Download or read book Optimal Fault Detection and Resolution During Maneuvering for Autonomous Underwater Vehicles written by Andrew S. Gibbons and published by . This book was released on 2000 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to increase robustness, reliability, and mission success rate, autonomous vehicles must detect debilitating system control faults. Prior model-based observer design for 21UUV was analyzed using actual vehicle sensor data. It was shown, based on experimental response, that residual generation during maneuvering was too excessive to detect manually implemented faults. Optimization of vehicle hydrodynamic coefficients in the model significantly decreased maneuvering residuals, but did not allow for adequate fault detection. Kalman filtering techniques were used to improve residual reduction during maneuvering and increase residual generation during fault conditions. Optimization of the Kalman filter's system noise matrix, measurement noise matrix, and input gain scalar multiplier produced fault resolution which allowed for accurate detection of fault of relatively minor magnitude within minimal time constraints.

Download or read book Optimal Fault Detection and Resolution During Maneuvaring for AutonomousUnderwater Vehicles written by Andrew S. Gibbons and published by . This book was released on 2000-03-01 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to increase robustness, reliability, and mission success rate, autonomous vehicles must detect debilitating system control faults. Prior model-based observer design for 21UUV was analyzed using actual vehicle sensor data. It was shown, based on experimental response, that residual generation during maneuvering was too excessive to detect manually implemented faults. Optimization of vehicle hydrodynamic coefficients in the model significantly decreased maneuvering residuals, but did not allow for adequate fault detection. Kalman filtering techniques were used to improve residual reduction during maneuvering and increase residual generation during fault conditions. Optimization of the Kalman filter's system noise matrix, measurement noise matrix, and input gain scalar multiplier produced fault resolution which allowed for accurate detection of fault of relatively minor magnitude within minimal time constraints.

Download or read book On Line Identification of the Speed Steering and Diving Response Parameters of an Autonomous Underwater Vehicle from Experimental Data written by and published by . This book was released on 1992 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: The experimental response data from autonomous maneuvering using the NPS AUV II vehicle has been analyzed with a view to defining Kalman filters to provide on-line estimates of system parameters and their variability. Kalman filters, designed for parameter estimation are expected to be the first step in the development of autonomous fault detection systems for underwater vehicles. Secondly, extraction of vehicle hydrodynamic coefficients from these parameters can help to develop vehicle dynamic simulators. Thirdly, knowledge of these parameters will allow the design of improved autopilot and guidance laws.

Download or read book Robust Model Based Fault Diagnosis for Unmanned Underwater Vehicles Using Sliding Mode Observers written by and published by . This book was released on 1999 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: The early detection of the malfunctions and faults as well as their compensation is crucial both for maintenance and for mission reliability of unmanned underwater vehicles (UUVs). Among the different fault detection methods using analytical redundancy, the first distinction rises between model-free and model-based approaches. Model-free methods are well-suited for large-scale systems, where the development of a model is too expensive. The lumped parameter model of an underwater vehicle can be easily described by a small set of well-known equations with highly uncertain parameters. This uncertainty suggests the introduction of robustness requirements in the model-based residual generation for UUVs. Robustness can be addressed in many different ways. According to the same view, the so-called unknown input observer (UIO) has been proposed. These approaches share the common idea of decoupling residuals and noises by eliminating (or at least reducing in some optimal sense) the influence of the disturbances on the residuals.

Download or read book AUV Fault Detection Using Model Based Observer Residuals written by James E. Melvin and published by . This book was released on 1998-06-01 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order for the Navy's next generation Unmanned Undersea Vehicles to be more robust to software/hardware faults, on-line failure detection and resolution is needed. Typically, fault detection methods include limits and trends analysis, model free, and model based techniques. Here, model based observers are proposed for the detection of fault induced dynamic signals in the diving, steering, and roll control systems. Such automatic fault detection systems were designed and implemented in a Simulink model of the "21UUV." in the course of conducting simulations with the model, numerous vehicle behaviors were studied and detection response was verified. In addition, the model based observer residuals may be designed to distinguish actuator faults from wave disturbances and fin faults from maneuvering responses.

