Problem Of Autonomous Underwater Vehicle Research Articles

Control of Autonomous Underwater Vehicle using Reduced Order Model Predictive Control in Three Dimensional Space

The paper investigates the motion control problem of Autonomous Underwater Vehicle (AUV) in three-dimensional space. Here, we consider a non-linear, nonholonomic and highly under-actuated dynamical model of AUV with six degrees of freedom. Because of its higher-dimensional complex model, the traditional model predictive control technique leads to computational complexity and loss of controllability. The paper proposes a novel MPC scheme using reduced dynamical model. In which, the MPC problem to control AUV in vertical and horizontal planes is formulated as independent optimization problems. The proposed scheme reduces higher-dimensional model to two independent time-varying linearized models for controlling motion in vertical and horizontal planes by neglecting weakly coupled dynamics. Further the reduced optimization problem is solved using quadratic programming to achieve trade-off between computational complexity and control effort optimization. The simulation results show the effectiveness of the proposed control scheme which is employed on non-linear model.

Diving control of Autonomous Underwater Vehicle based on improved active disturbance rejection control approach

The control problem of Autonomous Underwater Vehicle (AUV) is a very challenging one since the mathematical model of AUV is characterized by high nonlinearity, strongly coupling and time-varying features. In this paper, our aim is to design a diving active disturbance rejection controller for AUV. Firstly, a mathematical model of AUV is established, and the mathematical model is subsequently decoupled into three subsystems including speed control model, diving control model and steering control model. Then, an improved tracking differentiator is employed, which can provide better noise attenuation performance and avoid the chattering phenomenon as compared to the traditional tracking differentiator. After that, the controller is designed by using the active disturbance rejection control (ADRC) with the improved tracking differentiator. Finally, simulations are given to shown the effectiveness of the developed control scheme.

Finite-Time Output Feedback Tracking Control for Autonomous Underwater Vehicles

<?Pub Dtl=""?> In this paper, the finite-time output feedback trajectory tracking control problem for autonomous underwater vehicles (AUVs) is investigated. The vehicle model is constructed in six degrees of freedom and the vehicle attitude is represented by quaternions to avoid representation singularities. The control design consists of three steps. First, by using the finite-time control technique, two global finite-time stabilizing controllers based on state feedback are proposed for the vehicle translational and rotational tracking error subsystems, respectively. Second, considering the estimation problem of the vehicle translational velocities, a global finite-time convergent observer is employed to reconstruct the information of the vehicle translational velocities. Finally, based on the proposed state feedback controllers and the finite-time convergent observer, a finite-time output feedback trajectory tracking control scheme for AUVs is derived. Global finite-time stability of the closed-loop system is rigorously proved by using Lyapunov theory. Compared with the conventional backstepping control scheme via output feedback, the proposed finite-time output feedback control scheme offers not only a faster convergence rate but also a higher tracking accuracy for trajectory tracking control of AUVs. Simulations demonstrate the effectiveness of the proposed control scheme.

Imperialist Competitive Algorithm for AUV Path Planning in a Variable Ocean

An imperialist competitive algorithm (ICA) is introduced for solving the optimal path planning problem for autonomous underwater vehicles (AUVs) operating in turbulent, cluttered, and uncertain environments. ICA is a new sociopolitically inspired global search metaheuristic based on a form of competition between “imperialist” forces and opposing colonies. In this study, ICA is applied to optimize the coordinates of a set of control points for generating a curved spline path. The ICA-based path planner is tested to find an optimal trajectory for an AUV navigating through a variable ocean environment in the presence of an irregularly shaped underwater terrain. The genetic algorithm (GA) and quantum-behaved particle swarm optimization (QPSO) are described and evaluated with the ICA for the path optimization problem. Simulation results show that the proposed ICA approach is able to obtain a more optimized trajectory than the GA- or QPSO-based methods. Monte Carlo simulations demonstrate the robustness and superiority of the proposed ICA scheme compared with the GA and QPSO schemes.

A Survey on Formation Control Algorithms for Multi-AUV System

With the development of autonomous underwater vehicle (AUV) application techniques, formation control of multiple AUVs becomes a worldwide research focus. In this paper, first, formation control methods are summarized as: virtual structure method, behavior-based method, leader–follower method and artificial potential field method. Second, the peculiarities and difficulties of formation control especially for multi-AUV system are analyzed based on the research and development status in this area. The critical technical problems are summarized into three aspects: problem of AUV's dynamic complexity; problem of environmental complexity; problem of severe underwater communication constraints. Finally, the major development trends of multi-AUV system are discussed.

