The structure of a counter-rotating turbine of an underwater vehicle is designed by adding the counter-rotating second-stage turbine disk to the conventional single-stage turbine. The available kinetic energy and the absorption power of the auxiliary system are calculated at different working conditions, and the results show that the power of the main engine and auxiliary system at the counter-rotating turbine system matches well with each other. The technology scheme of the counter-rotating turbine system is proposed, then the experimental simulation of the lubricating oil loop, fuel loop, and seawater loop is completed. The simulation results indicate that the hydraulic transmission system can satisfy the requirements for an underwater vehicle running at a steady sailing or variable working conditions.

Autonomous Underwater Vehicles (AUVs) are capable of conducting various underwater missions and marine tasks over long periods of time. In this study, a novel conflict-free motion-planning framework is introduced. This framework enhances AUV mission performance by completing the maximum number of highest priority tasks in a limited time through a large-scale waypoint cluttered operating field and ensuring safe deployment during the mission. The proposed combinatorial route-path-planner model takes advantage of the Biogeography- Based Optimization (BBO) algorithm to satisfy the objectives of both higher- and lower-level motion planners and guarantee the maximization of mission productivity for a single vehicle operation. The performance of the model is investigated under different scenarios, including cost constraints in time-varying operating fields. To demonstrate the reliability of the proposed model, the performance of each motion planner is separately assessed and statistical analysis is conducted to evaluate the total performance of the entire model. The simulation results indicate the stability of the proposed model and the feasibility of its application to real-time experiments.

In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal; the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body’s minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.

This paper proposed a new concept of an adaptable multi-legged skid design for retro-fitting to a remotely-operated vehicle (ROV) during high tidal current underwater pipeline inspection. The sole reliance on propeller-driven propulsion for ROV is replaced with a proposed low cost biomimetic solution in the form of an attachable hexapod walking skid. The advantage of this adaptable walking skid is the high stability in positioning and endurances to strong current on the seabed environment. The computer simulation flow studies using Solidworks Flow Simulation shown that the skid attachment in different compensation postures caused at least four times increase in overall drag, and negative lift forces on the seabed ROV to achieve a better maneuvering and station keeping under the high current condition (from 0.5 m/s to 5.0 m/s). A graphical user interface is designed to interact with the user during robot-in-the-loop testing and kinematics simulation in the pool.

Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model’s collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.

A pneumatic launcher is theoretically investigated to study its natural transverse vibration in water. Considering the mass effect of the sealing cover, the launcher is simplified as a uniform cantilever beam with a top point mass. By introducing the boundary and continuity conditions into the motion equation, the natural frequency equation and the mode shape function are derived. An iterative calculation method for added mass is also presented using the velocity potential function to account for the mass effect of the fluid on the launcher. The first 2 order natural frequencies and mode shapes are discussed in external flow fields and both external and internal flow fields. The results show good agreement with both natural frequencies and mode shapes between the theoretical analysis and the FEM studies. Also, the added mass is found to decrease with the increase of the mode shape orders of the launcher. And because of the larger added mass in both the external and internal flow fields than that in only the external flow field, the corresponding natural frequencies of the former are relatively smaller.

This article discusses the dynamic state analysis of underwater towed-cable when tow-ship changes its speed in a direction making parabolic profile path. A three-dimensional model of underwater towed system is studied. The established governing equations for the system have been solved using the central implicit finite-difference method. The obtained difference non-linear coupled equations are solved by Newton’s method and satisfactory results were achieved. The solution of this problem has practical importance in the estimation of dynamic loading and motion, and hence it is directly applicable to the enhancement of safety and the effectiveness of the offshore activities.

For the purpose of identifying the stern of the SWATH (Small Waterplane Area Twin Hull) availably and perfecting the detection technique of the SWATH ship’s performance, this paper presents a novel bidirectional image registration strategy and mosaicing technique based on the scale invariant feature transform (SIFT) algorithm. The proposed method can help us observe the stern with a great visual angle for analyzing the performance of the control fins of the SWATH. SIFT is one of the most effective local features of the scale, rotation and illumination invariant. However, there are a few false match rates in this algorithm. In terms of underwater machine vision, only by acquiring an accurate match rate can we find an underwater robot rapidly and identify the location of the object. Therefore, firstly, the selection of the match ratio principle is put forward in this paper; secondly, some advantages of the bidirectional registration algorithm are concluded by analyzing the characteristics of the unidirectional matching method. Finally, an automatic underwater image splicing method is proposed on the basis of fixed dimension, and then the edge of the image’s overlapping section is merged by the principal components analysis algorithm. The experimental results achieve a better registration and smooth mosaicing effect, demonstrating that the proposed method is effective.

