[PDF] A Hybrid Nonlinear Model Predictive Control And Recurrent Neural Networks For Fault Tolerant Control Of An Autonomous Underwater Vehicle eBook

Author : Mahsa Khoshab
Publisher :
Page : 227 pages
File Size : 14,67 MB
Release : 2018
Category :
ISBN :

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The operation of Autonomous Unmanned Vehicles (AUVs) that is used for environment protection, risk evaluation and plan determination for emergency, are among the most important and challenging problems. An area that has received much attention for use of AUVs is in underwater applications where much work remains to be done to equip AUVs with systems to steer them accurately and reliably in harsh marine environments. Design of control strategies for AUVs is very challenging as compared to other systems due to their operational environment (ocean). Particularly when hydrodynamic parameters uncertainties are to be integrated into both the controller design as well as AUVs nonlinear dynamics. On the other hand, AUVs like all other mechanical systems are prone to faults. Dealing effectively with faulty situations for mechanical systems is an important consideration since faults can result in abnormal operation or even a failure. Hence, fault tolerant and fault-accommodating methods in the controller design are among active research topics for maintaining the reliability of complex AUV control systems. The objective of this thesis is to develop a nonlinear Model Predictive Control (MPC) that requires solving an online Quadratic Programming (QP) problem by using a Recurrent Neural Network (RNN). Also, an Extended Kalman Filter (EKF) is integrated with the developed scheme to provide the MPC algorithm with the system states estimates as well as a nonlinear prediction. This hybrid control approach utilizes both the mathematical model of the system as well as the adaptive nature of the intelligent technique through neural networks. The reason behind the selection of MPC is to benefit from its main capability in optimization within the current time slots while taking future time slots into consideration. The proposed control method is integrated with EKF which is an appropriate method for state estimation and data reconciliation of nonlinear systems. In order to address the high performance runtime cost of solving the MPC problem (formulated as a quadratic programming problem), an RNN is developed that has a low model complexity as well as good performance in real-time implementation. The proposed method is first developed to control an AUV following a desired trajectory. Since the problem of trajectory tracking and path following of AUVs exhibit nonlinear behavior, the effectiveness of the developed MPC-RNN algorithm is studied in comparison with two other control system methods, namely the linear MPC using Kalman Filter (KF) and the conventional nonlinear MPC using the EKF. In order to guarantee the fault-tolerant features of our proposed control method when faced with severe actuator faults, the developed MPC-RNN scheme is integrated with a dual Extended Kalman Filter that is used for a combined estimation of AUV states and parameters. The actuator faults are defined as the system parameters that are to be estimated online by the dual-EKF. Therefore, the developed Active Fault-Tolerant Control (AFTC) strategy is then applied to an AUV faced with loss of effectiveness (LOE) actuator fault scenarios while following a trajectory. Analysis and discussions regarding the comparison of the proposed AFTC method with Fault-Tolerant Nonlinear Model Predictive Control (FTNMPC) algorithm are presented in this work. The proposed approach to AFTC exploits the advantages of the MPC-RNN algorithm properties as well as accounting explicitly for severe control actuator faults in the nonlinear AUV model with uncertainties that are formulated by the MPC.

Author : Yang Shi
Publisher : Springer Nature
Page : 210 pages
File Size : 42,95 MB
Release : 2023-02-13
Category : Technology & Engineering
ISBN : 3031193547

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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.

Author : Zhiyong Chen
Publisher : Springer
Page : 473 pages
File Size : 31,23 MB
Release : 2018-08-03
Category : Computers
ISBN : 3319975897

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The two volume set LNAI 10984 and LNAI 10985 constitutes the refereed proceedings of the 11th International Conference on Intelligent Robotics and Applications, ICIRA 2018, held in Newcastle, NSW, Australia, in August 2018. The 81 papers presented in the two volumes were carefully reviewed and selected from 129 submissions. The papers in the first volume of the set are organized in topical sections on multi-agent systems and distributed control; human-machine interaction; rehabilitation robotics; sensors and actuators; and industrial robot and robot manufacturing. The papers in the second volume of the set are organized in topical sections on robot grasping and control; mobile robotics and path planning; robotic vision, recognition and reconstruction; and robot intelligence and learning.

Author : Jing Yan
Publisher : Springer Nature
Page : 222 pages
File Size : 35,93 MB
Release : 2021-11-01
Category : Technology & Engineering
ISBN : 9811660964

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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.

Author : Chao Shen
Publisher :
Page : pages
File Size : 16,29 MB
Release : 2018
Category :
ISBN :

