Fault Diagnosis and energy efficiency has become an issue of primary importance in process automation as it provides the pre-requisites for fault tolerance, reliability or security, which constitutes fundamental design features in complex engineering systems. The goal of this project is design of novel, sophisticated FDI algorithms and their application to complex systems with a huge number of sensors and actuators. Characteristic examples of such systems are power plants and biofuels factories that usually involve more than a hundred closed control loops whereas each of them contains at least one actuator and two or more sensors. Having in mind the complexity of such systems, significance of safety aspects and the financial consequences of system failures, the development of the efficient and reliable techniques for failure detection and isolation becomes of paramount importance. The aim of this project is to develop and test new and improved FDI techniques tailored to the complex applicative scenario of power systems. The research within the proposed project will be devoted to the following directions: 1) New state estimation schemes for instrument fault detection and robust fault diagnosis using unknown input observers; 2) Advanced intelligent algorithms for fault and leakage detection in local electro-mechanical devices within the power plants and biofuels factories. These algorithms should be based either on statistical pattern recognition or soft-computing techniques, 3) Design of novel analytical techniques for multi-sensor signal processing in order to detect existence and localization of failures in a distributed sensors networks; 4) Integration considerations and system implementation in architectures and validation on a real plant.