Download or read book Advanced Model Predictive Control for Autonomous Marine Vehicles written by Yang Shi and published by Springer Nature. This book was released on 2023-02-13 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of marine control system design related to underwater robotics applications. In particular, it presents novel optimization-based model predictive control strategies to solve control problems appearing in autonomous underwater vehicle applications. These novel approaches bring unique features, such as constraint handling, prioritization between multiple design objectives, optimal control performance, and robustness against disturbances and uncertainties, into the control system design. They therefore form a more general framework to design marine control systems and can be widely applied. Advanced Model Predictive Control for Autonomous Marine Vehicles balances theoretical rigor – providing thorough analysis and developing provably-correct design conditions – and application perspectives – addressing practical system constraints and implementation issues. Starting with a fixed-point positioning problem for a single vehicle and progressing to the trajectory-tracking and path-following problem of the vehicle, and then to the coordination control of a large-scale multi-robot team, this book addresses the motion control problems, increasing their level of challenge step-by-step. At each step, related subproblems such as path planning, thrust allocation, collision avoidance, and time constraints for real-time implementation are also discussed with solutions. In each chapter of this book, compact and illustrative examples are provided to demonstrate the design and implementation procedures. As a result, this book is useful for both theoretical study and practical engineering design, and the tools provided in the book are readily applicable for real-world implementation.

Download or read book Autonomous Underwater Vehicles written by Jing Yan and published by Springer Nature. This book was released on 2021-11-01 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous underwater vehicles (AUVs) are emerging as a promising solution to help us explore and understand the ocean. The global market for AUVs is predicted to grow from 638 million dollars in 2020 to 1,638 million dollars by 2025 – a compound annual growth rate of 20.8 percent. To make AUVs suitable for a wider range of application-specific missions, it is necessary to deploy multiple AUVs to cooperatively perform the localization, tracking and formation tasks. However, weak underwater acoustic communication and the model uncertainty of AUVs make achieving this challenging. This book presents cutting-edge results regarding localization, tracking and formation for AUVs, highlighting the latest research on commonly encountered AUV systems. It also showcases several joint localization and tracking solutions for AUVs. Lastly, it discusses future research directions and provides guidance on the design of future localization, tracking and formation schemes for AUVs. Representing a substantial contribution to nonlinear system theory, robotic control theory, and underwater acoustic communication system, this book will appeal to university researchers, scientists, engineers, and graduate students in control theory and control engineering who wish to learn about the core principles, methods, algorithms, and applications of AUVs. Moreover, the practical localization, tracking and formation schemes presented provide guidance on exploring the ocean. The book is intended for those with an understanding of nonlinear system theory, robotic control theory, and underwater acoustic communication systems.

Download or read book Formation Control and Fault Accommodation for a Team of Autonomous Underwater Vehicles written by Sahar Sedaghati and published by . This book was released on 2015 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this thesis is the development of efficient formation control and fault accommodation algorithms for a team of autonomous underwater vehicles (AUVs). The team of AUVs are capable of performing a wide range of deep water marine applications such as seabed mapping and surveying, oil and gas exploration and extraction, and oil and gas pipeline inspection. However, communication limitations and the presence of undesirable events such as component faults in any of the team members can prevent the whole team to achieve safe, reliable, and efficient performance while executing underwater mission tasks. In this regard, the semi-decentralized control scheme is developed to achieve trajectory tracking and formation keeping while requiring information exchange only among neighboring agents. To this end, model predictive control (MPC) technique and dynamic game theory are utilized to formulate and solve the formation control problem. Moreover, centralized and decentralized control schemes are developed to assess the performance of the proposed semi-decentralized control scheme in the simulation studies. The simulation results verify that the performance of the proposed semi-decentralized scheme is very close to the centralized scheme with lower control effort cost while it does not impose stringent communication requirements as in the centralized scheme. Moreover, the semi-decentralized active fault recovery scheme is developed to maintain a graceful degraded performance and to ensure that the team of autonomous underwater vehicles can satisfy mission objectives when an actuator fault occurs in any of the team members. In this regard, online fault information provided by fault detection and isolation (FDI) modules of each agent and its neighbors are incorporated to redesign the nominal controllers based on the MPC technique and dynamic game theory. Additionally, FDI imperfections such as fault estimation error and time delay are taken into account, and a performance index is derived to show the impact of FDI imperfections on the performance of team members. Moreover, centralized and decentralized active fault recovery schemes are developed to evaluate the performance of the proposed semi-decentralized recovery scheme through comparative simulation studies with various fault scenarios. The comparative simulation studies justify that the proposed semi-decentralized fault recovery scheme meets the design specifications even if the performance of the FDI module is not ideal.

