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“Fault Detection and Isolation: Multi-Vehicle Unmanned System” deals with the design and development of fault detection and isolation algorithms for unmanned vehicles such as spacecraft, aerial drones and other related vehicles. Addressing fault detection and isolation is a key step towards designing autonomous, fault-tolerant cooperative control of networks of unmanned systems. This book proposes a solution based on a geometric approach, and presents new theoretical findings for fault detection and isolation in Markovian jump systems. Also discussed are the effects of large environmental disturbances, as well as communication channels, on unmanned systems. The book proposes novel solutions to difficulties like robustness issues, as well as communication channel anomalies. “Fault Detection and Isolation: Multi-Vehicle Unmanned System” is an ideal book for researchers and engineers working in the fields of fault detection, as well as networks of unmanned vehicles.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Recent years have witnessed a strong interest and intensive research activities in the area of networked autonomous unmanned vehicles, such as spacecraft formation flight, unmanned aerial vehicles, autonomous underwater vehicles, automated highway systems and multiple mobile robots. The envisaged networked architecture can provide surpassing performance capabilities and enhanced reliability; however, it requires extending the traditional theories of control, estimation, and Fault Detection and Isolation (FDI). Among the many challenges for these systems is development of autonomous cooperative control and estimation strategies that can maintain the group behavior and mission performance in presence of undesirable events such as failures and faults in the vehicles. In order to achieve this goal, the team should have the capability to detect and isolate vehicles faults and reconfigure the cooperative control algorithms to compensate for them. The main objective of this book is to explore the fault detection and isolation issues in networked multi-vehicle unmanned systems.
Nader Meskin, Khashayar Khorasani

Chapter 2. Geometric Approach to the Problem of Fault Detection and Isolation (FDI)

In this chapter, we briefly review a structured fault detection and isolation problem (SFDIP) for both linear and nonlinear systems based on geometric approaches that are developed in [120] and [154].
Nader Meskin, Khashayar Khorasani

Chapter 3. FDI in a Network of Unmanned Vehicles: Ideal Communication Channels

In this chapter, we address the problem of actuator fault detection and isolation of a network of unmanned vehicles corresponding to three different architectures, namely centralized, decentralized, and semi-decentralized. It is shown that the fault signatures in a network of unmanned vehicles with relative state measurements are dependent and the overall system is overactuated. This motivates us to investigate the development, design, and analysis of a fault detection and isolation (FDI) scheme for both linear and nonlinear systems with dependent fault signatures. Earlier versions of the work presented in this chapter have partially appeared in [127, 128, 129, 131].
Nader Meskin, Khashayar Khorasani

Chapter 4. A Robust FDI Scheme with a Disturbance Decoupling Property

In this chapter, the actuator fault detection and isolation problem for a network of unmanned vehicles subject to large input disturbances is considered. One of the main challenges in the design of FDI algorithms is to distinguish the effects of disturbances from faults and develop a robust FDI scheme without compromising the detection of incipient faults in the vehicles. In unmanned vehicles such as UAV’s, this problem is more challenging due to the small size feature and higher sensitivity of these vehicles to disturbances such as wind gust. In this chapter, a robust FDI scheme is designed by developing a hybrid fault detection and isolation strategy for both linear and nonlinear systems that are subject to large environmental disturbances. The work presented in this chapter has partially appeared in [136, 138, 135].
Nader Meskin, Khashayar Khorasani

Chapter 5. Compensating for Communication Channels Effects in the FDI Problem

This chapter deals with the problem of fault detection and isolation in a network of unmanned vehicles when there exist imperfect communication channels among the vehicles. A discrete-time communication link having a stochastic packet dropping effect is considered based on the Gilbert-Elliott model [62, 78] which is known as the packet erasure channel model. It is shown that the entire network can be modeled as a discrete-time Markovian Jump System (MJS). This problem is then treated in the general framework of Markovian jump systems. This motivates us to develop a geometric FDI framework for both continuous-time and discrete-time Markovian jump systems and apply the developed scheme to FDI of a network of unmanned vehicles in presence of imperfect communication channels. The work presented in this chapter has partially appeared in [130, 137, 133, 134, 132].
Nader Meskin, Khashayar Khorasani

Chapter 6. Perspectives and Future Directions of Research

In this book, we have been interested in design and analysis of fault detection and isolation (FDI) strategies for networked multi-vehicle unmanned systems. This problem is timely and important due to the fact that one of the main challenges in these systems is developing an autonomous cooperative control solution that can maintain the group or team behavior and mission performance in presence of undesirable events such as faults in vehicles. In order to have an autonomous network of unmanned vehicles, fault detection and isolation schemes should be developed that are capable of detecting and isolating faults in the vehicles. The approach and framework that is proposed and presented here is based on geometric FDI. We have formulated and introduced several problems within the domain of multi-vehicle systems and obtained some very novel results.
Nader Meskin, Khashayar Khorasani

Backmatter

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