Chapter 01- Model-based Fault Diagnosis and Inverse Problems -- Chapter 02- Fault Diagnosis Inverse Problems -- Chapter 03- Metaheuristics for Optimization Problems -- Chapter 04- Applications of the Fault Diagnosis: Inverse Problem Methodology to Benchmark Problems -- Chapter 05- Final Remarks -- Appendix A- Implementation in Matlab of Differential Evolution with Particle Collision (DEwPC) -- Appendix B- Implementation in Mathlab of Particle Swarm Optimization with Memory (PSO-M) -- References.

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.