On March 26, 2010 an underwater explosion (UWE) led to the sinking of the ROKS Cheonan. The official Multinational Civilian-Military Joint Investigation Group (MCMJIG) report concluded that the cause of the underwater explosion was a 250 kg net explosive weight (NEW) detonation at a depth of 6?9 m from a DPRK “CHT-02D” torpedo. Kim and Gitterman (2012a) determined the NEW and seismic magnitude as 136 kg at a depth of approximately 8m and 2.04, respectively using basic hydrodynamics based on theoretical and experimental methods as well as spectral analysis and seismic methods. The purpose of this study was to clarify the cause of the UWE via more detailed methods using bubble dynamics and simulation of propellers as well as forensic seismology. Regarding the observed bubble pulse period of 0.990 s, 0.976 s and 1.030 s were found in case of a 136 NEW at a detonation depth of 8 m using the boundary element method (BEM) and 3D bubble shape simulations derived for a 136 kg NEW detonation at a depth of 8 m approximately 5 m portside from the hull centerline. Here we show through analytical equations, models and 3D bubble shape simulations that the most probable cause of this underwater explosion was a 136 kg NEW detonation at a depth of 8m attributable to a ROK littoral “land control” mine (LCM).

In order to analyze the spatial maneuverability of the remotely operated underwater vehicle (ROV), the 6-DOF motion mathematic model of the ROV was founded. Hydrodynamics were analyzed by using the Taylor series. The thrusters on the ROV were discussed. This paper considers three cases of motion simulation: vertical motion, rotational motion and Z-shape motion. A series of simulation experiments showed that the 6-DOF motion mathematic model was correct and reliable, and also fit with the scene simulation.

The double pulse sources method (DPS) is presented for linear track estimation in this work. In the field of noise identification of underwater moving target, the Doppler will distort the frequency and amplitude of the radiated noise. To eliminate this, the track estimation is necessary. In the DPS method, the bearings of two sinusoidal pulse sources installed in the moving target are estimated through baseline positioning method in the first step. Meanwhile, the emitted and recorded time of each pulse are also acquired. Then the linear track parameters will be achieved based on the geometry pattern with the help of double sources spacing. The simulated results confirm that the DPS improves the performance of the previously presented double source spacing method. The simulated experiments were carried out using a moving battery car to further evaluate its performance. When the target is 40~60m away, the experiment results show that biases of track azimuth and abeam distance of DPS are under 0.6o and 3.4m, respectively. And the average deviation of estimated velocity is around 0.25m/s.

To provide a simulation system platform for designing and debugging a small autonomous underwater vehicle’s (AUV) motion controller, a six-degree of freedom (6-DOF) dynamic model for AUV controlled by thruster and fins with appendages is examined. Based on the dynamic model, a simulation system for the AUV’s motion is established. The different kinds of typical motions are simulated to analyze the motion performance and the maneuverability of the AUV. In order to evaluate the influences of appendages on the motion performance of the AUV, simulations of the AUV with and without appendages are performed and compared. The results demonstrate the AUV has good maneuverability with and without appendages.

Underwater gliders are recent innovative types of autonomous underwater vehicles (AUVs) used in ocean exploration and observation. They adjust their buoyancy to dive and to return to the ocean surface. During the change of altitude, they use the hydrodynamic forces developed by their wings to move forward. Their flights are controlled by changing the position of their centers of gravity and their buoyancy to adjust their trim and heel angles. For better flight control, the understanding of the hydrodynamic behavior and the flight mechanics of the underwater glider is necessary. A 6-DOF motion simulator is coupled with an unsteady potential flow model for this purpose. In some specific cases, the numerical study demonstrates that an inappropriate stabilizer dimension can cause counter-steering behavior. The simulator can be used to improve the automatic flight control. It can also be used for the hydrodynamic design optimization of the devices.

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

The S/N of an underwater image is low and has a fuzzy edge. If using traditional methods to process it directly, the result is not satisfying. Though the traditional fuzzy C-means algorithm can sometimes divide the image into object and background, its time-consuming computation is often an obstacle. The mission of the vision system of an autonomous underwater vehicle (AUV) is to rapidly and exactly deal with the information about the object in a complex environment for the AUV to use the obtained result to execute the next task. So, by using the statistical characteristics of the gray image histogram, a fast and effective fuzzy C-means underwater image segmentation algorithm was presented. With the weighted histogram modifying the fuzzy membership, the above algorithm can not only cut down on a large amount of data processing and storage during the computation process compared with the traditional algorithm, so as to speed up the efficiency of the segmentation, but also improve the quality of underwater image segmentation. Finally, particle swarm optimization (PSO) described by the sine function was introduced to the algorithm mentioned above. It made up for the shortcomings that the FCM algorithm can not get the global optimal solution. Thus, on the one hand, it considers the global impact and achieves the local optimal solution, and on the other hand, further greatly increases the computing speed. Experimental results indicate that the novel algorithm can reach a better segmentation quality and the processing time of each image is reduced. They enhance efficiency and satisfy the requirements of a highly effective, real-time AUV.

