking trajectory, where the trajectory smoothness and collision avoidance constraints under a complex environment need to be considered. Through the designed fast matching (FM) method based on the electric field model, the algorithm gains the direction trend of collision avoidance planning and then combines it with a flexible distance to reconstruct the architecture of the MPC and constraint system, generating the optimal trajectory tracking controller. The new algorithm was tested and validated for several situations, and it can potentially be developed to advance collision-free trajectory tracking navigation in multivessel situations.

To ensure navigation safety, unmanned surface vehicles (USVs) need to have autonomous collision avoidance capability. A large number of studies on ship collision avoidance are available, and most of these papers assume that the target ships keep straight or follows the International Regulations for Preventing Collisions at Sea (COLREGS). However, in the actual navigation process, the target ship may temporarily turn. Based on the above reasons, this paper proposes a multi-ship collision avoidance decision method for USVs based on the improved velocity obstacle algorithm. In the basic dynamic ship domain model, a collision risk model is constructed to improve the accuracy of the risk assessment between the USV and target ships. The velocity obstacle algorithm is combined with the dynamic ship domain, and the collision avoidance timing and method are judged according to the collision risk. The simulation results show that the decision method can handle the situation that the target ship temporarily turns and has an emergency collision avoidance capability. Compared with the traditional VO algorithm, the collision avoidance time of the method is shorter, and the number of course changes is less.

With the increasing construction of offshore engineering, there is an increasing demand for the floating transportation of offshore-unpowered facilities. Current offshore towing floating transportation is manipulated uniformly through manual command, which depends on the experience to control and coordinate. There will be delay in the manipulation time, and the manual factor has great influence. The intelligent control method is introduced to establish the cooperative control strategy, and the design of a cooperative controller could increases the adaptive regulation capacity of the system, which applies the coupling correlation of systems to realize the automatic regulation for the direction and towing force. The rapid, intelligent, and stable turning of system could be accomplished. Finally, through simulation and hardware experimental testing analysis, the track and direction changes under different sea conditions are compared with the control quality, and the performance of the cooperative strategy is analyzed, acquiring excellent control effect, which is of guiding significance for the intelligent control practice of the system.