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Fault Diagnosis and Fault Tolerance for Mechatronic Systems: Recent Advances

Author : Fabrizio Caccavale
Publisher : Springer
Page : 199 pages
File Size : 26,39 MB
Release : 2003-09-05
Category : Technology & Engineering
ISBN : 3540457372

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This book will play a central role in ensuring safe and reliable behaviour of intelligent and autonomous systems. It collects some of the most recent results in fault diagnosis and fault tolerant systems, with particular emphasis on mechatronic systems.

A Closer Look at Fault-Tolerant Control

Author : Jeremy M. Hutton
Publisher :
Page : 348 pages
File Size : 44,21 MB
Release : 2020
Category : Technology & Engineering
ISBN : 9781536175295

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"A Closer Look at Fault-Tolerant Control first presents the application of a fault tolerant control system on distillation processes, with automatic actuator faults containment capabilities and an atmospheric crude distillation unit. Following this, model-based fault-tolerant control and fault accommodation algorithms are presented for two challenging classes of distributed systems: a spatially distributed system that can be decomposed into interconnected subsystems, and a distributed parameter system where the system state is distributed over a continuous range of space. The authors present recent research on fault-tolerant control systems for unmanned aerial systems, particularly for multirotor-type vehicles commonly known as drones. An overview of tools for the analysis of the fundamental properties of an automated system is provided, allowing for any inherent redundancy in the controlled process to be utilised to maintain availability. Additionally, a reconfigurable fault-tolerant flight control system is proposed to combat sensor/actuator faults for autonomous underwater vehicles. The reconfigurable design and operation of complex systems is addressed, with emphasis on autonomous systems, building upon concepts of autonomy, incipient failure diagnosis and prognosis algorithms. The authors present a fault detection filter for induction motors speed as a class of nonlinear system in networked control systems subject to induced time delays. The multi-model approach for the modeling of induction motors is described using a set of linear models. In the concluding study, the construction of an induction motor is presented, and a review of induction motor failures is discussed"--

Fault-Tolerant Design and Control of Automated Vehicles and Processes

Author : Ralf Stetter
Publisher : Springer
Page : 207 pages
File Size : 41,19 MB
Release : 2019-02-14
Category : Technology & Engineering
ISBN : 3030128466

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This book summarizes strategies, methods, algorithms, frameworks and systems for the fault-tolerant design and control of automated vehicles and processes. Intelligent systems may be able to accommodate inevitable faults, but this ability requires targeted design processes and advanced control systems. This book explains the respective elements involved in automated vehicles and processes. It provides detailed descriptions of fault-tolerant design, not offered in the existent scientific literature. With regard to fault-tolerant control, the focus is on innovative methods, which can accommodate not only uncertainties, but also shared and flexible redundant elements. The book is intended to present a concise guide for researchers in the field of fault-tolerant design and control, and to provide concrete insights for design and control engineers working in the field of automated vehicles and processes.

Fault-tolerant Synchronization of Autonomous Underwater Vehicles

Author : Faegheh Amirarfaei
Publisher :
Page : 210 pages
File Size : 35,61 MB
Release : 2016
Category :
ISBN :

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The main objective of this thesis is to develop a fault-tolerant and reconfigurable synchronization scheme based on model-based control protocols for stern and sail hydroplanes that are employed as actuators in the attitude control subsystem (ACS) of an autonomous underwater vehicle (AUV). In this thesis two control approaches are considered for synchronization, namely i) state feedback synchronization, and ii) output feedback synchronization. Both problems are tackled by proposing a passive control approach as well as an active reconfiguration (re-designing the control gains). For the ?state feedback? synchronization scheme, to achieve consensus the relative/absolute measurements of the AUV’s states (position and attitude) are available. The states of a longitudinal model of an AUV are mainly heave, pitch, and their associated rates. For the state feedback problem we employ a static protocol, and it is shown that the multi-agent system will synchronize in the stochastic mean square sense in the presence of measurement noise. However, the resulting performance index defined as the accumulated sum of variations of control inputs and synchronization errors is high. To deal with this problem, Kalman filtering is used for states estimation that are used in synchronization protocol. Moreover, the e�ffects of parameter uncertainty of the agent’s dynamics are also investigated through simulation results. By employing the static protocol it is demonstrated that when a loss of e�ffectiveness (LOE) or float fault occurs the synchronization can still be achieved under some conditions. Finally, one of the main problems that is tackled in the state feedback scenario is our proposed proportional-integral (PI) control methodology to deal with the lock in place (LIP) fault. It is shown that if the LIP fault occurs, by employing a PI protocol the synchronization could still be achieved. Finally, our proposed dynamic synchronization protocol methodology is applied given that the fault (LOE/float) severity is known. Since after a fault occurrence the agents become heterogeneous, employing the dynamic scheme makes the task of reconfiguration (redesigning the gains) more e�ffective. For the ?output feedback? synchronization approach, to achieve consensus relative/absolute measurements of the AUV’s states except the pitch rate are available. For the output feedback problem a dynamic protocol through a Luenberger observer is first employed for state estimation and the synchronization achievement is demonstrated. Then, a system under state and measurement noise is considered, and it is shown that by employing a Kalman filter for the state estimation; the multi-agent system will synchronize in the stochastic mean square sense. Furthermore, by employing the static protocol, it is shown that when a LOE/float fault occurs the synchronization is still achieved under certain conditions. Finally, one of the main problems that is tackled in the output feedback scenario is our proposed dynamic controller methodology. The results of this scheme are compared with another approach that exploits both dynamic controller and dynamic observer. The former approach has less computational e�ort and results in more a robust control with respect to the actuator fault. The reason is that the later method employs an observer that uses the control input matrix information. When fault occurs, this information will not be correct any more. However, if there is a need to redesign the synchronization gains under faulty scenario, the later methodology is preferred. The reason is that the former approach becomes complicated when there is a fault even though its severity is known. In this thesis, fault-tolerant synchronization of autonomous underwater vehicles is considered. In the first chapter a brief introduction on the motivation, problem definition, objectives and the methodologies that are used in the dissertation are discussed. A literature review on research dedicated to synchronization, fault diagnosis, and fault-tolerant control is provided. In Chapter 2, a through literature review on unmanned underwater vehicles is covered. It also comprises a comprehensive background information and definitions including algebraic graph theory, matrix theory, and fault modeling. In the problem statement, the two main problems in this thesis, namely state feedback synchronization and output feedback synchronization are discussed. Chapters 3 and 4 will cover these two problems, their solutions, and the corresponding simulation results that are provided. Finally, Chapter 5 includes a discussion of conclusions and future work.

Advanced Model Predictive Control for Autonomous Marine Vehicles

Author : Yang Shi
Publisher : Springer Nature
Page : 210 pages
File Size : 48,46 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.

A Hybrid Nonlinear Model Predictive Control and Recurrent Neural Networks for Fault-Tolerant Control of an Autonomous Underwater Vehicle

Author : Mahsa Khoshab
Publisher :
Page : 227 pages
File Size : 11,54 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.