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The increasing reliance on oceans, rivers and waterways in a spectrum of human activities have demonstrated the large demand for advanced marine technologies that facilitate multifarious in-water services and tasks. The autonomous underwater vehicle (AUV) is a representative marine technology which has been contributing continuously to many ocean-related fields. An elaborate control system is essential to AUVs. However, AUVs present difficult control system design problems due to their nonlinear dynamics, the unpredictable environment and the poor knowledge about the hydrodynamic coupling of the vehicle degrees of freedom. When designing the motion controller, the practical constraints on the AUV system such as limited perceiving, computing and actuating capabilities should also be respected. The model predictive control (MPC) is an advanced control technology that leverages optimization to calculate the control command. Thanks to the optimization nature, MPC can conveniently handle the complex nonlinearity in system dynamics as well as the state and control constraints. MPC takes the receding horizon control paradigm which gains satisfactory robustness against model uncertainties and external disturbances. Therefore, MPC is an ideal candidate for solving the AUV motion control problems. On the other hand, since the optimization is solved by iterative numerical algorithms, the obtained control signal is an implicit function of the system state, which complicates the characterization of the closed-loop properties. Moreover, the nonlinear system dynamics makes the online optimization nonlinear programming (NLP) problems. The high computational complexity may cause an issue on the real-time control for embedded platforms with limited computing resources. In order to push the advanced MPC technology towards real-world AUV applications, this PhD dissertation is concerned with fundamental AUV motion control problems and attempts to address the aforementioned challenges and provide novel solutions. This dissertation proceeds with Chapter 1 by providing state-of-the-art introductions to related research areas. The mathematical model used for the AUV motion control is elaborated in Chapter 2. In Chapter 3, we consider the AUV navigation and control problem in constrained workspace. A unified receding horizon optimization framework consisting of the dynamic path planning and the nonlinear model predictive control (NMPC) tracking control is developed. Although the NMPC tracking controller well accommodates the practical constraints on the AUV system, it presents a brand new design philosophy compared with the existing control systems that are implemented on real AUVs. Since the existing AUV control systems are reliable controllers, AUV practitioners tend not to fully replace them but to improve the control performance by adding features. By considering this, in Chapter 4, we develop the Lyapunov-based model predictive control (LMPC) scheme which builds on the existing AUV control system and invoke online optimization to improve the control performance. Chapter 5 focuses on the path following (PF) problem. Unlike the trajectory tracking control which equally emphasizes the spatial and temporal control objectives, the PF control often prioritizes the path convergence over the speed assignment. To incorporate this objective prioritization into the controller design, a novel multi-objective model predictive control (MOMPC) scheme is developed. While the MPC technique provides several salient features (e.g., optimality, constraints handling, objective prioritization, robustness, etc.), those features come at a price: a computational bottleneck is formed by the heavy burden of solving online optimizations in real time. To explicitly address this issue, in Chapter 6, the computational complexity of the MPC algorithms is particularly emphasized. Two novel strategies which potentially alleviate the computational burden of the MPC-based AUV tracking control are proposed. In Chapter 7, some conclusive remarks are provided and a few avenues for future research are identified.

Author : Gianluca Antonelli
Publisher : Springer
Page : 294 pages
File Size : 37,59 MB
Release : 2013-11-22
Category : Technology & Engineering
ISBN : 3319028774

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This book, now at the third edition, addresses the main control aspects in underwater manipulation tasks. The mathematical model with significant impact on the control strategy is discussed. The problem of controlling a 6-degrees-of-freedoms autonomous underwater vehicle is deeply investigated and a survey of fault detection/tolerant strategies for unmanned underwater vehicles is provided. Inverse kinematics, dynamic and interaction control for underwater vehicle-manipulator systems are then discussed. The code used to generate most of the numerical simulations is made available and briefly discussed.

Author : Sabiha Wadoo
Publisher : CRC Press
Page : 165 pages
File Size : 21,79 MB
Release : 2017-12-19
Category : Technology & Engineering
ISBN : 1439818320

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Underwater vehicles present some difficult and very particular control system design problems. These are often the result of nonlinear dynamics and uncertain models, as well as the presence of sometimes unforeseeable environmental disturbances that are difficult to measure or estimate. Autonomous Underwater Vehicles: Modeling, Control Design, and Simulation outlines a novel approach to help readers develop models to simulate feedback controllers for motion planning and design. The book combines useful information on both kinematic and dynamic nonlinear feedback control models, providing simulation results and other essential information, giving readers a truly unique and all-encompassing new perspective on design. Includes MATLAB® Simulations to Illustrate Concepts and Enhance Understanding Starting with an introductory overview, the book offers examples of underwater vehicle construction, exploring kinematic fundamentals, problem formulation, and controllability, among other key topics. Particularly valuable to researchers is the book’s detailed coverage of mathematical analysis as it applies to controllability, motion planning, feedback, modeling, and other concepts involved in nonlinear control design. Throughout, the authors reinforce the implicit goal in underwater vehicle design—to stabilize and make the vehicle follow a trajectory precisely. Fundamentally nonlinear in nature, the dynamics of AUVs present a difficult control system design problem which cannot be easily accommodated by traditional linear design methodologies. The results presented here can be extended to obtain advanced control strategies and design schemes not only for autonomous underwater vehicles but also for other similar problems in the area of nonlinear control.

Author : Lauren Alise Cooney
Publisher :
Page : 93 pages
File Size : 15,85 MB
Release : 2009
Category : Remote submersibles
ISBN :

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The Odyssey IV autonomous underwater vehicle (AUV) is the next generation of unmanned subsurface robots from the MIT Sea Grant AUV Laboratory. The Odyssey IV AUV has a novel propulsion system, which includes a pair of azimuthing thrusters for maneuvering in surge and heave. An analytical model was developed to describe the complex nonlinear vehicle dynamics, and experiments were performed to refine this model. The fluid dynamics of unsteady azimuthing marine propulsors are largely unstudied, especially for small vehicles like the Odyssey IV AUV. Experiments suggest that thrust developed by an azimuthing propulsor is dependent on the azimuth angle rate of change, and can substantially affect vehicle dynamics. A simple model capturing the effects of azimuthing on the thruster dynamics is developed, and is shown to improve behavior of the model.The use of azimuthing thrusters presents interesting problems and opportunities in maneuvering and control. Nonlinear model predictive control (MPC) is a technique that consists of the real-time optimization of a nonlinear dynamic system model, with the ability to handle constraints and nonlinearities. In this work, several variations of simulated and experimental MPC-based controllers are investigated. The primary challenge in applying nonlinear MPC to the Odyssey IV is solving the time intensive trajectory optimization problem online. Simulations suggest that MPC is able to capitalize on its knowledge of the system, allowing more aggressive trajectories than a traditional PID controller.

Author : Cynthia Mitchell
Publisher :
Page : 0 pages
File Size : 35,82 MB
Release : 2017
Category : Automated vehicles
ISBN : 9781536118193

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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.