Fault diagnosis inverse problems: solution with metaheuristics
The book is written by a group of authors, all of them well-known for their research works in the field of model based fault diagnosis and inverse problems, metaheuristic and optimization problems. The book starts on a very elementary level, by introducing information about model based fault diagnosis and inverse problems. In Chapter 2 presents and formalizes fault diagnosis as an inverse problem as as the new methodology for fault diagnosis: fault diagnosis -- inverse problem methodology. The three benchmark problems used here: DC motor, inverted pendulum system and two tanks system. In Chapter 3 makes an introduction to metaheuristics for optimization. This Chapter also presents two new metaheuristics: particle swam optimization with memory and differential evolution with particle collision. Chapter 4 presents the application of fault diagnosis -- inverse problem methodology to the three benchmark problems considerer. Appendices A and B show the Matlab codes for the algorithm of the new metaheuristics differential evolution with particle collision and particle swarm optimization with memory, respectively. The book is complete, eminently readable, and is accessible to novices and experts working in the above-mentioned fields.
scientific article; zbMATH DE number 6898570