Nadia Magnenat-Thalmann; Constantine Stephanidis; Enhua Wu; Daniel Thalmann; Bin Sheng; Jinman Kim; George Papagiannakis Springer Nature Switzerland AG (2020) Pehmeäkantinen kirja
Benli Huang; Hai Ying; Pengyuan Yang; Xiaoru Wang; Sheng Gu; Zhigang Zhang; Zhixia Zhuang; Zhenhua Sun; Bing Li Royal Society of Chemistry (2000) Kovakantinen kirja
This book investigates in detail model-based fault diagnosis methods, including observer-based residual generation, residual evaluation based on threshold computation, observer-based fault isolation strategies, observer-based fault estimation, Kalman filter-based fault diagnosis methods, and parity space approach. Studies on model-based fault diagnosis have attracted engineers and scientists from various disciplines, such as electrical, aerospace, mechanical, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of state-space approach. The methods introduced in the book are systemic and easy to follow. The book is intended for undergraduate and graduate students who are interested in fault diagnosis and state estimation, researchers investigating fault diagnosis and fault-tolerant control, and control system design engineers working on safety-critical systems.