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The demand for automation in modern society has been increasing steadily during the last few decades. Robotic systems have played an important role in automation that includes manufacturing, assembly, and biotechnology to name a few. In addition, there is a growing need for unmanned operation in different service and research sectors such as search and rescue, nuclear waste clean up, mining, planetary exploration and others. Such complex applications increase the possibility of system faults that are characterized by critical and unpredictable changes in the system dynamics. The consequences of system faults can be extremely serious in terms of not only economic loss, but also adverse environmental impact and even loss of human lives. This book focuses on model based fault detection and isolation for robotic systems. The methodology presented in this book allows the robotic system to self-diagnose its faults so that catastrophic consequences can be averted. The method is both robust and practical and therefore has the potential to be implemented in the future robotic systems.
Robust Nonlinear Fault Detection and Isolation of Robotic System
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