Dynamic formation control for autonomous underwater vehicles

Path planning and formation structure forming are two of the most important problems for autonomous underwater vehicles (AUVs) to collaborate with each other. In this work, a dynamic formation model was proposed, in which several algorithms were developed for the complex underwater environment. Dimension changeable particle swarm algorithm was used to find an optimized path by dynamically adjusting the number and the distribution of the path nodes. Position relationship based obstacle avoidance algorithm was designed to detour along the edges of obstacles. Virtual potential point based formation-keeping algorithm was employed by incorporating dynamic strategies which were decided by the current states of the formation. The virtual potential point was used to keep the formation structure when the AUV or the formation was deviated. Simulation results show that an optimal path can be dynamically planned with fewer path nodes and smaller fitness, even with a concave obstacle. It has been also proven that different formation-keeping strategies can be adaptively selected and the formation can change its structure in a narrow area and restore back after passing the obstacle.

Cooperative localization of AUVs using moving horizon estimation

This paper studies the localization problem of autonomous underwater vehicles (AUVs) constrained by limited size, power and payload. Such AUVs cannot be equipped with heavy sensors which makes their underwater localization problem difficult. The proposed cooperative localization algorithm is performed by using a single surface mobile beacon which provides range measurement to bound the localization error. The main contribution of this paper is twofold: 1) The observability of single beacon based localization is first analyzed in the context of nonlinear discrete time system, deriving a sufficient condition on observability. It is further compared with observability of linearized system to verify that a nonlinear state estimation is necessary. 2) Moving horizon estimation is integrated with extended Kalman filter (EKF) for three dimensional localization using single beacon, which can alleviate the computational complexity, impose various constraints and make use of several previous range measurements for each estimation. The observability and improved localization accuracy of the localization algorithm are verified by extensive numerical simulation compared with EKF.

Spatial Path Following for AUVs Using Adaptive Neural Network Controllers

The spatial path following control problem of autonomous underwater vehicles (AUVs) is addressed in this paper. In order to realize AUVs’ spatial path following control under systemic variations and ocean current, three adaptive neural network controllers which are based on the Lyapunov stability theorem are introduced to estimate uncertain parameters of the vehicle’s model and unknown current disturbances. These controllers are designed to guarantee that all the error states in the path following system are asymptotically stable. Simulation results demonstrated that the proposed controller was effective in reducing the path following error and was robust against the disturbances caused by vehicle's uncertainty and ocean currents.

Research on active detection and direction finding method of autonomous underwater vehicle based on vector sensor

To resolve the detection and orientation problem of autonomous underwater vehicle which platform is limited, single vector sensor with orientation ability is selected. The method of detection and bearing estimation based on vector sensor and its performance are researched in this paper. Vector sonar synthetical copy correlator and vector sonar synthetical adaptive correlator are put forward here, which use both pressure and velocity information. The composing principle and realizing method of the two processors above are studied and the processing gain, detecting probability and bearing estimation ability of the two are analyzed in acoustic multi-path condition. The theoretical results simulation and experiments show that all methods studied above have better performance than common copy correlation, and in multipath condition, the vector sonar synthetical adaptive correlation does better than vector sonar synthetical copy correlation in the aspect of processing gain and bearing estimation. Keywords: active detection; direction finding; autonomous underwater vehicle; vector sensor; synthetical copy correlator; synthetical adaptive correlator

Path Tracking Control for Underactuated Autonomous Underwater Vehicles Using Approach Angle

In this paper, we propose a novel path tracking control algorithm for an underactuated autonomous underwater vehicle (AUV). The underactuated AUV is controlled by the thrust force and the yaw torque: no sway thruster is used. To deal with this underactuated AUV problem in the path tracking, we introduce an approach angle which makes the AUV converge to the reference path. To design the path tracking controller, we obtain the vehicle's error dynamics in the body-fixed frame, and then design the path tracking controller based on the dynamic surface control (DSC) method. The proposed controller only needs the information of the position and the heading angle of the reference path. Some simulation results demonstrate the effectiveness of the proposed controller.

Black‐box position and attitude tracking for underwater vehicles by second‐order sliding‐mode technique

AbstractIn this work we address the tracking control problems for autonomous underwater vehicles (AUVs). The proposed solution is based on the variable structure systems (VSS) theory and, in particular, on the second‐order sliding‐mode (2‐SM) methodology. The tuning of the controller is carried out via black‐box approach, dispensing with the knowledge of the actual AUV parameters, by simply progressively increasing a single gain parameter. The presented stability analysis includes explicitly the unmodelled actuator dynamics and the presence of external uncertain disturbances. The good performance of the proposed scheme is verified by means of simulations on a 6‐DOF AUV. Copyright © 2009 John Wiley &amp; Sons, Ltd.

