5 papers
Safe Learning-Based Adaptive Augmentation Control for Fixed-Wing UAV under Uncertainty
Leon Raguse, Lennart Kracke, Mayank Shekhar Jha +2
This paper presents a learning-based adaptive augmentation control concept inspired by the adaptation mechanisms of conventional adaptive control, while not being restricted to the…
CAPSULE: Control-Theoretic Action Perturbations for Safe Uncertainty-Aware Reinforcement Learning
Rahul Narava, Siddharth Verma, Ojas Jain +2
Ensuring safe exploration in high-dimensional systems with unknown dynamics remains a significant challenge. Existing safe reinforcement learning methods often provide safety guara…
Remaining useful life prediction of Lithium-ion batteries using spatio-temporal multimodal attention networks
Sungho Suh, Dhruv Aditya Mittal, Hymalai Bello +3
Lithium-ion batteries are widely used in various applications, including electric vehicles and renewable energy storage. The prediction of the remaining useful life (RUL) of batter…
Two-stage Early Prediction Framework of Remaining Useful Life for Lithium-ion Batteries
Dhruv Mittal, Hymalai Bello, Bo Zhou +3
Early prediction of remaining useful life (RUL) is crucial for effective battery management across various industries, ranging from household appliances to large-scale applications…
A Reinforcement Learning Approach to Health Aware Control Strategy
Mayank Shekhar Jha, Philippe Weber, Didier Theilliol +2
Health-aware control (HAC) has emerged as one of the domains where control synthesis is sought based upon the failure prognostics of system/component or the Remaining Useful Life (…