A Time-Domain Numerical Simulation for Free Motion Responses of Two Ships Advancing in Head Waves

The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems within a time domain framework,the free water surface needs to simultaneously satisfy both the kinematic and dynamic boundary conditions of the free water surface.This provides conditions for adding artificial damping layers.Using the Runge−Kutta method to solve equations related to time.An upwind differential scheme is used in the present method to deal with the convection terms on the free surface to prevent waves upstream.Through the comparison with the available experimental data and other numerical methods,the present method is proved to have good mesh convergence,and satisfactory results can be obtained.The constant panel method is applied to calculate the hydrodynamic interaction responses of two parallel ships advancing in head waves.Numerical simulations are conducted on the effects of forward speed,different longitudinal and lateral distances on the motion response of two modified Wigley ships in head waves.Then further investigations are conducted on the effects of different ship types on the motion response.

Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

Multipoint Heave Motion Prediction Method for Ships Based on the PSO-TGCN Model

During ship operations,frequent heave movements can pose significant challenges to the overall safety of the ship and completion of cargo loading.The existing heave compensation systems suffer from issues such as dead zones and control system time lags,which necessitate the development of reasonable prediction models for ship heave movements.In this paper,a novel model based on a time graph convolutional neural network algorithm and particle swarm optimization algorithm(PSO-TGCN)is proposed for the first time to predict the multipoint heave movements of ships under different sea conditions.To enhance the dataset's suitability for training and reduce interference,various filter algorithms are employed to optimize the dataset.The training process utilizes simulated heave data under different sea conditions and measured heave data from multiple points.The results show that the PSO-TGCN model predicts the ship swaying motion in different sea states after 2 s with 84.7%accuracy,while predicting the swaying motion in three different positions.By performing a comparative study,it was also found that the present method achieves better performance that other popular methods.This model can provide technical support for intelligent ship control,improve the control accuracy of intelligent ships,and promote the development of intelligent ships.

Mathematical Modeling of Moored Ship Motion in Arbitrary Harbor utilizing the Porous Breakwater

The motion of the moored ship in the harbor is a classical hydrodynamics problem that still faces many challenges in naval operations,such as cargo transfer and ship pairings between a big transport ship and some small ships.A mathematical model is presented based on the Laplace equation utilizing the porous breakwater to investigate the moored ship motion in a partially absorbing/reflecting harbor.The motion of the moored ship is described with the hydrodynamic forces along the rotational motion(roll,pitch,and yaw)and translational motion(surge,sway,and heave).The efficiency of the numerical method is verified by comparing it with the analytical study of Yu and Chwang(1994)for the porous breakwater,and the moored ship motion is compared with the theoretical and experimental data obtained by Yoo(1998)and Takagi et al.(1993).Further,the current numerical scheme is implemented on the realistic Visakhapatnam Fishing port,India,in order to analyze the hydrodynamic forces on moored ship motion under resonance conditions.The model incorporates some essential strategies such as adding a porous breakwater and utilizing the wave absorber to reduce the port’s resonance.It has been observed that these tactics have a significant impact on the resonance inside the port for safe maritime navigation.Therefore,the current numerical model provides an efficient tool to reduce the resonance within the arbitrarily shaped ports for secure anchoring.

A Hybrid BPNN-GARF-SVR Prediction Model Based on EEMD for Ship Motion

Accurate prediction of shipmotion is very important for ensuringmarine safety,weapon control,and aircraft carrier landing,etc.Ship motion is a complex time-varying nonlinear process which is affected by many factors.Time series analysis method and many machine learning methods such as neural networks,support vector machines regression(SVR)have been widely used in ship motion predictions.However,these single models have certain limitations,so this paper adopts amulti-model prediction method.First,ensemble empirical mode decomposition(EEMD)is used to remove noise in ship motion data.Then the randomforest(RF)prediction model optimized by genetic algorithm(GA),back propagation neural network(BPNN)prediction model and SVR prediction model are respectively established,and the final prediction results are obtained by results of three models.And the weights coefficients are determined by the correlation coefficients,reducing the risk of prediction and improving the reliability.The experimental results show that the proposed combined model EEMD-GARF-BPNN-SVR is superior to the single predictive model and more reliable.The mean absolute percentage error(MAPE)of the proposed model is 0.84%,but the results of the single models are greater than 1%.

Disturbance Observer Based Sliding Mode Controller Design for Heave Motion of Surface Effect Ships

In order to damp the heave motion of surface effect ships(SESs),a sliding mode controller with a disturbance observer was designed.At first,a disturbance observer was proposed to estimate the unknown time-varying disturbance acting on SESs due to waves.Then,based on the disturbance,a slide mode controller was designed to minimize the magnitude of SES's heave motion position.It was theoretically proved that the designed sliding mode controller with the disturbance observer could guarantee the stability of the closed-loop heave motion control system of SESs.Simulations on a Norwegian Navy's SES were carried out and the simulation results illustrated the effectiveness of the proposed controller with the disturbance observer.

