Automatic control techniques have been widely employed in industry to increase efficiency and profitability of the processes. However, reliability on automation increases the susceptibility of the system to faults in major control equipment such as actuators and sensors. This realization has motivated design of frameworks for fault detection and isolation (FDI) and fault tolerant control (FTC). The success of these FDI and FTC mechanisms is contingent on their ability to handle complexities associated with process systems such as nonlinearity, uncertainty, high dimensionality and the resulting effects of the existence of complexity in system structure such as faults that cannot be isolated. Motivated by the above considerations, this thesis considers the problem of fault diagnosis and fault tolerant control for complex process systems. First, an FDI framework is designed that can detect and confine possible locations for faults that cannot be isolated. Next, the problem of simultaneous actuator and sensor fault diagnosis for nonlinear uncertain systems. The key idea is to design FDI filters in a way they account for the impact of uncertainty explicitly. This work then considers the problem of simultaneous fault diagnosis in nonlinear uncertain networked systems. FDI is achieved using a distributed architecture, comprised of a bank of local FDI (LFDI) schemes that communicate with each other. The efficacy of the proposed FDI methodologies is shown via application to a number of chemical process examples. Finally, an integrated framework is proposed for fault diagnosis and fault tolerant control of variable air volume (VAV) boxes, a common component of heating, ventilation and air conditioning (HVAC) systems as an industrial case study of complex systems. The advantages of the proposed framework are diagnosing multiple faults and handling faults in stuck dampers using a safe parking strategy with energy saving capability. / Thesis / Doctor of Philosophy (PhD) / Automation is the key to increase efficiency and profitability of the processes. However, as the level of automation increases, major control equipment are more prone to faults. Thus, fault detection and isolation (FDI) and fault tolerant control (FTC) frameworks are required for fault handling. Fault handling, however, can only be efficiently achieved if the designed FDI and FTC frameworks are able to deal with complexities arising in process systems such as nonlinearity, uncertainty, high dimensionality and the resulting effects of the existence of complexity in system structure such as faults that cannot be isolated. This motivates design of FDI and FTC frameworks for complex process systems. First, FDI frameworks are presented that can diagnose faults in the presence of complexities mentioned above. Then, an integrated framework is designed for diagnosing and handling faults of heating, ventilation and air conditioning (HVAC) systems as an industrial case study of complex process systems.