Maneuvering modeling and simulation of AUV dynamic systems with Euler-Rodriguez quaternion method

The purpose of this study is to develop maneuvering models and systems of a simulator to improve the motion performance of autonomous underwater vehicles (AUVs) at the preliminary design stages in advance. The AUVs simulation systems based on the standard submarine equations of motion in six-degree-of-freedom (6-DOF) integrated with the Euler-Rodriguez quaternion method for representing singularity-free AUV attitude and time-saving calculation, and with a nonlinear control model for maneuvering and depth control simulations, time-marching in the fourth-order Runge-Kutta scheme. For validation of the simulation codes, results of the ISiMI AUV open-loop tests including turning test and zigzag test as well as an AUV simulator on the basis of Euler-angle method were used to compare with the quaternion-based AUV simulator. The computational results from the proposed simulator agree well with those from both the ISiMI AUV experiments and the Euler-angle based simulations. Additionally, a new maneuvering procedure, namely "put-out" was implemented to test directional stability for a large-scale AUV in the proposed AUV simulator that can be considered for vehicles in space as well as in constrained planes.     

On-line learning control of autonomous underwater vehicles usingfeedforward neural networks

A neural-network-based learning control scheme for the motion control of autonomous underwater vehicles (AUV) is described. The scheme has a number of advantages over the classical control schemes and conventional adaptive control techniques. The dynamics of the controlled vehicle need not be fully known. The controller with the aid of a gain layer learns the dynamics and adapts fast to give the correct control action. The dynamic response and tracking performance could be accurately controlled by adjusting the network learning rate. A modified direct control scheme using multilayered neural network architecture is used in the studies with backpropagation as the learning algorithm. Results of simulation studies using nonlinear AUV dynamics are described in detail. The robustness of the control system to sudden and slow varying disturbances in the dynamics is studied and the results are presented     

Robust Nonlinear Path-Following Control of an AUV

This paper develops a robust nonlinear controller that asymptotically drives the dynamic model of an autonomous underwater vehicle (AUV) onto a predefined path at a constant forward speed. A kinematic controller is first derived, and extended to cope with vehicle dynamics by resorting to backstepping and Lyapunov-based techniques. Robustness to vehicle parameter uncertainty is addressed by incorporating a hybrid parameter adaptation scheme. The resulting nonlinear adaptive control system is formally shown and it yields asymptotic convergence of the vehicle to the path. Simulations illustrate the performance of the derived controller .      

AUV定位信号检测延时的蒙特卡洛模拟分析

在简要介绍AUV声学定位声纳接收机原理基础上,分析了CW脉冲信号在极性相关检测电路中的传输过程,建立了极性相关积分检测延时仿真分析模型。提出采用蒙特卡洛模拟方法获取检测延时的分布特征和统计参数的观点。实验结果表明蒙特卡洛模拟实验与硬件电路实验结果一致,对于解决随机性检测延时问题具有很强的能力。获得的结果可为AUV定位声纳检测门限的设定、声学测距和定位精度分析以及水声通信延时分析提供参考。     

Discrete-time quasi-sliding mode control of an autonomousunderwater vehicle

This paper presents a discrete-time quasi-sliding mode controller for an autonomous underwater vehicle (AUV) in the presence of parameter uncertainties and a long sampling interval. The AUV, named VORAM, is used as a model for the verification of the proposed control algorithm. Simulations of depth control and contouring control are performed for a numerical model of the AUV with full nonlinear equations of motion to verify the effectiveness of the proposed control schemes when the vehicle has a long sampling interval. By using the discrete-time quasi-sliding mode control law, experiments on depth control of the AUV are performed in a towing tank. The controller makes the system stable in the presence of system uncertainties and even external disturbances without any observer nor any predictor producing high rate estimates of vehicle states. As the sampling interval becomes large, the effectiveness of the proposed control law is more prominent when compared with the conventional sliding mode controller     

