$H_{2}$ and $H_{infty}$ Designs for Diving and Course Control of an Autonomous Underwater Vehicle in Presence of Waves

$H_{2}$ and $H_{infty}$ designs applied to the diving and course control of an autonomous underwater vehicle (AUV) considering the presence of wave disturbances are described. The six-degrees-of-freedom equations of motion of the vehicle are described as a linear model and divided into three noninteracting (or lightly interacting) subsystems for speed control, steering, and diving. This work is based on the slender form of the Naval Postgraduate School (NPS, Monterey, CA) AUV, considering that the subsystems can be controlled by means of two single-screw propellers, a rudder, port and starboard bow planes, and a stern plane. A model of the AUV dynamics is presented with the first- and the second-order wave force disturbances, i.e., the Froude–Kriloff and diffraction forces. An algorithm of nonlinear regression for the rationalization of the subsurface sea spectrum is provided in this case study. The obtained results are analyzed and evaluated in the frequency domain comparing the controllers performance considering or not the inclusion of the model of waves.      

Model simplification for AUV pitch-axis control design

Although the use of low-order equivalent models is common and extensively studied for control of aircraft systems, similar analysis has not been performed for submersible systems. Toward an improved understanding of the utility of low-order equivalent models for submersible systems, we examine control design for pitch-axis motion of an autonomous underwater vehicle (AUV). Derived from first principles, the pitch-axis motion of a streamlined AUV is described by third-order dynamics. However, second-order approximate models are common for system identification and control design. In this work, we provide theoretical justification for both the use of and limitations of a second-order model, and we verify our results in practice via a series of case studies. We conclude that a second-order pitch-axis model should often be sufficient for system identification and control design.     

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.     

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.     

Nonlinear path-following control of an AUV

A new type of control law is developed to steer an autonomous underwater vehicle (AUV) along a desired path. The methodology adopted for path-following deals explicitly with vehicle dynamics. Furthermore, it overcomes stringent initial condition constraints that are present in a number of path-following control strategies described in the literature. Controller design builds on Lyapunov theory and backstepping techniques. The resulting nonlinear feedback control law yields convergence of the path-following error trajectory to zero. Simulation results illustrate the performance of the control system proposed.     

Robust leader-follower formation tracking control of multiple underactuated surface vessels

This paper is concerned with the formation control problem of multiple underactuated surface vessels moving in a leader-follower formation.The formation is achieved by the follower to track a virtual target defined relative to the leader.A robust adaptive target tracking law is proposed by using neural network and backstepping techniques.The advantage of the proposed control scheme is that the uncertain nonlinear dynamics caused by Coriolis/centripetal forces,nonlinear damping,unmodeled hydrodynamics and disturbances from the environment can be compensated by on line learning.Based on Lyapunov analysis,the proposed controller guarantees the tracking errors converge to a small neighborhood of the origin.Simulation results demonstrate the effectiveness of the control strategy.     

Control synthesis and adaptation for an underactuated autonomousunderwater vehicle

The motion of an autonomous underwater vehicle (AUV) is controllable even with reduced control authority such as in the event of an actuator failure. In this paper we describe a technique for synthesizing controls for underactuated AUV's and show how to use this technique to provide adaptation to changes in control authority. Our framework is a motion control system architecture which includes both feed-forward control as well as feedback control. We confine ourselves to kinematic models and exploit model nonlinearities to synthesize controls. Our results are illustrated for two examples, the first a yaw maneuver of an AUV using only roll and pitch actuation, and the second a “parking maneuver” for an AUV. Experimental results for the yaw maneuver example are described     

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 .      

Model reference adaptive autopilot with anti-windup compensator for an autonomous underwater vehicle: Design and hardware in the loop implementation results

In this paper, a novel model reference adaptive controller with anti-windup compensator (MRAC_AW) is proposed for an autonomous underwater vehicle (AUV). Input saturations and parametric uncertainties are among the practical problems in the control of autonomous vehicles. Hence, utilizing a proper adaptive controller with the ability to handle actuator saturations is of a particular value. The proposed technique of this paper incorporates the well-posed model reference adaptive control with integral state feedback and a modern anti-windup scheme to present an appropriate performance in practical conditions of an AUV. Stability of the proposed method is analyzed by Lyapunov theory. Then, the proposed controller is implemented in the hardware in the loop simulation of AUV. For this purpose, the introduced method is implemented in an onboard computer to be checked in a real-time dynamic simulation environment. Obtained results in the presence of real hardware of system, actuators, computational delays and real-time execution verify the effectiveness of proposed scheme.     

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.     

