PhD Oral Exam - Jin Li, Mechanical Engineering

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

The deployment of Cyber-Physical System (CPS) in smart grid infrastructures significantly enhances operational capabilities but simultaneously introduces vulnerabilities susceptible to cyber-attacks and physical faults. This doctoral research comprehensively addresses these critical challenges by proposing robust methodologies for detection, diagnosis, fault-tolerant and cyber-resilient control within the smart grid framework.

Initially, the research underscores the necessity for advanced modeling techniques that encapsulate both physical characteristics and networked interactions inherent to CPS. It presents a hybrid modeling approach, integrating network science and detailed physical characterization, effectively capturing the dynamics and interdependencies within smart grid systems. This modeling foundation is pivotal for accurate diagnosis and efficient mitigation strategies in complex CPS environments.

The study investigates common physical faults in inverter-based smart grids, particularly inverter malfunctions, together with major cyber threats including False Data Injection (FDI) attacks and Denial-of-Service (DoS) attacks. The adverse impacts of both physical faults and cyber disturbances on system stability and operational continuity are systematically analyzed. To enhance reliability, this research primarily develops and validates observer-based fault diagnosis methodologies for physical inverter faults. Novel techniques, particularly Interval Sliding Mode Observers and Super-Twisting Algorithms (STA), are rigorously designed to achieve accurate fault detection and diagnosis while maintaining robustness under cyber anomalies. In addition, an Adaptive Unscented Kalman Filter (AUKF) is implemented to improve state estimation accuracy under FDI attacks, further strengthening resilience against network-induced disturbances.

To fortify smart grid resilience, the research introduces a distributed resilient control framework that operates effectively even under simultaneous sensor and controller cyber-attacks. Unlike traditional methodologies, this control framework integrates attack compensation directly into the control strategies, thus eliminating reliance on explicit detection mechanisms. Through rigorous Lyapunov-based stability analysis, it is theoretically established that this approach guarantees global asymptotic stability and maintains robust performance under sustained cyber threats.

Extensive validation via MATLAB/Simulink-based simulations across various scenarios, including normal operations, intentional fault injections, and orchestrated cyber-attacks, demonstrate the effectiveness of the proposed methodologies in preserving system stability, reliability, and efficiency. Results confirm that the developed techniques significantly outperform traditional control strategies in mitigating the adverse effects of both cyber and physical system.

The doctoral work achieves advances in observer-based fault detection, scalable Distributed State Estimation (DSE) frameworks, observer based fault-tolerant control, and real-time cyber-resilient control strategies. The practical applications of these innovations extend to large-scale, geographically dispersed smart grid implementations, presenting significant improvements in system security, reliability, and operational continuity.

Furthermore, this research provides a foundation for future explorations into CPS security, advocating for the integration of emerging technologies such as artificial intelligence, blockchain, and digital twins to further strengthen smart grid systems. By bridging theoretical developments and practical applications, this study significantly contributes to the evolution of fault-tolerant control, and resilient control of smart grid infrastructures, with substantial implications for both academic research and industrial deployment.