Download or read book Fault Detection Isolation and Identification of Autonomous Underwater Vehicles Using Dynamic Neural Networks and Genetic Algorithms written by Shaghayegh Shahrokhi Tehrani and published by . This book was released on 2015 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this thesis is to propose and develop a fault detection, isolation and identification scheme based on dynamic neural networks (DNNs) and genetic algorithm (GA) for thrusters of the autonomous underwater vehicles (AUVs) which provide the force for performing the formation missions. In order to achieve the fault detection task, in this thesis two level of fault detection are proposed, I) Agent-level fault detection (ALFD) and II) Formation-level fault detection (FLFD). The proposed agent-level fault detection scheme includes a dynamic neural network which is trained with absolute measurements and states of each thruster in the AUV. The genetic algorithm is used in order to train the DNN. The results from simulations indicate that although the ALFD scheme can detect the high severity faults, for low severity faults the accuracy is not satisfy our expectations. Therefore, a formation-level fault detection scheme is developed. In the proposed formation-level fault detection scheme, a fault detection unit consist of two dynamic neural networks corresponding to its adjacent neighbors, is employed in each AUV to detect the fault in formation. Each DNN of the fault detection unit is trained with one relative and one absolute measurements. Similar to ALFD scheme, these two DNNs are trained with GA. The simulation results and confusion matrix analysis indicate that our proposed FLFD can detect both low severity and high severity faults with high level of accuracy compare to ALFD scheme. In order to indicate the type and severity of the occurred fault the agent-level and formation-level fault isolation and identification schemes are developed and their performances are compared. In the proposed fault isolation and identification schemes, two neural networks are employed for isolating the type of the fault in the thruster of the AUV and determining the severity of the occurred fault. In the fist step, a multi layer perceptron (MLP) neural network categorize the type of the fault into thruster blocking, flooded thruster and loss of effectiveness in rotor and in the next step a MLP neural network classify the severity into low, medium and high. The neural networks in fault isolation and identification schemes are trained based on genetic algorithm with various data sets which are obtained through different faulty operating condition of the AUV. The simulation results and the confusion matrix analysis indicate that the proposed formation-level fault isolation and identification schemes have a better performance comparing to agent-level schemes and they are capable of isolating and identifying the faults with high level of accuracy and precision.

Download or read book A Priori and On line Route Optimization for Unmanned Underwater Vehicles written by Brian A. Crimmel and published by . This book was released on 2012 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: The U.S. military considers Unmanned Underwater Vehicles (UUVs) a critical component of the future for two primary reasons - they are effective force multipliers and a significant risk-reducing agent. As the military's technology improves and UUVs become a reliable mission asset, the vehicle's ability to make intelligent decisions will be crucial to future operations. The thesis develops various algorithms to solve the UUV Mission-Planning Problem (UUVMPP), where the UUV must choose which tasks to perform in which sequence in a stochastic mission environment. The objective is to find the most profitable way to execute tasks with restrictions of total mission time, energy, time-restricted areas, and weather conditions. Since the UUV accumulates navigation error over time while maneuvering underwater, the UUV must occasionally halt operations to re-orient itself via a navigation fix. While a navigation fix takes time and increases the likelihood of exposing the vehicle's position to potential adversaries, a reduction in navigation error allows the UUV to perform tasks and navigate with a greater amount of certainty. The algorithms presented in this thesis successfully incorporate navigation fixes into the mission-planning process. The thesis considers Mixed-Integer Programming, Exact Dynamic Programming, and an Approximate Dynamic Programming technique known as Rollout to determine the optimal a priori route that meets operational constraints with a specified probability. The thesis then shows how these formulations can solve and re-solve the UUVMPP on-line. In particular, the Rollout Algorithm finds task route solutions on average 96% of the optimal solution a priori and 98% of the optimal solution on-line compared to exact algorithms; with a significant reduction in computation run time, the Rollout Algorithm permits the solving of increasingly complex mission scenarios.