全姿态水下移动平台模式切换姿态控制研究

为了适应复杂海洋环境中多样性的观探测任务需求,本文提出了一种融合Argo浮标、水下滑翔机（Glider）和自治式水下机器人（Autonomous Underwater Vehicle,AUV） 3种工作模式的全姿态水下移动平台（All-attitude Multimode Underwater Vehicle,AMUV）。首先,基于3种水下移动平台的工作原理,建立了AMUV的六自由度动力学模型;然后,针对动力学模型中的非线性耦合特性及模式切换过程中的驱动位形变化等问题,基于比例、积分、微分控制器（Proportional Integral Derivative,PID）与模糊控制概念,设计了不依赖于数学模型的自适应模糊PID姿态控制器,实现了AMUV多模式切换过程中的姿态控制;最后,开展多模式切换控制仿真实验,将自适应模糊PID控制器与传统PID控制器仿真结果进行对比,并设计了全模式任务工况,仿真结果表明,本文提出的控制器能够精确和稳定地控制AMUV进行多种工作模式的相互切换。     

System identification of open-loop maneuvers leads to improved AUV flight performance

The authors focus on demonstrating a simple design procedure for the Odyssey III autonomous underwater vehicle (AUV) flight control system. This procedure can be carried out quickly and routinely to maximize vehicle effectiveness. A hydrodynamic model of the vehicle was first developed from theory and bench-top laboratory tests. Using this initial model, a controller was developed from basic principles. Then, using this initial controller to reach a desired typical operating condition, a very compact set of open-loop maneuvers was performed in the field. The vehicle model was optimized using the Nelder-Mead simplex method, and a revised controller was then implemented and tested successfully.     

Discrete time-delay control of an autonomous underwater vehicle: Theory and experimental results

A discrete time-delay control (DTDC) law for a general six degrees of freedom unsymmetric autonomous underwater vehicle (AUV) is presented. Hydrodynamic parameters like added mass coefficients and drag coefficients, which are generally uncertain, are not required by the controller. This control law cancels the uncertainties in the AUV dynamics by direct estimation of the uncertainties using time-delay estimation technique. The discrete-time version of the time-delay control does not require the derivative of the system state to be measured or estimated, which is required by the continuous-time version of the controller. This particularly provides an advantage over continuous-time controller in terms of computational effort or availability of sensors for measuring state derivatives, i.e., linear and angular accelerations. Implementation issues for practical realization of the controller are discussed. Experiments on a test-bed AUV were conducted in depth, pitch, and yaw degrees of freedom. Results show that the proposed control law performs well in the presence of uncertainties.     

Three-dimensional visualization of mission planning and control forthe NPS autonomous underwater vehicle

The Naval Postgraduate School (NPS) is constructing a small autonomous underwater vehicle (AUV) with an onboard mission control computer. The mission controller software for this vehicle is a knowledge-based artificial intelligence (AI) system requiring thorough analysis and testing before the AUV is operational. The manner in which rapid prototyping of this software has been demonstrated by developing a controller code on a LISP machine and using an Ethernet link with a graphics workstation to simulate the controller's environment is discussed. The development of a testing simulator using a knowledge engineering environment (KEE) expert system shell that examines AUV controller subsystems and vehicle models before integrating them with the full AUV for its test environment missions is discussed. This AUV simulator utilizes an interactive mission planning control console and is fully autonomous once initial parameters are selected     

Adaptive output feedback control based on DRFNN for AUV

The tracking control problem of AUV in six degrees-of-freedom (DOF) is addressed in this paper. In general, the velocities of the vehicles are very difficult to be accurately measured, which causes full state feedback scheme to be not feasible. Hence, an adaptive output feedback controller based on dynamic recurrent fuzzy neural network (DRFNN) is proposed, in which the location information is only needed for controller design. The DRFNN is used to online estimate the dynamic uncertain nonlinear mapping. Compared to the conventional neural network, DRFNN can clearly improve the tracking performance of AUV due to its less inputs and stronger memory features. The restricting condition for the estimation of the external disturbances and network's approximation errors, which is often given in the existing literatures, is broken in this paper. The stability analysis is given by Lyapunov theorem. Simulations illustrate the effectiveness of the proposed control scheme.     

水下机器人推力器布置及控制仿真研究

针对自治水下机器人(Autonomous underwater vehicle,AUV)推力器布置和控制仿真的困难性及以往电机仿真难以进行的缺点,提出1种进行多推力器运动仿真的方法,该方法建立的模型克服了推力器推力控制系统不能与电机结合的问题,能较好地反映推力器布置和电机的响应情况,可为AUV的运动控制、布置设计及控制系统开发等提供验证模型.针对流线型AUV CRanger-2的推力器布置情况,在对其建立推力器模型的基础上,利用模型对设定推力下的推力器控制进行仿真.仿真结果表明:该方法能够有效地模拟推力器布置既定情况下的电机运动与推力控制,可为水下机器人控制策略优化提供仿真平台.     