Nonlinear Backstepping Ship Course Controller

A ship, as an object of course control, is characterized by a nonlinear function describing the static maneuvering characteristics. The backstepping method is one of the methods that can be used during the designing process of a nonlinear course controller for ships. The method has been used for the purpose of designing two configurations of nonlinear controllers, which were then used to control the ship course. One of the configurations took dynamic characteristic of a steering gear into account during the designing stage. The parameters of the obtained nonlinear control structures have been tuned to optimise the operation of the control system. The optimisation process has been performed by means of genetic algorithms. The quality of operation of the designed control algorithms has been checked in simulation tests performed on the mathematical model of a tanker. The results of simulation experiments have been compared with the performance of the system containing a conventional proportional-derivative （PD） controller.

CAN-based Synchronized Motion Control for Induction Motors

A control area network （CAN） based multi-motor synchronized motion control system with an advanced synchronized control strategy is proposed. The strategy is to incorporate the adjacent cross-coupling control strategy into the sliding mode control architecture. As illustrated by the four-induction-motor-based experimental results, the multi-motor synchronized motion control system, via the CAN bus, has been successfully implemented. With the employment of the advanced synchronized motion control strategy, the synchronization performance can be significantly improved.

Domain Decomposition and Matching for Time-Domain Analysis of Motions of Ships Advancing in Head Sea

A domain decomposition and matching method in the time-domain is outlined for simulating the motions of ships advancing in waves. The flow field is decomposed into inner and outer domains by an imaginary control surface, and the Rankine source method is applied to the inner domain while the transient Green function method is used in the outer domain. Two initial boundary value problems are matched on the control surface. The corresponding numerical codes are developed, and the added masses, wave exciting forces and ship motions advancing in head sea for Series 60 ship and S175 containership, are presented and verified. A good agreement has been obtained when the numerical results are compared with the experimental data and other references. It shows that the present method is more efficient because of the panel discretization only in the inner domain during the numerical calculation, and good numerical stability is proved to avoid divergence problem regarding ships with flare.

Adaptive robust dissipative designs on straight path control for underactuated ships

An adaptive robust control algorithm for ship straight path control system in the presence of both modeling uncertainties and the bounded disturbances is proposed. Motivated by the backstepping approach, the algorithm is developed by using the dissipation theory, such that the resulting dosed-loop system is both strictly dissipative and asymptotically adaptively stable for all admissible uncertainties. Also, it is able to steer an underactuated ship along a prescribed straight path with ultimate bounds under external disturbances induced by wave, wind and ocean current. When there are no disturbances, the straight path control can be implemented in a locally asymptotically stable manner. Simulation results on an ocean-going training ship ‘YULONG＇ are presented to validate the effectiveness of the algorithm.

Path following control of underactuated ships based on nonswitch analytic model predictive control

A path following controller is developed for underactuated ships with only surge force and yaw moment available to follow a predefined path.The proposed controller is based on nonswitch analytic model predictive control.It is shown that the optimal control law for a nonlinear path following system with ill-defined relative degree is continuous and nonsingular.The problem of ill-defined relative degree is solved.The path-following ability of the nonlinear system is guaranteed.Numerical simulations are provided to demonstrate the effectiveness of the proposed control law.

Effects of Deck Motion and Ship Airwake on Ski-Jump Takeoff Performance of Carrier-Based Aircraft

We first analyzed the force and motion of naval aircraft during launching process.Further,we investigated the ship deck with the form of a ramp and established deck motion model and ship airwake model.Finally,we conducted simulations at medium sea.Results showed that the effects of deck motion on takeoff varied with initial phases,and airwake could help reducing aircraft′s sinkage.We also found that the deck motion played a major role in the effects caused by the interaction of deck motion and ship airwake.

Sloshing-Coupled Ship Motion Algorithm for Estimation of Slosh-Induced Pressures

The effect of coupling between sloshing and ship motions in the evaluation of slosh-induced interior pressures is studied. The coupling between sloshing loads and ship motions is modelled through a hybrid algorithm which combines a potential flow solution based on transient Green function for the external ship hydrodynamics with a viscous flow solution based on a multiphase interface capturing volume of fluid(VOF) technique for the interior sloshing motion. The coupled algorithm accounts for full nonlinear slosh forces while the external forces on the hull are determined through a blended scheme of linear radiationdiffraction with nonlinear Froude-Krylov and restoring forces. Consideration of this level of nonlinearities in ship motions is found to have non-negligible effects on the slosh-coupled responses and slosh-induced loads. A scheme is devised to evaluate the statistical measure of the pressures through long-duration simulation studies in extreme irregular waves. It is found that coupling significantly influences the tank interior pressures, and the differences in the pressures between coupled and uncoupled cases can be as much as 100% or more. To determine the RAO over the frequency range needed for the simulation studies in irregular waves, two alternative schemes are proposed, both of which require far less computational time compared to the conventional method of finding RAO at each frequency, and the merits of these are discussed.

