| 1 |
Plantwide optimization via real-time optimization with persistent parameter adaptation
Matias JOA, Le Roux GAC
Journal of Process Control, 92, 62, 2020 |
| 2 |
The phi-Relation and a Simple Method to Predict How Many Data Points Are Needed for Relevant Steady-State Detection
Nellis C, Hin C, Savara A
AIChE Journal, 64(9), 3354, 2018 |
| 3 |
A data-driven adaptive multivariate steady state detection strategy for the evaporation process of the sodium aluminate solution
Xie S, Yang CH, Wang XL, Yuan XF, Xie YF
Journal of Process Control, 68, 145, 2018 |
| 4 |
Real-time Optimization with persistent parameter adaptation using online parameter estimation
Matias JOA, Le Roux GAC
Journal of Process Control, 68, 195, 2018 |
| 5 |
Preliminary tests on dynamic characteristics of a CO2 transcritical power cycle using an expansion valve in engine waste heat recovery
Li XY, Shu GQ, Tian H, Shi LF, Huang GD, Chen TY, Liu P
Energy, 140, 696, 2017 |
| 6 |
Steady state identification for on-line data reconciliation based on wavelet transform and filtering
Korbel M, Bellec S, Jiang TW, Stuart P
Computers & Chemical Engineering, 63, 206, 2014 |
| 7 |
Investigation on a new methodology for thermal power plant assessment through live diagnosis monitoring of selected process parameters; application to a case study
Blanco JM, Vazquez L, Pena F
Energy, 42(1), 170, 2012 |
| 8 |
Inference of multi-variable trends in unmeasured process quantities
Flehmig F, Marquardt W
Journal of Process Control, 18(5), 491, 2008 |
| 9 |
Soft sensors based on nonlinear steady-state data reconciliation in the process industry
Schladt M
Chemical Engineering and Processing, 46(11), 1107, 2007 |
| 10 |
Detection of multivariable trends in measured process quantities
Flehmig F, Marquardt W
Journal of Process Control, 16(9), 947, 2006 |