The construction and shape of UUVs are described in the paper. UUV design is the shape of the overall design of unmanned underwater vehicle should first be resolved UUV underwater vehicle directly affects the shape of the resistance and noise, which is related to energy, payload, maneuverability and concealment UUV problem The main characteristic and parameter tables for foreign torpedo shape, flat shape and anomalous shape are also given in the paper. The general layout of typical foreign UUVs is analyzed in detail. And the total layout figure and interior constructive figure are introduced. Torpedo-type because of its good water power and low noise, no one has been the main form of underwater vehicle-like, and many designers are now highly favored because of its stable performance, anti-environmental interference capability. Other irregular shapes designed primarily for the completion of a specific task, according to the specific environment and mission requirements. According to comparing and summarizing, some suggestions and conclusions are presented.

To provide a suitable model for AUV simulation and control purposes, a general nonlinear dynamic model including a novel thruster hydrodynamics model was derived. Based on the modeling method, the “AUV-XX” simulation platform was established to carry out fundamental tests on its motion characteristics, stability, and controllability. A motion control strategy consisting of both position and speed control in a horizontal plane was designed for different task assignments of underwater vehicles. Combined control of heave and pitch was adopted to compensate for the reduction of vertical tunnel thrusters when the vehicle is moving at a high speed. An improved S-surface controller based on the capacitor plate model was developed with flexible gain selections made possible by different forms of restricting the error and changing the rate of the error. Simulation results show that the derived general mathematical model together with simulation platform can provide a test bed for fundamental tests of motion control. Additionally, the capacitor plate model S-surface control shows a good performance in guiding the vehicle to achieve the desired position and speed with sufficient accuracy.

S surface controllers have been proven to provide effective motion control for an autonomous underwater vehicle (AUV). However, it is difficult to adjust their control parameters manually. Choosing the optimum parameters for the controller of a particular AUV is a significant challenge. To automate the process, a modified particle swarm optimization (MPSO) algorithm was proposed. It was based on immune theory, and used a nonlinear regression strategy for inertia weight to optimize AUV control parameters. A semi-physical simulation system for the AUV was developed as a platform to verify the proposed control method, and its structure was considered. The simulation results indicated that the semi-physical simulation platform was helpful, the optimization algorithm has good local and global searching abilities, and the method can be reliably used for an AUV.

An autonomous underwater vehicle (AUV) must use an algorithm to plan its path to distant, mobile offshore objects. Because of the uneven distribution of obstacles in the real world, the efficiency of the algorithm decreases if the global environment is represented by regular grids with all of them at the highest resolution. The framed quadtree data structure is able to more efficiently represent the environment. When planning the path, the dynamic object is expressed instead as several static objects which are used by the path planner to update the path. By taking account of the characteristics of the framed quadtree, objects can be projected on the frame nodes to increase the precision of the path. Analysis and simulations showed the proposed planner could increase efficiency while improving the ability of the AUV to follow an object.

Focused underwater plasma sound sources are being applied in more and more fields. Focusing performance is one of the most important factors determining transmission distance and peak values of the pulsed sound waves. The sound source’s components and focusing mechanism were all analyzed. A model was built in 3D Max and wave strength was measured on the simulation platform. Error analysis was fully integrated into the model so that effects on sound focusing performance of processing-errors and installation-errors could be studied. Based on what was practical, ways to limit the errors were proposed. The results of the error analysis should guide the design, machining, placement, debugging and application of underwater plasma sound sources.

In order to improve the security and reliability for autonomous underwater vehicle (AUV) navigation, an H∞ robust fault-tolerant controller was designed after analyzing variations in state-feedback gain. Operating conditions and the design method were then analyzed so that the control problem could be expressed as a mathematical optimization problem. This permitted the use of linear matrix inequalities (LMI) to solve for the H∞ controller for the system. When considering different actuator failures, these conditions were then also mathematically expressed, allowing the H∞ robust controller to solve for these events and thus be fault-tolerant. Finally, simulation results showed that the H∞ robust fault-tolerant controller could provide precise AUV navigation control with strong robustness.

