Resilience of Control Systems

A key challenge is quantifying the maximum disturbances a system can tolerate without violating its specifications. In our work, we define resilience as the largest set of admissible disturbances under which a system can still satisfy complex operational and safety requirements. Our work focuses on the resilience analysis and synthesis of control systems, developing methods to quantify, guarantee, and maximize the performance of controlled dynamical systems under real-world perturbations. The research sits at the intersection of theoretical foundations (robust control, formal methods, optimization) and applied domains (autonomous systems, robotics, power networks).

• Resilience as a Quantitative Metric

While traditional robust control ensures performance under bounded disturbances, it primarily emphasizes maintaining safety rather than quantifying the maximum disturbance a system can tolerate before violating its specifications. We formally define and analyze resilience as a metric, defined as the largest set of admissible disturbances under which a system can still satisfy complex behavioral requirements.

• Computation of Resilience

Beyond theoretical formulation, we study how to compute resilience efficiently for deployable systems using optimization approaches for linear and nonlinear systems. We leverage techniques from linear algebra and analysis to translate infeasible optimization problems to   tractable problems. We further use scenario optimization approaches to approximate resilience for general nonlinear systems. 

• A. Saoud, P. Jagtap and S. Soudjani, “Temporal Logic Resilience for Dynamical Systems,” IEEE Transactions on Automatic Control, 2025.

• A. Saoud, P. Jagtap, and S. Soudjani, “Temporal Logic Resilience for Cyber-Physical Systems,” IEEE Conference on Decision and Control (CDC), 2023 , (pp. 2066-2071).

• Y. Ait si, R. Das, N. Monir, S. Soudjani, P. Jagtap and A. Saoud, “Maximally Resilient Controllers under Temporal Logic Specifications,” IEEE Conference on Decision and Control (CDC), 2025.

• N. Monir, Y. Ait Si, R. Das, P. Jagtap, A. Saoud and S. Soudjani, “Computation of Feasible Assume-Guarantee Contracts: A Resilience-based Approach,” IEEE Conference on Decision and Control (CDC), 2025.