This paper surveys the recent advances in marine mechatronic systems from a control perspective. The survey is by no means exhaustive, but introduces some notable results in marine control area. New developments in terms of control system designs for surface vessels, underwater robotic vehicles, profiling floats, underwater gliders, wave energy converters, and offshore wind turbines are briefly reviewed. In addition, a few avenues for future research are identified.

Advanced Control in Marine Mechatronic Systems: A Survey

This paper studies the model predictive stabilization problem of underactuated autonomous underwater vehicles (AUVs) with control input constraints, where the full dynamic and kinematic model including Coriolis and centripetal matrix, the hydrodynamic added mass, and damping is utilized, and a four-control-input configuration is considered. A novel model predictive control algorithm is proposed based on the homogeneity of system model and an existing time-varying control law. Theoretical results on ensuring algorithm feasibility and closed-loop stability are provided. It is shown that if the terminal set level and the cost weights are designed appropriately, the developed algorithm is iteratively feasible and the closed-loop system is asymptotically stabilized at the equilibrium point. Comparison studies verify the effectiveness of the developed results.

Model Predictive Stabilization of Constrained Underactuated Autonomous Underwater Vehicles With Guaranteed Feasibility and Stability

This paper proposes a novel fault tolerant control strategy for dynamic positioning of unmanned marine vehicles using the quantized feedback sliding mode control technique. Due to the complex ocean environment, the unmanned marine vehicles are modeled as the Takagi-Sugeno fuzzy system with unknown membership functions. When the membership functions are not available, traditional sliding mode control technique becomes infeasible. To tackle this difficulty, a novel quantized sliding mode control strategy based on switching mechanism is designed to compensate for thruster faults effects. In addition, the phenomenon of time-varying delay leads to conservativeness of the existing dynamic quantization parameter adjustment strategy. Then a larger quantization parameter adjustment range, by taking time delay and fault factor into account, is given. Combining the novel sliding mode controller design and the improved dynamic quantization parameter adjustment strategy, the dynamic positioning of unmanned marine vehicles with thruster faults and quantization can be maintained. Finally, the effectiveness of the proposed method is verified through the simulation comparison results.

Fault Tolerant Control for Dynamic Positioning of Unmanned Marine Vehicles Based on T-S Fuzzy Model With Unknown Membership Functions

Nowadays, optimization of ship energy efficiency attracts increasing attention in order to meet the requirement for energy conservation and emission reduction. Ship operation energy efficiency is significantly influenced by environmental factors such as wind speed and direction, water speed and depth. Owing to inherent time-variety and uncertainty associated with these various factors, it is very difficult to determine optimal sailing speeds accurately for different legs of the whole route using traditional static optimization methods, especially when the weather conditions change frequently over the length of a ship route. Therefore, in this paper, a novel dynamic optimization method adopting the model predictive control (MPC) strategy is proposed to optimize ship energy efficiency accounting for these time-varying environmental factors. Firstly, the dynamic optimization model of ship energy efficiency considering time-varying environmental factors and the nonlinear system model of ship energy efficiency are established. On this basis, the control algorithm and controller for the dynamic optimization of ship energy efficiency (DOSEE) are designed. Finally, a case study is carried out to demonstrate the validity of this optimization method. The results indicate that the optimal sailing speeds at different time steps could be determined through the dynamic optimization method. This method can improve ship energy efficiency and reduce CO 2 emissions effectively.

Dynamic optimization of ship energy efficiency considering time-varying environmental factors

Autonomous Surface Vessels (ASVs) have been developed for more than 20 years. Many ASV projects have been successfully realized, and as many are still under development. In literature there is a lack of research on the different applications and suitable environments for the deployment of ASV.

Survey on Autonomous Surface Vessels: Part II - Categorization of 60 Prototypes and Future Applications.

At present, with the development of waterborne transport vehicles, research on ship faces a new round of challenges in terms of intelligence and autonomy. The concept of maritime autonomous surface ships (MASS) has been put forward by the International Maritime Organization in 2017, in which MASS become the new focus of the waterborne transportation industry. This paper elaborates on the state-of-the-art research on motion control of MASS. Firstly, the characteristics and current research status of unmanned surface vessels in MASS and conventional ships are summarized, and the system composition of MASS is analyzed. In order to better realize the self-adaptability of the MASS motion control, the theory and algorithm of ship motion control-related systems are emphatically analyzed under the condition of classifying ship motion control. Especially, the application of intelligent algorithms in the ship control field is summarized and analyzed. Finally, this paper summarizes the challenges faced by MASS in the model establishment, motion control algorithms, and real ship experiments, and proposes the composition of MASS motion control system based on variable autonomous control strategy. Future researches on the accuracy and diversity of developments and applications to MASS motion control are suggested.