Valuable mineral resources are widely distributed throughout the seabed. autonomous underwater vehicles (AUVs) are preferable to remotely-operated vehicles (ROVs) when probing for such mineral resources as the extensive exploration area makes it difficult to maintain contact with operators. AUVs depend on batteries, so their power consumption should be reduced to extend exploration time. Power for conventional marine instrument systems is incorporated in their waterproof sealing. External intermittent control of this power source until termination of exploration is challenging due to limitations imposed by the underwater environment. Thus, the AUV must have a power control system that can improve performance and maximize use of battery capacity. The authors developed such a power control system with a three-step algorithm. It automatically detects underwater operational states and can limit power, effectively decreasing power consumption by about 15%.

Underwater multi-target tracking logic and decision (UMTLD) has difficulty resolving multi-target tracking problems for underwater vehicles. Present methods assume factors in UMTLD are uncorrelated, when these are actually in a complex, interdependent relationship. To provide this, an index set of multi-target tracking decision characteristics and an analytic network process (ANP) model of the UMTLD method was established. This method brings the index set of multi-target tracking decision into the ANP model, and the optimization multitarket tracking decision is achieved via computation of the resulting supermatrix. The rationality and robustness of decision results increase in simulations by 13% and 47% respectively with analytic hierarchy process (AHP). These results indicate that the ANP method should be the preferred method when UMTLD factors are interdependent.

The authors proposed a moving long baseline algorithm based on the extended Kalman filter (EKF) for cooperative navigation and localization of multi-unmanned underwater vehicles (UUVs). Research on cooperative navigation and localization for multi-UUVs is important to solve navigation problems that restrict long and deep excursions. The authors investigated improvements in navigation accuracy. In the moving long base line (MLBL) structure, the master UUV is equipped with a high precision navigation system as a node of the moving long baseline, and the slave UUV is equipped with a low precision navigation system. They are both equipped with acoustic devices to measure relative location. Using traditional triangulation methods to calculate the position of the slave UUV may cause a faulty solution. An EKF was designed to solve this, combining the proprioceptive and exteroceptive sensors. Research results proved that the navigational accuracy is improved significantly with the MLBL method based on EKF.

Accurate modeling and simulation of autonomous underwater vehicle (AUV) is essential for autonomous control and maneuverability research. In this paper, a mini AUV? “MAUV-Ⅱ” was researched and the nonlinear mathematic model of the AUV in spatial motion was derived based on momentum theorem. The forces acting on AUV were resolved to several modules which were expressed in matrix form. Based on the motion model and combined with virtual reality technology, a motion simulation system was constructed. Considering the characteristic of “MAUV-Ⅱ”, the heading control and depth control were simulated by adopting S-surface control method. A long distance traveling simulation experiment based on target planning was also done. The simulation results show that the “MAUV-Ⅱ” has good spatial maneuverability, and verify the feasibility and reliability of control software.

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

S-surface control has proven to be an effective means for motion control of underwater autonomous vehicles (AUV). However there are still problems maintaining steady precision of course due to the constant need to adjust parameters,especially where there are disturbing currents. Thus an intelligent integral was introduced to improve precision. An expert S-surface control was developed to tune the parameters on-line,based on the expert system,it provides S-surface control according to practical experience and control knowledge. To prevent control output over-compensation,a fuzzy neural network was included to adjust the production rules to the knowledge base. Experiments were conducted on an AUV simulation platform,and the results show that the expert S-surface controller performs better than an S-surface controller in environments with currents,producing good steady precision of course in a robust way.

Variable ballast systems are necessary for manned submersibles to adjust their buoyancy. In this paper,the design of a variable ballast system for a manned submersible is described. The variable ballast system uses a super high pressure hydraulic seawater system. A super high pressure seawater pump and a deep-sea brushless DC motor are used to pump seawater into or from the variable ballast tank,increasing or decreasing the weight of the manned submersible. A magnetostrictive linear displacement transducer can detect the seawater level in the variable ballast tank. Some seawater valves are used to control pumping direction and control on-off states. The design and testing procedure for the valves is described. Finally,the future development of variable ballast systems and seawater hydraulic systems is projected.

This paper informally introduces colored object-oriented Petri Nets(COOPN) with the application of the AUV system. According to the characteristic of the AUV system’s running environment,the object-oriented method is used in this paper not only to dispart system modules but also construct the refined running model of AUV system,then the colored Petri Net method is used to establish hierarchically detailed model in order to get the performance analyzing information of the system. After analyzing the model implementation,the errors of architecture designing and function realization can be found. If the errors can be modified on time,the experiment time in the pool can be reduced and the cost can be saved.

