| 1 |
Machine learning applied for metabolic flux-based control of micro-aerated fermentations in bioreactors
Mesquita TJB, Campani G, Giordano RC, Zangirolami TC, Horta ACL
Biotechnology and Bioengineering, 118(5), 2076, 2021 |
| 2 |
Application of autoregressive dynamic adaptive (ARDA) model in realtime wind power forecasting
Zhang F, Li PC, Gao L, Liu YQ, Ren XY
Renewable Energy, 169, 129, 2021 |
| 3 |
Integrated advanced nonlinear neural network-simulink control system for production of bio-methanol from sugar cane bagasse via pyrolysis
Kasmuri NH, Kamarudin SK, Abdullah SRS, Hasan HA, Som AM
Energy, 168, 261, 2019 |
| 4 |
Smart manufacturing and energy systems
Edgar TF, Pistikopoulos EN
Computers & Chemical Engineering, 114, 130, 2018 |
| 5 |
Advanced Model-Based Control Strategies for the Intensification of Upstream and Downstream Processing in mAb Production
Papathanasiou MM, Quiroga-Campano AL, Steinebach F, Elviro M, Mantalaris A, Pistikopoulos EN
Biotechnology Progress, 33(4), 966, 2017 |
| 6 |
Intelligent, model-based control towards the intensification of downstream processes
Papathanasiou MM, Steinebach F, Morbidelli M, Mantalaris A, Pistikopoulos EN
Computers & Chemical Engineering, 105, 173, 2017 |
| 7 |
Effect of process control on optimization of pulp and paper mill wastewater treatment by electrocoagulation
Camcioglu S, Ozyurt B, Hapoglu H
Process Safety and Environmental Protection, 111, 300, 2017 |
| 8 |
Survey on higher-level advanced control for grinding circuits operation
Zhou P, Lu SW, Yuan M, Chai TY
Powder Technology, 288, 324, 2016 |
| 9 |
Process performance improvement in a co-current, fixed bed biomass gasification facility by control system modifications
Mikulandric R, Loncar D, Bohning D, Bohme R, Beckmann M
Energy Conversion and Management, 104, 135, 2015 |
| 10 |
Model predictive control utilizing fuel and moisture soft-sensors for the BioPower 5 combined heat and power (CHP) plant
Kortela J, Jamsa-Jounela SL
Applied Energy, 131, 189, 2014 |
