This paper introduces PIRC, a lightweight physics-informed reservoir computing framework that embeds degradation priors into a closed-form ridge regression readout for battery state-of-health prediction, validated on the NASA PCoE dataset and chaotic benchmark systems.

This paper introduces RCUKF, a framework combining Reservoir Computing and Unscented Kalman Filtering to achieve accurate state estimation in complex systems, validated on benchmark problems and real-time vehicle simulations.

This paper proposes a resilient input and state estimation method for autonomous vehicles, improving robustness against uncertainties and outliers. Simulations in CARLA validate enhanced estimation accuracy and system resilience.