Fuzzy neural networks (FNN) based on Gaussian membership functions can effectively control the motion of underwater vehicles. However, their operating processes and training algorithms are complicated, placing great demands on embedded hardware. This paper presents an advanced FNN with an S membership function matching the motion characteristics of mini underwater vehicles with wings. A learning algorithm was then developed. Simulation results showed that the modified FNN is a simpler algorithm with faster calculations and improves responsiveness, compared with a Gaussian membership function-based FNN. It is applicable for mini underwater vehicles that don’t need accurate positioning but must have good maneuverability.

Underwater vehicles have already adopted self-correcting directional guidance algorithms based on multi-beam self-guidance systems, not waiting for research to determine the most effective algorithms. The main challenges facing research on these guidance systems have been effective modeling of the guidance algorithm and a means to analyze the simulation results. A simulation structure based on Simulink that dealt with both issues was proposed. Initially, a mathematical model of relative motion between the vehicle and the target was developed, which was then encapsulated as a subsystem. Next,steps for constructing a model of the self-correcting guidance algorithm based on the Stateflow module were examined in detail. Finally, a 3-D model of the vehicle and target was created in VRML, and by processing mathematical results, the model was shown moving in a visual environment. This process gives more intuitive results for analyzing the simulation. The results showed that the simulation structure performs well. The simulation program heavily used modularization and encapsulation, so has broad applicability to simulations of other dynamic systems.

Underwater cylindrical shell structures have been found a wide of application in many engineering fields,such as the element of marine,oil platforms,etc.The coupled vibration analysis is a hot issue for these underwater structures.The vibration characteristics of underwater structures are influenced not only by hydrodynamic pressure but also by hydrostatic pressure corresponding to different water depths.In this study,an acoustic finite element method was used to evaluate the underwater structures.Taken the hydrostatic pressure into account in terms of initial stress stiffness,an acoustical fluid-structure coupled analysis of underwater cylindrical shells has been made to study the effect of hydrodynamic pressures on natural frequency and sound radiation.By comparing with the frequencies obtained by the acoustic finite element method and by the added mass method based on the Bessel function,the validity of present analysis was checked.Finally,test samples of the sound radiation of stiffened cylindrical shells were acquired by a harmonic acoustic analysis.The results showed that hydrostatic pressure plays an important role in determining a large submerged body motion,and the characteristics of sound radiation change with water depth. Furthermore,the analysis methods and the results are of significant reference value for studies of other complicated submarine structures.

In the underwater environment,many visual sensors don’t work,and many sensors which work well for robots working in space or on land can not be used underwater.Therefore,an optical fiber slide tactile sensor was designed based on the inner modulation mechanism of optical fibers.The principles and structure of the sensor are explained in detail.Its static and dynamic characteristics were analyzed theoretically and then simulated.A dynamic characteristic model was built and the simulation made using the GA based neural network.In order to improve sensor response,the recognition model of the sensor was designed based on the’inverse solution’principle of neural networks,increasing the control precision and the sensitivity of the manipulator.

The control system determines the effectiveness of an underwater hydraulic shock shovel.This paper begins by analyzing the working principles of these shovels and explains the importance of their control systems.A new type of control system’s mathematical model was built and analyzed according to those principles.Since the initial control system’s response time could not fulfill the design requirements,a PID controller was added to the control system.System response time was still slower than required,so a neural network was added to nonlinearly regulate the proportional element,integral element and derivative element coefficients of the PID controller.After these improvements to the control system,system parameters fulfilled the design requirements.The working performance of electrically-controlled parts such as the rapidly moving high speed switch valve is largely determined by the control system. Normal control methods generally can’t satisfy a shovel’s requirements,so advanced and normal control methods were combined to improve the control system,bringing good results.

An optimized methodology to design a more robust torpedo shell is proposed. The method has taken into account reliability requirements and controllable and uncontrollable factors such as geometry, load, material properties, manufacturing processes, installation, etc. as well as human and environmental factors. The result is a more realistic shell design. Our reliability optimization design model was developed based on sensitivity analysis. Details of the design model are given in this paper. An example of a torpedo shell design based on this model is given and demonstrates that the method produces designs that are more effective and reliable than traditional torpedo shell designs. This method can be used for other torpedo system designs.

This paper researches on a kind of control architecture for autonomous underwater vehicle (AUV). After describing the hybrid property of the AUV control system, we present the hierarchical AUV control architecture. The architecture is organized in three layers: mission layer, task layer and execution layer. State supervisor and task coordinator are two key modules handling discrete events, so we describe these two modules in detail. Finally, we carried out a series of tests to verify this architecture. The test results show that the AUV can perform autonomous missions effectively and safely. We can conclude the control architecture is valid and practical.