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State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

The invention provides a model ship based autonomous navigation control simulation system and method of an under-actuated unmanned ship The whole system is arranged on a model ship, and the model ship is arranged in a simulated navigation channel; the system comprises an environment sensing sub system, a path programming sub system and a motion control sub system; the environment sensing sub system collects the navigation state of the model ship and simulates environment factor information; according to the navigation state of the model ship and the simulated environment factor information, the path programming sub system carries out navigation programming to obtain the tracking route, the set speed and the set course; and the motion control system combines a course tracking model, a path tracking model, the route deviation, the course deviation and the speed deviation to calculate the rudder angle and propeller rotating speed instruction needed in next navigation of the model ship and control a steering engine and a propeller According to the invention, simulation experiments are carried out on the model ship, an instance is provided for operation and control experiments of large ships, important guarantee is provided for safe navigation of large ships in inland rivers, and the system reduces the difficult and cost of experiments of the large ships

Model ship based autonomous navigation control simulation system and method of under-actuated unmanned ship

An autonomous vessel can improve the intelligence, efficiency and economy of shipping logistics. To realize autonomous navigation control of underactuated vessels (USVs), this paper presents a controller that can make USV track a reference trajectory with only 2 inputs, i.e., surge and yaw. A nonlinear state-space model with 2 inputs considering environmental disturbances induced by wind, current and waves for a 3 degree of freedom (DOF) surface vessel is considered. Based on this model, a trajectory tracking controller using Nonlinear Model Predictive Control (NMPC) is designed. System constraints on inputs, input increment and output are incorporated in the NMPC framework. Simulation results show that the controller can track an ellipse trajectory well and that the tracking errors are within acceptable ranges, while system constraints are satisfied.

Trajectory Tracking Control for Underactuated Surface Vessels Based on Nonlinear Model Predictive Control

The invention provides an under-actuated unmanned ship formation structure based on model ships. The structure comprises the multiple model ships that are arranged in a simulated navigation channel, and the simulated navigation channel includes simulated environment factors; one model ship serves as a master ship, and other model ships serve as slavery ships; the master ship is provided with a master ship simulation control system, the slavery ships are provided with a slavery ship simulation control system, the shore base is provided with a positioning information monitoring system, and the master ship simulation control system, the slavery ship simulation control system and the positioning information monitoring system are connected via network; and the positioning information monitoring system comprises a shore-based camera and a computer, the shore-based camera is used to capture marker lamps on the model ships and thus carry out image identification positioning on all the model ships, and the computer is used to identify and process images collected by the shore-based camera and obtain positioning information of the master and slavery ships. According to the invention, the difficulty and cost of large ship formation experiments are reduced, an instance is provided for operation and control of the large ship formation, and important guarantee is provided for tasks of safe ship formation navigation.

Under-actuated unmanned ship formation structure based on model ships

Intelligent motion control is one of the key technologies of ships. This paper studies the application of Adaptive Mutation Beetle Particle Swarm (AMBPS)-PID algorithm in ship motion control. Firstly, the ship MMG model is established. Then the BAS algorithm is introduced, and AMBPS algorithm is improved and designed on this basis. Secondly, ship heading and path following controllers are designed according to the algorithm, and rudder turning rate constraint is introduced to limit the rudder angle. Thirdly, through the test function effect analysis of AMBPS and other similar algorithms, the improved effect of this algorithm is verified. Finally, from manual tuning PID parameters to off-line and on-line optimizing parameters based on AMBPS algorithm, the optimal control parameters are obtained step by step, and the optimal heading and path following simulation results are achieved. Compared with the results of traditional PID, AMBPS-PID algorithm has a better adaptive control effect on ship motion control, reduces the error of manual tuning parameters and improves efficiency.

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Le Wang

Papers

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Model ship based autonomous navigation control simulation system and method of under-actuated unmanned ship

Trajectory Tracking Control for Underactuated Surface Vessels Based on Nonlinear Model Predictive Control

Under-actuated unmanned ship formation structure based on model ships

Ship Motion Control Based on AMBPS-PID Algorithm