Adaptive sliding mode control of autonomous underwater vehicles inthe dive plane

The problem of controlling an autonomous underwater vehicle (AUV) in a diving maneuver is addressed. Having a simple controller which performs satisfactorily in the presence of dynamical uncertainties calls for a design using the sliding mode approach, based on a dominant linear model and bounds on the nonlinear perturbations of the dynamics. Nonadaptive and adaptive techniques are considered, leading to the design of robust controllers that can adjust to changing dynamics and operating conditions. The problem of using the observed state in the control design is addressed, leading to a sliding mode control system based on input-output signals in terms of drive-phase command and depth measurement. Numerical simulations using a full set of nonlinear equations of motion show the effectiveness of the proposed techniques     

Closed-loop randomized kinodynamic path planning for an autonomous underwater vehicle

A randomized kinodynamic path planning algorithm based on the incremental sampling-based method is proposed here as the state-of-the-art in this field applicable in an autonomous underwater vehicle. Designing a feasible path for this vehicle from an initial position and velocity to a target position and velocity in three-dimensional spaces by considering the kinematic constraints such as obstacles avoidance and dynamic constraints such as hard bounds and non-holonomic characteristic of AUV are the main motivation of this research. For this purpose, a closed-loop rapidly-exploring random tree (CL-RRT) algorithm is presented. This CL-RRT consists of three tightly coupled components: a RRT algorithm, three fuzzy proportional-derivative controllers for heading and diving control and a six degree-of-freedom nonlinear AUV model. The branches of CL-RRT are expanded in the configuration space by considering the kinodynamic constraints of AUV. The feasibility of each branch and random offspring vertex in the CL-RRT is checked against the mentioned constraints of AUV. Next, if the planned branch is feasible by the AUV, then the control signals and related vertex are recorded through the path planner to design the final path. This proposed algorithm is implemented on a single board computer (SBC) through the xPC Target and then four test-cases are designed in 3D space. The results of the processor-in-the-loop tests are compared by the conventional RRT and indicate that the proposed CL-RRT not only in a rapid manner plans an initial path, but also the planned path is feasible by the AUV.     

Robust control based on feedback linearization for roll stabilizing of autonomous underwater vehicle under wave disturbances

In the case of Autonomous Underwater Vehicle(AUV) navigating with low speed near water surface,a new method for design of roll motion controller is proposed in order to restrain wave disturbance effectively and improve roll stabilizing performance.Robust control is applied,which is based on uncertain nonlinear horizontal motion model of AUV and the principle of zero speed fin stabilizer.Feedback linearization approach is used to transform the complex nonlinear system into a comparatively simple linear system.For parameter uncertainty of motion model,the controller is designed with mixed-sensitivity method based on H-infinity robust control theory.Simulation results show better robustness improved by this control method for roll stabilizing of AUV navigating near water surface.     

Coupled dynamic analysis of deep-sea mining support vessel with dynamic positioning

Deep-sea mining (DSM) is an advanced concept. A simulation method of coupled vessel/riser/body system in DSM combined with dynamic positioning (DP) is proposed. Based on the three-dimensional potential flow theory, lumped mass method, and Morison’s equations the dynamic models of the production support vessel, riser and slurry pump are established. A proportion integration differentiation (PID) controller with a nonlinear observer and a thrust allocation unit are used to simulate the DP system. Coupled time domain simulation is implemented with the vessel operated in two DP modes. Results of the vessel and pump motions, riser tension, and thruster forces are obtained. It shows that the pump will be lifted by the riser when the vessel is chasing the next set point. Riser tension is influenced by the wave frequency motions of the vessel in positioning mode and low-frequency motions in tracking mode. The proposed simulation scheme is practical to study the DSM operation.     

