Guaranteeing a high system performance over a wide operating range is an
important issue surrounding the design of automatic control systems with
successively increasing complexity. As a key technology in the search
for a solution, advanced fault detection and identification (FDI) is
receiving considerable attention. This book introduces basic model-based
FDI schemes, advanced analysis and design algorithms, and mathematical
and control-theoretic tools.
This second edition of Model-Based Fault Diagnosis Techniques
contains:
- new material on fault isolation and identification and alarm
management;
- extended and revised treatment of systematic threshold determination
for systems with both deterministic unknown inputs and stochastic
noises;
- addition of the continuously-stirred tank heater as a representative
process-industrial benchmark; and
- enhanced discussion of residual evaluation which now deals with
stochastic processes.
Model-based Fault Diagnosis Techniques will interest academic
researchers working in fault identification and diagnosis and as a text
it is suitable for graduate students in a formal university-based course
or as a self-study aid for practising engineers working with automatic
control or mechatronic systems from backgrounds as diverse as chemical
process and power engineering.