1 |
MPC relevant identification method for Hammerstein and Wiener models Quachio R, Garcia C Journal of Process Control, 80, 78, 2019 |
2 |
An efficient MILP framework for integrating nonlinear process dynamics and control in optimal production scheduling calculations Kelley MT, Pattison RC, Baldick R, Baldea M Computers & Chemical Engineering, 110, 35, 2018 |
3 |
Control-oriented modeling of geothermal borefield thermal dynamics through Hammerstein-Wiener models Atam E, Schulte DO, Arteconi A, Sass I, Helsen L Renewable Energy, 120, 468, 2018 |
4 |
Generic model identification framework for thermodynamic engines for use in hybrid power stations control and simulation Alamir M, Rahmani MA, Gualino D Journal of Process Control, 24(6), 966, 2014 |
5 |
A new approach for nonlinear process identification using orthonormal bases and ordinal splines MacArthur JW Journal of Process Control, 22(2), 375, 2012 |
6 |
Identification of uncertain MIMO Wiener and Hammerstein models Biagiola SI, Figueroa JL Computers & Chemical Engineering, 35(12), 2867, 2011 |
7 |
Support vector method for identification of Wiener models Totterman S, Toivonen HT Journal of Process Control, 19(7), 1174, 2009 |
8 |
Continuous-time Hammerstein and Wiener modeling under second-order static nonlinearity for periodic process signals Zhai DM, Rollins DK, Bhandari N, Wu HQ Computers & Chemical Engineering, 31(1), 1, 2006 |
9 |
Identification of Hammerstein nonlinear ARMAX systems Ding F, Chen TW Automatica, 41(9), 1479, 2005 |
10 |
Identification of piecewise affine systems via mixed-integer programming Roll J, Bemporad A, Ljung L Automatica, 40(1), 37, 2004 |