| 1 |
CONVERGENCE ANALYSIS AND ADAPTIVE ORDER SELECTION FOR THE POLYNOMIAL CHAOS APPROACH TO DIRECT OPTIMAL CONTROL UNDER UNCERTAINTIES
Frison L, Kirches C
SIAM Journal on Control and Optimization, 59(1), 509, 2021 |
| 2 |
Artificial Neural Networks for dynamic optimization of stochastic multiscale systems subject to uncertainty
Kimaev G, Ricardez-Sandoval LA
Chemical Engineering Research & Design, 161, 11, 2020 |
| 3 |
Intermittent sensor fault detection for stochastic LTV systems with parameter uncertainty and limited resolution
Zhang JF, Christofides PD, He X, Albalawi F, Zhao YH, Zhou DH
International Journal of Control, 93(4), 788, 2020 |
| 4 |
Parameter uncertainty quantification for a four-equation transition model using a data assimilation approach
Yang MC, Xiao ZX
Renewable Energy, 158, 215, 2020 |
| 5 |
Efficient Direct-Model Predictive Control With Discrete-Time Integral Action for PMSGs
Abdelrahem M, Hackl CM, Kennel R, Rodriguez J
IEEE Transactions on Energy Conversion, 34(2), 1063, 2019 |
| 6 |
Consensus tracking control with transient performance improvement for a group of unmanned aerial vehicles subject to faults and parameter uncertainty
Wang QS, Huang D, Duan ZS, Wang JY
International Journal of Control, 92(4), 796, 2019 |
| 7 |
PARAMETER UNCERTAINTY IN THE KALMAN-BUCY FILTER
Allan AL, Cohen SN
SIAM Journal on Control and Optimization, 57(3), 1646, 2019 |
| 8 |
Robust dynamic optimization of batch processes under parametric uncertainty: Utilizing approaches from semi-infinite programs
Puschke J, Djelassi H, Kleinekorte J, Hannemann-Tamas R, Mitsos A
Computers & Chemical Engineering, 116, 253, 2018 |
| 9 |
Robust feasible control based on multi-stage eNMPC considering worst-case scenarios
Puschke J, Mitsos A
Journal of Process Control, 69, 8, 2018 |
| 10 |
Uncertainty quantification of a newly optimized methanol and formaldehyde combustion mechanism
Olm C, Varga T, Valko E, Curran HJ, Turanyi T
Combustion and Flame, 186, 45, 2017 |
