Camps Echevarría, Lídice.
Fault Diagnosis Inverse Problems: Solution with Metaheuristics [electronic resource] / by Lídice Camps Echevarría, Orestes Llanes Santiago, Haroldo Fraga de Campos Velho, Antônio José da Silva Neto. - 1st ed. 2019. - XVIII, 167 p. 68 illus., 52 illus. in color. online resource. - Studies in Computational Intelligence, 763 1860-9503 ; . - Studies in Computational Intelligence, 763 .
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.
9783319899787
10.1007/978-3-319-89978-7 doi
Mathematical models.
Mathematics—Data processing.
Mathematical optimization.
Calculus of variations.
Mathematical Modeling and Industrial Mathematics.
Computational Science and Engineering.
Calculus of Variations and Optimization.
TA342-343
003.3
Fault Diagnosis Inverse Problems: Solution with Metaheuristics [electronic resource] / by Lídice Camps Echevarría, Orestes Llanes Santiago, Haroldo Fraga de Campos Velho, Antônio José da Silva Neto. - 1st ed. 2019. - XVIII, 167 p. 68 illus., 52 illus. in color. online resource. - Studies in Computational Intelligence, 763 1860-9503 ; . - Studies in Computational Intelligence, 763 .
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.
9783319899787
10.1007/978-3-319-89978-7 doi
Mathematical models.
Mathematics—Data processing.
Mathematical optimization.
Calculus of variations.
Mathematical Modeling and Industrial Mathematics.
Computational Science and Engineering.
Calculus of Variations and Optimization.
TA342-343
003.3