(4fj) Emerging Sources of Non-Determinism: Modified Advanced Control Strategies for Cyberattack Detection, and Control-Based Strategies to Handle Quantum Noise

I have a strong interest in the development of advanced process control techniques for industrial setups influenced by cyber-physical systems ideology. The fundamental objective of process control is to establish safe process operating conditions while ensuring minimal economic loss. One of the fundamental challenges of achieving this objective is non-determinism from various sources that can create unexpected process behavior. A traditional goal in industrial process control is the rejection of environmental disturbances (time-varying process inputs not directly modified by the control system), measurement inaccuracies, and changes in plant dynamics. In recent decades, manufacturers have sought to push toward more efficient and digitalized operations within a framework called “smart manufacturing” or “Industry 4.0”. This framework involves an increased utilization of cyber-physical systems (CPS), which are process systems integrated with computers, communication, and networking components to improve process transparency and efficiency [1]. Additionally, it can be accompanied by new sources of uncertainty that require a thorough characterization of safety risks and mitigation techniques. One such source of non-determinism, introduced using automation and networked systems, is a cyberattack on control systems in which a malicious actor can manipulate sensor readings or actuator outputs and potentially mask their actions compromising human safety and process profits [2]. Furthermore, control being implemented on computing platforms is influenced by technological developments in the computing domain and must also be vetted from a cyber-physical systems safety perspective. For example, advances in quantum computation prompt whether this emerging computing paradigm (currently affected by hardware-related quantum “noise”) could ever be evaluated for control applications, or if the hardware limitation that introduces non-determinism as noise will render it unsafe for control applications. My doctoral thesis rigorously characterizes safety in manufacturing systems by addressing non-determinism from digitalization and emerging technologies, advancing control systems theory and practice.

My first thesis topic focused on developing cybersecure control strategies that theoretically guarantee safety and stability despite practical challenges such as cyberattacks, disturbances, and changing process dynamics [3]. The thesis addresses the control of nonlinear systems using an optimization-based model predictive control (Lyapunov-based Economic MPC) algorithm modified to also detect for cyberattacks. The research conducted thus far analyzes multiple detection strategies such as comparing state predictions/estimates to measurements or applying random updates to the control algorithm to detect cyberattacks on control elements such as process sensors and actuators [4,5]. However, these methods have seen limited success in terms of the duration for which theoretical guarantees hold, especially when the dynamics of the nonlinear process change with time [6]. To address this, a random string of binary numbers that alter the control input law applied at any sampling time during process operation is utilized to make the prediction of control actions challenging, consequently making it more difficult to develop stealthy cyberattacks [7]. This formulation gives us an opportunity to develop theoretical guarantees of safety until a cyberattack is detected.
My second thesis topic analyzes the safety of a linear control system using quantum computation with depolarizing error (a type of quantum noise) through simulation studies. The contributions of this work [8,9,10], include the application of a Quantum Fourier Transform-based algorithms to implement a linear closed-loop control action that forces the system to a stable state. As a faculty researcher, I will stabilize nonlinear systems with control algorithms run on noisy quantum devices in an industrial setup influenced and vetted from a CPS safety perspective.

Teaching Statement:

My teaching experience, while short, has helped me develop a number of new skills. I have taught multiple labs for an undergraduate materials engineering course over the last year, which has involved designing the presentation of multiple experiments outside of my background and laying the expectations of the course. In addition, I was also responsible for validating all the experimental setups, lab inventory, grading all reports, and providing final grades. This was a great opportunity to realize the expectations of being responsible for a course and helping shape the minds of future engineers. In order to develop a sustainable future for the course, I have been recording videos for not only the future students of the course but to help orient future instructors of the course.

The experience of mentoring an undergraduate student on not only a research topic based on Image based modeling but also understanding the student’s strength’s and aspirations to pursue a lucrative future in the industry and supporting this objective has strongly influenced my teaching philosophy. I believe in initially spending time individually with students to understand their thought process, and then designing individual work structures to help bring all students to a certain level of understanding before pursuing a common objective for a course/lab. In addition, it is my belief that addressing past work to be technically accurate is critical to developing technically sound engineers in the long term, as opposed to introducing as many new topics as possible within a certain time frame. In addition, providing multiple opportunities for students to display their understanding of the course, such as oral quizzes or discussion groups, could help reduce the pressures of a written test/exam and nurture the growth of more confident individuals. While I can teach introductory courses at the undergraduate level if necessary, I would feel most comfortable discussing topics steeped in mathematical analysis techniques and topics related to process engineering and control.

References:

[1] Lezzi, M., Lazoi, M., & Corallo, A. (2018). Cybersecurity for Industry 4.0 in the current literature: A reference framework. Computers in Industry, 103, 97-110.

[2] Tuptuk, N., & Hailes, S. (2018). Security of smart manufacturing systems. Journal of manufacturing systems, 47, 93-106.

[3] Rangan, K. K., & Durand, H. (2020, July). Lyapunov-based Economic Model Predictive Control with Taylor Series State Approximations. In 2020 American Control Conference (ACC) (pp. 1980- 1985). IEEE.

[4] Oyama, H., Rangan, K. K., & Durand, H. (2021). Handling of stealthy sensor and actuator cyberattacks on evolving nonlinear process systems. Journal of Advanced Manufacturing and Processing, 3(3), e10099.

[5] Rangan, K. K., Oyama, H., & Durand, H. (2022). Actuator Cyberattack Handling Using Lyapunov-based Economic Model Predictive Control. IFAC-PapersOnLine, 55(7), 489-494.

[6] Rangan, K. K., Oyama, H., & Durand, H. (2021). Integrated cyberattack detection and handling for nonlinear systems with evolving process dynamics under Lyapunov-based economic model predictive control. Chemical Engineering Research and Design, 170, 147-179.

[7] Oyama, H., Messina, D., Rangan, K. K., Leonard, A. F., Nieman, K., Durand, H., ... & Williamson, M. (2023). Development of directed randomization for discussing a minimal security architecture. Digital Chemical Engineering, 6, 100065.

[8] Rangan, K. K., J. Abou Halloun, H. Oyama, S. Cherney, I. Azali Assoumani, N. Jairazbhoy, H. Durand, and S. K. Ng. (2022). Quantum Computing and Resilient Design Perspectives for Cybersecurity of Feedback Systems. Proceedings of the IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS), Busan, Republic of Korea.

[9] Nieman, K., Kasturi Rangan, K., & Durand, H. (2022). Control Implemented on Quantum Computers: Effects of Noise, Nondeterminism, and Entanglement. Industrial & Engineering Chemistry Research, 61(28), 10133-10155.

[10] Rangan, K.K., Oyama, H., Azali Assoumani, I., Durand, H., and Ng, K. Y. S. (2023). “Cyberphysical Systems and Energy: A Discussion with Reference to an Enhanced Geothermal Process,” Energy Systems and Processes: Recent Advances in Design and Control, Li, M. (Ed.), AIP Publishing, Melville, New York.