Toward an improved understanding of thruster dynamics forunderwater vehicles

This paper proposes a novel approach to modeling the four quadrant dynamic response of thrusters as used for the motion control of ROV and AUV underwater vehicles. The significance is that these vehicles are small in size and respond quickly to commands. Precision in motion control will require further understanding of thruster performance than is currently available. The model includes a four quadrant mapping of the propeller blades lift and drag forces and is coupled with motor and fluid system dynamics. A series of experiments is described for both long and short period triangular, as well as square wave inputs. The model is compared favorably with experimental data for a variety of differing conditions and predicts that force overshoots are observed under conditions of rapid command changes. Use of the model will improve the control of dynamic thrust on these vehicles     

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.     

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     

可着陆式水下机器人的多体动力学建模与仿真

可着陆式水下机器人由于变浮力机构的设计要求,其外形与结构较之传统的水下航行器更为复杂。在设计阶段对可着陆式水下机器人进行仿真和操纵性分析具有重要意义。文中采用多体系统动力学方法分析可着陆式水下机器人动力学特性,将作用在系统各组成部分上的流体动力、推进力以及其它作用力分别计算和考虑,建立了多体动力学模型,并进行了三维空间运动仿真。该方法为具有较复杂附体结构的水下机器人设计和动力学仿真提供了有效途径。     

Numerical analysis of control surface effects on AUV manoeuvrability

Computational fluid dynamics, CFD, is becoming an essential tool in the prediction of the hydrodynamic efforts and flow characteristics of underwater vehicles for manoeuvring studies. However, when applied to the manoeuvrability of autonomous underwater vehicles, AUVs, most studies have focused on the determination of static coefficients without considering the effects of the vehicle control surface deflection. This paper analyses the hydrodynamic efforts generated on an AUV considering the combined effects of the control surface deflection and the angle of attack using CFD software based on the Reynolds-averaged Navier–Stokes formulations. The CFD simulations are also independently conducted for the AUV bare hull and control surface to better identify their individual and interference efforts and to validate the simulations by comparing the experimental results obtained in a towing tank. Several simulations of the bare hull case were conducted to select the k–ω SST turbulent model with the viscosity approach that best predicts its hydrodynamic efforts. Mesh sensitivity analyses were conducted for all simulations. For the flow around the control surfaces, the CFD results were analysed according to two different methodologies, standard and nonlinear. The nonlinear regression methodology provides better results than the standard methodology does for predicting the stall at the control surface. The flow simulations have shown that the occurrence of the control surface stall depends on a linear relationship between the angle of attack and the control surface deflection. This type of information can be used in designing the vehicle's autopilot system.     

水下自主机器人水动力预报方法研究

针对水下机器人操纵性优化设计中水动力系数预报问题,在水下机器人水动力预报中引入艇体肥瘦指数概念,确定了水下机器人艇体几何描述的五参数模型。提出采用小波神经网络方法预报水下机器人水动力,确定了神经网络的结构,利用均匀试验设计方法,设计了神经网络的学习样本。研究结果表明,只要确定适当的输入参数,选择适当的学习样本和网络结构,利用小波神经网络方法对水下机器人水动力进行预报可以达到较好的精度。     

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.     

Multivariable sliding mode control for autonomous diving andsteering of unmanned underwater vehicles

A six-degree-of-freedom model for the maneuvering of an underwater vehicle is used and a sliding-mode autopilot is designed for the combined steering, diving, and speed control functions. In flight control applications of this kind, difficulties arise because the system to be controlled is highly nonlinear and coupled, and there is a good deal of parameter uncertainty and variation with operational conditions. The development of variable-structure control in the form of sliding modes has been shown to provide robustness that is expected to be quite remarkable for AUV autopilot design. It is shown that a multivariable sliding-mode autopilot based on state feedback, designed assuming decoupled modeling, is quite satisfactory for the combined speed, steering, and diving response of a slow AUV. The influence of speed, modeling nonlinearity, uncertainty, and disturbances, can be effectively compensated, even for complex maneuvering. Waypoint acquisition based on line-of-sight guidance is used to achieve path tracking     

An intelligent control system for remotely operated vehicles

The application of a neural network controller to remotely operated vehicles (ROVs) is described. Three learning algorithms for online implementation of a neural net controller are discussed with a critic equation. These control schemes do not require any information about the system dynamics except an estimate of the inertia terms. Selection of the number of layers in the neural network, the number of neurons in the hidden layer, initial weights for the network and the critic coefficient were done based on the results of preliminary tests. The performances of the three learning algorithms were compared by computer simulation. The effectiveness of the neural net controller in handling time-varying parameters and random noise is shown by a case study of the ROV system