Unknown Input Observer For Cyber-Physical Systems Subjected To Malicious Attacks

Cyber-Physical Systems (CPSs) consist of physical and computational components usually interconnected through the internet. This type of systems have found applications in robotic surgery, smart medical services, driverless cars, smart power grids as well as in modern homes and offices. For a CPS to function properly, a reliable and secure communications between the system physical and cyber elements is of utmost importance. Malicious attacks during control signals and output measurements transmission between the physical plant and the control center must be addressed, which is the main research problem studied in this thesis.

A novel robust observer was proposed to synthesize a combined controller-observer compensator for a class of CPSs with sparse malicious attacks and arbitrary disturbances. The compensator consists of a controller, a norm approximator, and an unknown input observer (UIO). The proposed observer was compared with a norm-based observer given in the literature to show its advantage. To further enhance the proposed observer's performance against arbitrary disturbances, design methods were given that use fictitious output measurements and error correcting code (ECC) approach. The design of the UIO was extended to a bank of UIOs in order to improve the observer's performance against sparse malicious attacks.

The proposed observer can be used in the design of UIO-based fault detection and isolation (FDI) algorithms as well as in the distributed fault-tolerant control of large-scale interconnected systems. The results of this thesis can be applied to the design of controller-observer compensators for CPSs with modeling uncertainties.