Efficient robust nonlinear model predictive control via approximate multi-stage programming: A neural networks based approach

Predictive Control ◽

Nonlinear Model ◽

Stability properties of multi-stage nonlinear model predictive control

Systems & Control Letters ◽

10.1016/j.sysconle.2020.104743 ◽

2020 ◽

Vol 143 ◽

pp. 104743

Author(s):

Sergio Lucia ◽

Sankaranarayanan Subramanian ◽

Daniel Limon ◽

Sebastian Engell

Keyword(s):

Predictive Control ◽

Nonlinear Model ◽

Stability Properties ◽

Multi-stage nonlinear model predictive control applied to a semi-batch polymerization reactor under uncertainty

Journal of Process Control ◽

10.1016/j.jprocont.2013.08.008 ◽

2013 ◽

Vol 23 (9) ◽

pp. 1306-1319 ◽

Cited By ~ 149

Author(s):

Sergio Lucia ◽

Tiago Finkler ◽

Sebastian Engell

Keyword(s):

Predictive Control ◽

Nonlinear Model ◽

Multi Stage ◽

Polymerization Reactor

Nonlinear model predictive control of a multistage evaporator system using recurrent neural networks

2009 4th IEEE Conference on Industrial Electronics and Applications ◽

10.1109/iciea.2009.5138477 ◽

2009 ◽

Cited By ~ 3

Author(s):

J.C. Atuonwu ◽

Y. Cao ◽

G.P. Rangaiah ◽

M.O. Tade

Keyword(s):

Neural Networks ◽

Nonlinear Model Predictive Control

Predictive Control ◽

Nonlinear Model ◽

Recurrent Neural Networks ◽

Nonlinear model predictive control of a multiscale thin film deposition process using artificial neural networks

Chemical Engineering Science ◽

10.1016/j.ces.2019.07.044 ◽

2019 ◽

Vol 207 ◽

pp. 1230-1245 ◽

Cited By ~ 19

Author(s):

Grigoriy Kimaev ◽

Luis A. Ricardez-Sandoval

Keyword(s):

Thin Film ◽

Neural Networks ◽

Artificial Neural Networks ◽

Nonlinear Model Predictive Control

Predictive Control ◽

Nonlinear Model ◽

Thin Film Deposition ◽

Deposition Process ◽

Film Deposition ◽

Dual robust nonlinear model predictive control: A multi-stage approach

Journal of Process Control ◽

10.1016/j.jprocont.2018.10.003 ◽

2018 ◽

Vol 72 ◽

pp. 39-51 ◽

Cited By ~ 15

Author(s):

S. Thangavel ◽

S. Lucia ◽

R. Paulen ◽

S. Engell

Keyword(s):

Predictive Control ◽

Nonlinear Model ◽

Fast approximate learning-based multistage nonlinear model predictive control using Gaussian processes and deep neural networks

Computers & Chemical Engineering ◽

10.1016/j.compchemeng.2020.107174 ◽

2021 ◽

Vol 145 ◽

pp. 107174

Author(s):

Angelo D. Bonzanini ◽

Joel A. Paulson ◽

Georgios Makrygiorgos ◽

Ali Mesbah

Keyword(s):

Neural Networks ◽

Nonlinear Model Predictive Control

Predictive Control ◽

Nonlinear Model ◽

Gaussian Processes ◽

Deep Neural Networks ◽

Multi-stage and Two-stage Robust Nonlinear Model Predictive Control

IFAC Proceedings Volumes ◽

10.3182/20120823-5-nl-3013.00015 ◽

2012 ◽

Vol 45 (17) ◽

pp. 181-186 ◽

Cited By ~ 7

Author(s):

S. Lucia ◽

S. Engell

Keyword(s):

Predictive Control ◽

Nonlinear Model ◽

Two Stage ◽

Multi-stage Nonlinear Model Predictive Control with verified robust constraint satisfaction

53rd IEEE Conference on Decision and Control ◽

10.1109/cdc.2014.7039821 ◽

2014 ◽

Cited By ~ 16

Author(s):

Sergio Lucia ◽

Radoslav Paulen ◽

Sebastian Engell

Keyword(s):

Predictive Control ◽

Nonlinear Model ◽

Constraint Satisfaction ◽

Nonlinear model predictive control of an intensified continuous reactor using neural networks

2015 34th Chinese Control Conference (CCC) ◽

10.1109/chicc.2015.7260271 ◽

2015 ◽

Author(s):

Li Shi ◽

Li Yueyang

Keyword(s):

Neural Networks ◽

Predictive Control ◽

Nonlinear Model ◽

Continuous Reactor

Nonlinear model-predictive control with disturbance rejection property using adaptive neural networks

Journal of the Franklin Institute ◽

10.1016/j.jfranklin.2017.06.005 ◽

2017 ◽

Vol 354 (13) ◽

pp. 5201-5220 ◽

Cited By ~ 9

Author(s):

Bahareh Vatankhah ◽

Mohammad Farrokhi

Keyword(s):

Neural Networks ◽

Predictive Control ◽

Nonlinear Model ◽

Disturbance Rejection ◽

Adaptive Neural Networks