Interval observer design for unknown input estimation of linear time-invariant discrete-time systems EI Robinson, J Marzat, T Raïssi 20th IFAC World Congress, 2017, 50 (1), 4021-4026, 2017 | 31 | 2017 |
Filtering and uncertainty propagation methods for model-based prognosis of fatigue crack growth in unidirectional fiber-reinforced composites EI Robinson, J Marzat, T Raïssi ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A …, 2018 | 14 | 2018 |
Prognosis of uncertain linear time-invariant discrete systems using unknown input interval observer EI Robinson, J Marzat, T Raïssi International Journal of Control 93 (11), 2690-2706, 2020 | 11 | 2020 |
An uncertainty quantification framework for autonomous system tracking and health monitoring M Corbetta, C Kulkarni, P Banerjee, E Robinson International Journal of Prognostics and Health Management 12 (3), 2021 | 9 | 2021 |
Systems health monitoring: Integrating fmea into bayesian networks CS Kulkarni, M Corbetta, EI Robinson 2021 IEEE Aerospace Conference (50100), 1-11, 2021 | 9 | 2021 |
Enhancing fault isolation for health monitoring of electric aircraft propulsion by embedding failure mode and effect analysis into bayesian networks CS Kulkarni, M Corbetta, E Robinson Annual Conference of the PHM Society 12 (1), 12-12, 2020 | 8 | 2020 |
Model-based prognosis using an explicit degradation model and Inverse FORM for uncertainty propagation EI Robinson, J Marzat, T Raïssi 20th IFAC World Congress, 2017, 50 (1), 14242–14247, 2017 | 8 | 2017 |
Model-based prognosis algorithms with uncertainty propagation: Application to fatigue crack growth EI Robinson, J Marzat, T Raïssi 3rd Conference on Control and Fault-Tolerant Systems (SysTol), 2016, 458-465, 2016 | 7 | 2016 |
Model-based prognosis of fatigue crack growth under variable amplitude loading EI Robinson, J Marzat, T Raïssi IFAC-PapersOnLine 51 (24), 176-183, 2018 | 4 | 2018 |
Filtering and uncertainty propagation methods for model-based prognosis EI Robinson Conservatoire national des arts et metiers-CNAM, 2018 | 2 | 2018 |
Estimation of permanent magnet synchronous motor parameters using a linear unknown input interval observer W Okolo, E Robinson AIAA SCITECH 2022 Forum, 1993, 2022 | 1 | 2022 |
Improving tail accuracy of the predicted cumulative distribution function of time of failure G Sierra, EI Robinson, K Goebel Reliability Engineering & System Safety 207, 107333, 2021 | 1 | 2021 |
PMSM Parameter Estimation using a Linear Unknown Input Interval Observer EI Robinson, WA Okolo AIAA SciTech, 2022 | | 2022 |