Safety in industrial process and production plants is a concern of rising importance but because the control devices which are w exploited to improve the performance of industrial processes include both sophisticated digital system design techniques and complex hardware, there is a higher probability of failure. Control systems must include automatic supervision of closed-loop operation to detect and isolate malfunctions quickly. A promising method for solving this problem is analytical redundancy , in which residual signals are obtained and an accurate model of the system mimics real process behaviour. If a fault occurs, the residual signal is used to diagse and isolate the malfunction. This book focuses on model identification oriented to the analytical approach of fault diagsis and identification covering: choice of model structure; parameter identification; residual generation; and fault diagsis and isolation. Sample case studies are used to demonstrate the application of these techniques.