Improved filtered-ε adaptive inverse control and its application on nonlinear ship maneuvering

The drawbacks of common nonlinear Filtered-ε adaptive inverse control （AIC） method, such as the unreliability due to the change of delay time and the faultiness existing in its disturbance control loop, are discussed. Based on it, the diagram of AIC is amended to accommodate with the characteristic of nonlinear object with time delay. The corresponding Filtered-ε adaptive algorithm based on RTRL is presented to identify the parameters and design the controller. The simulation results on a nonlinear ship model of ＂The R.O.V Zeefakker＂ show that compared with the previous scheme and adaptive PID control, the improved method not only keeps the same dynamic response performance, but also owns higher robustness and disturbance rejection ability, and it is suitable for the control of nonlinear objects which have higher requirement to the maneuverability under complex disturbance environment.

Wave Loads and Motions of Ships and Offshore Structures

The special issue on wave loads and motions of ships and offshore structures is the outcome of a workshop on the same topic that was organised in Harbin Engineering University in November 2017 with the objective of bringing together recent work done on the subject area and providing a forum for discussing these results.

Real-Time Iterative Compensation Framework for Precision Mechatronic Motion Control Systems

With regard to precision/ultra-precision motion systems,it is important to achieve excellent tracking performance for various trajectory tracking tasks even under uncertain external disturbances.In this paper,to overcome the limitation of robustness to trajectory variations and external disturbances in offline feedforward compensation strategies such as iterative learning control(ILC),a novel real-time iterative compensation(RIC)control framework is proposed for precision motion systems without changing the inner closed-loop controller.Specifically,the RIC method can be divided into two parts,i.e.,accurate model prediction and real-time iterative compensation.An accurate prediction model considering lumped disturbances is firstly established to predict tracking errors at future sampling times.In light of predicted errors,a feedforward compensation term is developed to modify the following reference trajectory by real-time iterative calculation.Both the prediction and compen-sation processes are finished in a real-time motion control sampling period.The stability and convergence of the entire control system after real-time iterative compensation is analyzed for different conditions.Various simulation results consistently demonstrate that the proposed RIC framework possesses satisfactory dynamic regulation capability,which contributes to high tracking accuracy comparable to ILC or even better and strong robustness.

A learning-based flexible autonomous motion control method for UAV in dynamic unknown environments

This paper presents a deep reinforcement learning(DRL)-based motion control method to provide unmanned aerial vehicles(UAVs)with additional flexibility while flying across dynamic unknown environments autonomously.This method is applicable in both military and civilian fields such as penetration and rescue.The autonomous motion control problem is addressed through motion planning,action interpretation,trajectory tracking,and vehicle movement within the DRL framework.Novel DRL algorithms are presented by combining two difference-amplifying approaches with traditional DRL methods and are used for solving the motion planning problem.An improved Lyapunov guidance vector field(LGVF)method is used to handle the trajectory-tracking problem and provide guidance control commands for the UAV.In contrast to conventional motion-control approaches,the proposed methods directly map the sensorbased detections and measurements into control signals for the inner loop of the UAV,i.e.,an end-to-end control.The training experiment results show that the novel DRL algorithms provide more than a 20%performance improvement over the state-ofthe-art DRL algorithms.The testing experiment results demonstrate that the controller based on the novel DRL and LGVF,which is only trained once in a static environment,enables the UAV to fly autonomously in various dynamic unknown environments.Thus,the proposed technique provides strong flexibility for the controller.

Robust Position Observer for Sensorless Direct Voltage Control of Stand-Alone Ship Shaft Brushless Doubly-Fed Induction Generators

The aim of this paper is to investigate an adaptive sensorless direct voltage control(DVC)strategy for the stand-alone ship shaft brushless doubly-fed induction generators(BDFIGs).The proposed new rotor position observer using the space vector flux relations of BDFIG may achieve the desired voltage control of the power winding(PW)in terms of magnitude and frequency,without any speed/position sensors.The proposed algorithm does not require any additional observers for obtaining the generator speed.The proposed technique can directly achieve the desired DVC based on the estimated rotor position,which may reduce the overall system cost.The stability analysis of the proposed observer is investigated and confirmed with the concept of quadratic Lyapunov function and using the multi-model representation.In addition,the sensitivity analysis of the presented method is confirmed under different issues of parameter uncertainties.Comprehensive results from both simulation and experiments are realized with a prototype wound-rotor BDFIG,which demonstrate the capability and efficacy of the proposed sensorless DVC strategy with good transient behavior under different operating conditions.Furthermore,the analysis confirms the robustness of the proposed observer via the machine parameter changes.