An on-line adaptation method in a neural network based controlsystem for AUVs

A neural network based control system “Self-Organizing Neural-Net-Controller System: SONCS” has been developed as an adaptive control system for Autonomous Underwater Vehicles (AUVs). In this paper, an on-line adaptation method “Imaginary Training” is proposed to improve the time-consuming adaptation process of the original SONCS. The Imaginary Training can be realized by a parallel structure which enables the SONCS to adjust the controller network independently of actual operation of the controlled object. The SONCS is divided into two separate parts: the Real-World Part where the controlled object is operated according to the objective, and the Imaginary-World Part where the Imaginary Training is carried out. In order to adjust the controller network by the Imaginary Training, it is necessary to introduce a forward model network which can generate simulated state variables without involving actual data. A neural network “Identification Network” which has a specific structure to simulate the behavior of dynamical systems is proposed as the forward model network. The effectiveness of the Imaginary Training is demonstrated by applying to the heading keeping control of an AUV “Twin-Burger”. It is shown that the SONCS adjusts the controller network-through on-line processes in parallel with the actual operation     

Investigation of the vectored thruster AUVs based on 3SPS-S parallel manipulator

As an extremely significant tool, autonomous underwater vehicles (AUVs) obtain corresponding development which is widely used in the oceanographic survey, military applications and ocean investigation. However, it is rather hard to fulfill missions about ocean exploration in suspended status or at slow speeds for traditional AUVs, due to the effect of the control surfaces trends to decline or even invalid completely in this condition. To overcome the limitation mentioned above, a torpedo-shaped AUV with vectored thrust ducted propeller is presented in this paper, in which the vector thruster is designed based on a 3SPS-S parallel manipulator. The 3SPS-S parallel manipulator, which has merits of compact structure, high reliability, high precision and fast response, is employed for thrust vectoring control mechanism. Additionally, the kinematics and dynamics model of the thrust-vectoring mechanism is constructed, and the MATLAB simulation results show the designed vectored thruster have great application superiority and potential for AUV. Finally, a control scheme of the vectored thruster is designed after considering the case study. The main idea of this paper lies in describing a novel design of the vectored thruster AUV based on 3SPS-S parallel manipulator, which can complete the mission at zero or slow forward speeds.     

Numerical study on the cavity characteristics and impact loads of AUV water entry

The high-speed water entry process of an autonomous underwater vehicle (AUV) has a strong impact nonlinearity, and a cavity formed by air and water will often be generated as part of the entry process. The shape of the water-entry cavity plays an important role in the load characteristics and stability of the water-entry trajectory. In this paper, a numerical model for describing the cavity and impact load characteristics of a high-speed water-entry AUV is established. The simulation results such as cavity shape and impact load are compared with experimental data. The good agreement between the numerical results and those of the experiments reveals the accuracy and capability of the numerical algorithm. Subsequently, the arbitrary Lagrange-Euler (ALE) numerical algorithm is used to simulate and analyse the variation laws of the cavity characteristics and impact loads with different head shapes, water-entry velocities, water-entry angles and angles of attack. The results obtained in this study can provide a good reference for the trajectory control and structural design of the AUV.     

Transformed equations of motion for underwater vehicles

A method for dynamics investigation and coupling detection between velocities of autonomous underwater vehicles (AUVs) is presented in this paper. The method is based on transformation of equations of motion, which are usually used for an underwater vehicle, into equations with a diagonal mass matrix. The obtained equations contain quasi-velocities and allow one to give a further insight into the AUV dynamics especially for an underactuated system. Some advantages of the proposed approach are discussed, too. An analytical example for a 3-DOF AUV shows possible application of the transformed equations. Moreover, the given approach is validated via simulation on a 6-DOF vehicle.     

Adaptive fuzzy controller design for dynamic positioning system of vessels

This paper develops an adaptive fuzzy controller for the dynamic positioning (DP) system of vessels with unknown dynamic model parameters and unknown time-varying environmental disturbances. The controller is designed by combining the adaptive fuzzy system with the vectorial backstepping method. An adaptive fuzzy system is employed to approximate the uncertain term induced by unknown dynamic model parameters and unknown time-varying environmental disturbances. It is theoretically proved that the proposed adaptive fuzzy DP controller can make the vessel be maintained at the desired values of its position and heading with arbitrary accuracy, while guaranteeing the uniform ultimate boundedness of all signals in the closed-loop DP control system of vessels. Simulation studies with comparisons on a supply vessel are carried out, and the results illustrate the effectiveness of the proposed control scheme.