Download or read book Distributed Fault Detection in Formation of Multi Agent Systems with Attack Impact Analysis written by Arefeh Amrollahi Biyooki and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous Underwater Vehicles (AUVs) are capable of performing a variety of deepwater marine applications as in multiple mobile robots and cooperative robot reconnaissance. Due to the environment that AUVs operate in, fault detection and isolation as well as the formation control of AUVs are more challenging than other Multi-Agent Systems (MASs). In this thesis, two main challenges are tackled. We first investigate the formation control and fault accommodation algorithms for AUVs in presence of abnormal events such as faults and communication attacks in any of the team members. These undesirable events can prevent the entire team to achieve a safe, reliable, and efficient performance while executing underwater mission tasks. For instance, AUVs may face unexpected actuator/sensor faults and the communication between AUVs can be compromised, and consequently make the entire multi-agent system vulnerable to cyber-attacks. Moreover, a possible deception attack on network system may have a negative impact on the environment and more importantly the national security. Furthermore, there are certain requirements for speed, position or depth of the AUV team. For this reason, we propose a distributed fault detection scheme that is able to detect and isolate faults in AUVs while maintaining their formation under security constraints. The effects of faults and communication attacks with a control theoretical perspective will be studied. Another contribution of this thesis is to study a state estimation problem for a linear dynamical system in presence of a Bias Injection Attack (BIA). For this purpose, a Kalman Filter (KF) is used, where we show that the impact of an attack can be analyzed as the solution of a quadratically constrained problem for which the exact solution can be found efficiently. We also introduce a lower bound for the attack impact in terms of the number of compromised actuators and a combination of sensors and actuators. The theoretical findings are accompanied by simulation results and numerical can study examples.

Download or read book Autonomous Underwater Vehicles written by Cynthia Mitchell and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gravity-gradient and magnetic-gradient inversion equations are combined to estimate the orientation and distance of an underwater object. The CKF algorithm based on EMMAF algorithm and Spherical-Radial is proposed and is applied to the fault diagnosis of slaver AUV in multi AUV collaborative positioning system. Simulation results are used to analyze the advantages and disadvantages of the three algorithms. This book looks at how a Service-Oriented Agent Architecture (SOAA) for marine robots is endowed with resilient capabilities in order to build a robust (fault-tolerant) vehicle control approach. Particular attention is paid to cognitive RCAs based on agent technologies and any other smart solution already applied or potentially applicable to UMVs. The book also presents current and future trends of RCAs for UMVs.

Download or read book Cooperative Control and Fault Recovery for Network of Heterogeneous Autonomous Underwater Vehicles written by Maria Enayat and published by . This book was released on 2017 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this thesis is to develop cooperative recovery control schemes for a team of heterogeneous autonomous underwater vehicles (AUV). The objective is to have the network of autonomous underwater vehicles follow a desired trajectory while agents maintain a desired formation. It is assumed that the model parameters associated with each vehicle is different although the order of the vehicles are the same. Three cooperative control schemes based on dynamic surface control (DSC) technique are developed. First, a DSC-based centralized scheme is presented in which there is a central controller that has access to information of all agents at the same time and designs the optimal solution for this cooperative problem. This scheme is used as a benchmark to evaluate the performance of other schemes developed in this thesis. Second, a DSC-based decentralized scheme is presented in which each agent designs its controller based on only its information and the information of its desired trajectory. In this scheme, there is no information exchange among the agents in the team. This scheme is also developed for the purpose of comparative studies. Third, two different semi-decentralized or distributed schemes for the network of heterogeneous autonomous underwater vehicles are proposed. These schemes are a synthesis of a consensus-based algorithm and the dynamic surface control technique with the difference that in one of them the desired trajectories of agents are used in the consensus algorithm while in the other the actual states of the agents are used. In the former scheme, the agents communicate their desired relative distances with the agents within their set of nearest neighbors and each agent determines its own control trajectory. In this semi-decentralized scheme, the velocity measurements of the virtual leader and all the followers are not required to reach the consensus formation. However, in the latter, agents communicate their relative distances and velocities with the agents within their set of nearest neighbors. In both semi-decentralized schemes only a subset of agents has access to information of a virtual leader. The comparative studies between these two semi-decentralized schemes are provided which show the superiority of the former semi-decentralized scheme over latter. Furthermore, to evaluate the efficiency of the proposed DSC-based semi-decentralized scheme with consensus algorithm using desired trajectories, a comparative study is performed between this scheme and three cooperative schemes of model-dependent coordinated tracking algorithm, namely the centralized, decentralized, and semi-decentralized schemes. Given that the dynamics of autonomous underwater vehicles are inevitably subjected to system faults, and in particular the actuator faults, to improve the performance of the network of agents, active fault-tolerant control strategies corresponding to the three developed schemes are also designed to recover the team from the loss-of-effectiveness in the actuators and to ensure that the closed-loop signals remain bounded and the team of heterogeneous autonomous underwater vehicles satisfy the overall design specifications and requirements. The results of this research can potentially be used in various marine applications such as underwater oil and gas pipeline inspection and repairing, monitoring oil and gas pipelines, detecting and preventing any oil and gas leakages. However, the applications of the proposed cooperative control and its fault-tolerant scheme are not limited to underwater formation path-tracking and can be applied to any other multi-vehicle systems that are characterized by Euler-Lagrange equations.

