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This book presents a methodology based on inverse problems for use
in solutions for fault diagnosis in control systems, combining
tools from mathematics, physics, computational and mathematical
modeling, optimization and computational intelligence. This
methodology, known as fault diagnosis - inverse problem methodology
or FD-IPM, unifies the results of several years of work of the
authors in the fields of fault detection and isolation (FDI),
inverse problems and optimization. The book clearly and
systematically presents the main ideas, concepts and results
obtained in recent years. By formulating fault diagnosis as an
inverse problem, and by solving it using metaheuristics, the
authors offer researchers and students a fresh, interdisciplinary
perspective for problem solving in these fields. Graduate courses
in engineering, applied mathematics and computing also benefit from
this work.
This book presents a methodology based on inverse problems for use
in solutions for fault diagnosis in control systems, combining
tools from mathematics, physics, computational and mathematical
modeling, optimization and computational intelligence. This
methodology, known as fault diagnosis - inverse problem methodology
or FD-IPM, unifies the results of several years of work of the
authors in the fields of fault detection and isolation (FDI),
inverse problems and optimization. The book clearly and
systematically presents the main ideas, concepts and results
obtained in recent years. By formulating fault diagnosis as an
inverse problem, and by solving it using metaheuristics, the
authors offer researchers and students a fresh, interdisciplinary
perspective for problem solving in these fields. Graduate courses
in engineering, applied mathematics and computing also benefit from
this work.
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