Preprints and Submitted Material
R. Padmanabhan, M. Fowler, K. Huff, M. Neubauer, and M. Ornik, “A Vision for STEM Higher Education in the Face of AI,”, EdArXiv:Nzd53_v1, May 2026.
R. Padmanabhan and M. Ornik, “Finite-time Reachability for Constrained, Partially Uncontrolled Nonlinear Systems,” arXiv:2604.08327 [math.OC], Apr. 2026.
R. Padmanabhan and N. Mehr, “Robust Decentralized Multi-Agent Reinforcement Learning through Risk Sensitivity,” Apr. 2026.
R. Das*, R. Padmanabhan*, M. Ornik, and P. Jagtap, “Energetic Resilience under Temporal Logic Specifications,” arXiv:2604.14203 [eess.SY], Apr. 2026.
R. Padmanabhan and M. Ornik, “Ignore Drift, Embrace Simplicity: Constrained Nonlinear Control through Driftless Approximation,” arXiv:2509.06188 [math.OC], Sep. 2025.
Journal Articles
R. Padmanabhan and M. Ornik, “Approximate Energetic Resilience of Nonlinear Systems under Partial Loss of Control Authority,” Automatica, 187, May 2026. [Extended version available at arXiv:2502.07603]
R. Padmanabhan, A. Aspeel, N. Ozay, and M. Ornik, “Mode-Prefix-Based Control of Switched Linear Systems with Applications to Fault Tolerance,” IEEE Control Systems Letters, 9, pp. 1784–1789, Jul. 2025 (presented at 64th IEEE Conference on Decision and Control (CDC), Dec. 2025). [Available at arXiv:2505.13105]
R. Padmanabhan and P. Seiler, “Analysis of Gradient Descent with Varying Step Sizes using Integral Quadratic Constraints,” IEEE Transactions on Automatic Control, 70(1), pp. 587–594, Jan. 2025. [Available at arXiv:2210.00644]
R. Padmanabhan, R. Makam and K. George, “Multiple Estimation Models for Discrete-time Adaptive Iterative Learning Control,” International Journal of Systems Science, 55(10), pp. 2154-2171, Apr. 2024. [Available at arXiv:2203.11892]
R. Padmanabhan, M. Shetty and T. S. Chandar, “Discrete Robust Control of Robot Manipulators using an Uncertainty and Disturbance Estimator,” Journal of Dynamic Systems, Measurement and Control, 145(5): 051022, May 2023. [Available at arXiv:2203.03805]
R. Padmanabhan, M. Shetty and T. S. Chandar, “Discrete-Time Design and Applications of Uncertainty and Disturbance Estimator,” International Journal of Robust and Nonlinear Control, 31(10), pp. 4994-5015, Jul. 2021.
Conference Papers
G. Puthumanaillam*, R. Padmanabhan*, J. Fuentes, N. Cruz, P. Padrao, R. Hernandez, H. Jiang, W. Schafer, L. Bobadilla, and M. Ornik, “Online Learning of Deceptive Policies under Intermittent Observation,” in 2025 IEEE/RSJ International Conference on Intelligent Robots & Systems (IROS), Pittsburgh, PA, USA, Sep. 2026. [Available at arXiv:2509.14453]
S. A. Dinkar, R. Padmanabhan, A. Clarke, P.-O. Gutman, and M. Ornik, “Analysis of the Unscented Transform Controller for Systems with Bounded Nonlinearities,” in 5th Modeling, Estimation and Control Conference (MECC), Pittsburgh, PA, USA, Oct. 2025. [Available at arXiv:2504.08579]
R. Padmanabhan and M. Ornik, “Energetic Resilience of Linear Driftless Systems,” in 11th IFAC Symposium on Robust Control Design (ROCOND), Porto, Portugal, Jul. 2025. (Selected as Finalist, IFAC Young Author Award.) [Available at arXiv:2410.00323]
R. Padmanabhan, C. Bakker, S. A. Dinkar, and M. Ornik, “How Much Reserve Fuel: Quantifying the Maximal Energy Cost of System Disturbances,” in 63rd IEEE Conference on Decision and Control (CDC), Milan, Italy, Dec. 2024. [Available at arXiv:2408.10913]
R. Padmanabhan, M. Bhushan, K. K. Hebbar, R. Makam, and K. George, “Second-Level Adaptation and Optimization for Multiple Model Adaptive Iterative Learning Control,” in 2021 Seventh Indian Control Conference, Mumbai, India, Dec. 2021, pp. 289-294. (Virtual).
S. Damodaran, R. Padmanabhan, R. Maahin and S. Gurugopinath, “A Copula-Driven Unsupervised Learning Framework for Anomaly Detection with Multivariate Heterogeneous Data,” in 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), Gold Coast, Queensland, Australia, Oct. 2021. (Virtual).
R. Padmanabhan, M. Bhushan, K. K. Hebbar, R. Makam and K. George, “A Novel Strategy with Multiple Models to Improve Performance of Adaptive Iterative Learning Control,” in 2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), Bengaluru, India, Jul. 2021. (Virtual).
R. Padmanabhan, S. Damodaran, V. N. Batra and S. Gurugopinath, “A Convolutional Neural Network Architecture for Camera Model Identification with Small Datasets,” in 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), Bengaluru, India, Jul. 2020. (Virtual).