Download or read book Undersea Vehicles and National Needs written by Committee on Undersea Vehicles and National Needs and published by National Academies Press. This book was released on 1996-12-03 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: The United States faces decisions requiring information about the oceans in vastly expanded scales of time and space and from oceanic sectors not accessible with the suite of tools now used by scientists and engineers. Advances in guidance and control, communications, sensors, and other technologies for undersea vehicles can provide an opportunity to understand the oceans' influence on the energy and chemical balance that sustains humankind and to manage and deliver resources from and beneath the sea. This book assesses the state of undersea vehicle technology and opportunities for vehicle applications in science and industry. It provides guidance about vehicle subsystem development priorities and describes how national research can be focused most effectively.

Download or read book Fault Detection and Isolation in a Networked Multi vehicle Unmanned System written by Nader Meskin and published by . This book was released on 2008 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development and Testing of Navigation Algorithms for Autonomous Underwater Vehicles written by Francesco Fanelli and published by Springer. This book was released on 2019-06-20 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on pose estimation algorithms for Autonomous Underwater Vehicles (AUVs). After introducing readers to the state of the art, it describes a joint endeavor involving attitude and position estimation, and details the development of a nonlinear attitude observer that employs inertial and magnetic field data and is suitable for underwater use. In turn, it shows how the estimated attitude constitutes an essential type of input for UKF-based position estimators that combine position, depth, and velocity measurements. The book discusses the possibility of including real-time estimates of sea currents in the developed estimators, and highlights simulations that combine real-world navigation data and experimental test campaigns to evaluate the performance of the resulting solutions. In addition to proposing novel algorithms for estimating the attitudes and positions of AUVs using low-cost sensors and taking into account magnetic disturbances and ocean currents, the book provides readers with extensive information and a source of inspiration for the further development and testing of navigation algorithms for AUVs.

Download or read book Precision Control and Maneuvering of the Phoenix Autonomous Underwater Vehicle for Entering a Recovery Tube written by Duane T. Davis and published by . This book was released on 1996-09-01 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of range limitations imposed by speed and power supplies, covert launch and recovery of Autonomous Underwater Vehicles (AUVs) near the operating area will be required for their use in many military applications. This thesis documents the implementation of precision control and planning facilities on the Phoenix AUV that will be required to support recovery in a small tube and provides a preliminary study of issues involved with AUV recovery by submarines. Implementation involves the development of low-level behaviors for sonar and vehicle control, mid-level tactics for recovery planning, and a mission planning system for translating high-level goals into an executable mission. Sonar behaviors consist of modes for locating and tracking objects, while vehicle control behaviors provide the ability to drive to and maintain a position relative to a tracked object. Finally, a mission-planning system allowing graphical specification of mission objectives and recovery parameters is implemented. Results of underwater virtual world and in-water testing show that precise AUV control based on sonar data and its use by higher-level tactics to plan and control recovery. Additionally, the mission-planning expert system has been shown to reduce mission planning time by approximately two thirds and results in missions with fewer logical and programming errors than manually generated missions.