Output feedback control design for station keeping of AUVs under shallow water wave disturbances

AbstractIn this paper, we consider the problem of autonomous underwater vehicle (AUV) station keeping (SK) in shallow water area. During SK, an AUV is required to maintain position and orientation with respect to a fixed reference point at the sea floor. When AUV operates in shallow water, high‐frequency disturbances due to waves will significantly affect the motion of the AUV. In order to derive wave disturbance information for control purposes, a nonlinear observer is first designed to estimate the shallow water wave velocities and AUV relative velocities by using position and attitude measurement. Using the observer estimates, a nonlinear output feedback controller is subsequently synthesized by applying observer backstepping technique. Global exponential stability (GES) of the proposed nonlinear observer–controller design is proved through Lyapunov stability theory. Simulation studies on a model based on an actual AUV were performed to verify the performance of the proposed nonlinear observer and output feedback controller. Copyright © 2008 John Wiley &amp; Sons, Ltd.

Investigation of a method for predicting AUV derivatives

The paper addresses the problem of autonomous underwater vehicle (AUV) modelling and parameter estimation as a means to predict the dynamic performance of underwater vehicles and thus provide solid guidelines during their design phase. The use of analytical and semi-empirical (ASE) methods to estimate the hydrodynamic derivatives of a popular class of AUVs is discussed. A comparison is done with the results obtained by using computational fluid dynamics to evaluate the bare hull lift force distribution around a fully submerged body. An application is made to the estimation of the hydrodynamic derivatives of the MAYA AUV, an autonomous underwater vehicle developed under a joint Indian-Portuguese project. The estimates obtained were used to predict the turning diameter of the vehicle during sea trials.

Guidance, navigation and control system for the Tethra unmanned underwater vehicle

High-resolution (acoustic & video) seabed survey requires deployment of sensors on platforms close to the seabed. The unstructured, harsh and hazardous nature of the ocean environment and close proximity to the seabed and other hazards produces serious problems for autonomous underwater vehicles (AUV) during the mission. The Mobile & Marine Robotics Research Centre at the University of Limerick is developing a highly manoeuvrable AUV/ROV platform to address the challenges of high-resolution seabed survey in both shallow and deep water. The overall system integrates state-of-the-art survey equipment, a multi-thruster open-frame AUV Tethra and an advanced control system. This paper gives an overview of the overall system including simulation results.

Depth control of the INFANTE AUV using gain-scheduled reduced order output feedback

The paper addresses the problem of autonomous underwater vehicle (AUV) control in the absence of full state information. An application is made to the control of a prototype AUV in the vertical plane. The methodology adopted for controller design is nonlinear gain-scheduling control, whereby a set of linear, dynamic, reduced order output feedback controllers are designed and scheduled on the vehicle's forward speed. The paper summarizes the controller design steps, describes a technique for its practical implementation, and presents experimental results obtained with the INFANTE AUV during tests at sea.

DEPTH CONTROL OF THE INFANTE AUV USING GAIN-SCHEDULED REDUCED-ORDER OUTPUT FEEDBACK

The paper addresses the problem of autonomous underwater vehicle (AUV) control in the absence of full state information. An application is made to the control of a prototype AUV in the vertical plane. The methodology adopted for controller design is nonlinear gain scheduling control, whereby a set of linear, dynamic reduced order output feedback controllers are designed and scheduled on the vehicle's forward speed. The paper summarizes the basic controller design steps, describes a technique for practical implementation of the nonlinear control systems derived, and presents experimental results obtained with the INFANTE AUV during tests at sea.

AUV dynamics: Modelling and parameter estimation using analytical, semi-empirical, and CFD methods

The paper addresses the problem of autonomous underwater vehicle (AUV) modeling and parameter estimation as a means to predict the expected dynamic performance of underwater vehicles and thus provide solid guidelines during their design phase. The use of analytical and semi-empirical (ASE) methods to predict the hydrodynamic derivatives of a large class of AUVs with conventional, streamlined bodies is discussed. An application is made to the estimation of the hydrodynamic derivatives of the MAYA AUV, an autonomous vehicle that is being developed under a joint Indian-Portuguese project. The estimates are used to predict the behavior of the vehicle in the vertical plane and to assess the impact of stern plane size on its expected performance.

Multivariable Neurofuzzy Control of an Autonomous Underwater Vehicle

This paper discusses the application of a novel multivariable control technique to the problem of autonomous underwater vehicle (AUV) autopilot design. Based on an adaptive neural network structure a multivariable Sugeno style fuzzy inference system

Multivariable intelligent control strategies for an autonomous underwater vehicle

This paper discusses the application of a novel multivariable control technique to the problem of autonomous underwater vehicle (AUV) autopilot design. Based on an adaptive network structure a multivariable Sugeno style fuzzy inference system is tuned to produce autopilots for simultaneous control of multiple degrees of freedom for an AUV. Simulation results illustrate the effectiveness of this new multivariable approach for course-changing roll-regulating, and y-positional-changing yaw-regulating control when compared with a traditional multi-input single-output control approach whereby control of each degree of freedom is considered separately and hence no provision is made for the inherent cross-coupling between AUV channel motions.