top of page

Journal Papers

  1. Cabral T.O., Pourkargar D.B., Nonlinear predictive regulation of an integrated green hydrogen and ammonia production system under time-varying renewable energy supply, Computers and Chemical Engineering, 2025; 109376 Link

  2. Bagheri A., Ebrahimi A., Pourkargar D.B., Self-attention transformer architectures for cyberattack detection and secure state reconstruction of integrated chemical process systems, Chemical Engineering Research and Design, 2025; 220:162-179 Link

  3. Ighalo J.O., Ebrahimi A., Smith M., Al Mayyahi A., Almkhelfe H., Pourkargar D.B., Amama P.B., Exploiting MXenes properties for coking resistance of Ni catalyst in dry reforming of methane, Journal of Catalysis, 2025; 450:116268 Link

  4. Marmolejo C.E.V., Pourkargar D.B., A multiphase-multiphysics modeling framework for nonlinear predictive control of particulate polysilicon reactor systems, Industrial and Engineering Chemistry Research, 2025; 64(20):10163-10180 Link

  5. Bagheri A., Patrignani A., Ghanbarian B., Pourkargar D.B., A time-series based hybrid and physics-informed machine learning framework to predict soil water content, Engineering Applications of Artificial Intelligence, 2025; 144:110105 Link

  6. Bagheri A., Cabral T.O., Pourkargar D.B., Integrated learning-based estimation and nonlinear predictive control of an ammonia synthesis reactor, AIChE Journal, 2025; 71(5):e18732 Link

  7. Cabral T.O., Amama P.B., Pourkargar D.B., Multiscale-multiphysics predictive modeling of chemical vapor deposition processes for carbon nanotube synthesis, Chemical Engineering Science, 2025; 305:121137 Link

  8. Ebrahimi A., Pourkargar D.B., Multi-agent distributed control of integrated process networks using an adaptive community detection approach, Digital Chemical Engineering, 2024; 13:100196 Link

  9. Ebrahimi A., Pourkargar D.B., An adaptive distributed architecture for multi-agent state estimation and control of complex process systems, Chemical Engineering Research and Design, 2024; 210:594-604 Link

  10. Marmolejo C.E.V., Pourkargar D.B., Predictive modeling and robust nonlinear control of a polysilicon reactor system for enhanced solar cell production, Control Engineering Practice, 2024; 153:106065 (Invited Paper) Link

  11. Cabral T.O., Bagheri A., Pourkargar D.B., Learning-Based Model Reduction and Predictive Control of an Ammonia Synthesis Process, Industrial and Engineering Chemistry Research, 2024; 63(23):10325-10342 Link

  12. Pourkargar D.B., Armaou A., Lyapunov-based on-line model reduction and control of semilinear dissipative distributed parameter systems with minimum feedback information, Journal of Process Control, 2021; 104:135-145 Link

  13. Pourkargar D.B., Moharir, M., Almansoori A., Daoutidis P., Distributed estimation and nonlinear model predictive control using community detection, Industrial and Engineering Chemistry Research, 2019; 58(30):13495-13507 (Invited Paper) Link

  14. Daoutidis P., Allman A., Khatib S., Moharir, M., Palys M.J., Pourkargar D.B., Tang W., Distributed decision making for intensified process systems, Current Opinion in Chemical Engineering, 2019; 25:75-81 (Invited Paper) Link

  15. Moharir, M., Pourkargar D.B., Almansoori A., Daoutidis P., Graph representation for distributed control of diffusion-convection-reaction system networks, Chemical Engineering Science, 2019; 204:128-139 Link

  16. Pourkargar D.B., Almansoori A., Daoutidis P., Comprehensive study of decomposition effects on output tracking of an integrated process over a wide operating range, Chemical Engineering Research and Design, Special Issue on Dynamics and Control, 2018; 134:553-563 (Invited Paper) Link

  17. Moharir, M., Pourkargar D.B., Almansoori A., Daoutidis P., Distributed model predictive control of an amine gas sweetening plant, Industrial and Engineering Chemistry Research, 2018; 57:13103-13115 Link

  18. Tang W., Pourkargar D.B., Daoutidis P., Relative time-averaged gain array (RTAGA) for distributed control-oriented network decomposition, AIChE Journal, 2018; 64(5):1682-1690 Link

  19. Feng J., Lansford J., Mironenko A., Pourkargar D.B., Vlachos D.G., Katsoulakis M.A., Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir biomolecular adsorption model, AIP Advances, 2018; 8:035021 Link

  20. Tang W., Allman A., Pourkargar D.B., Daoutidis P., Optimal decomposition for distributed optimization in nonlinear model predictive control through community detection, Computers and Chemical Engineering, 2018; 111:43-54 Link

  21. Pourkargar D.B., Almansoori A., Daoutidis P., The impact of decomposition on distributed model predictive control: A process network case study, Industrial and Engineering Chemistry Research, 2017; 56(34):9606-9616 Link

  22. Pourkargar D.B., Shahri S.M.K., Rioux R.M., Armaou A., Spatiotemporal modeling and parametric estimation of isothermal CO2 adsorption columns, Industrial and Engineering Chemistry Research, 2016; 55(22):6443-6453 Link

  23. Pourkargar D.B., Armaou A., Dynamic shaping of transport-reaction processes with a combined sliding mode controller and Luenberger-type dynamic observer design, Chemical Engineering Science, 2015; 138:673-684 Link

  24. Pourkargar D.B., Armaou A., Design of APOD-based switching dynamic observers and output feedback control for a class of nonlinear distributed parameter systems, Chemical Engineering Science, Special Issue on Control and Optimization of Smart Plant Operations, 2015; 136:62-75 (Invited Paper) Link

  25. Pourkargar D.B., Armaou A., Control of spatially distributed processes with unknown transport-reaction parameters via two-layer system adaptations, AIChE Journal, 2015; 61(8):2497-2507 Link

  26. Pourkargar D.B., Armaou A., APOD-based control of general linear distributed parameter systems in the presence of network communication constraints, AIChE Journal, 2015; 61(2):434-447 Link

  27. Pourkargar D.B., Armaou A., Geometric output tracking of nonlinear distributed parameter systems via adaptive model reduction, Chemical Engineering Science, 2014; 116:418-427 Link

  28. Pourkargar D.B., Armaou A., Modification to adaptive model reduction for regulation of distributed parameter systems with fast transients, AIChE Journal, 2013; 59(12):4595-4611 (Finalist for the Best Paper Award, Department of Chemical Engineering, Pennsylvania State University, 2014) Link

  29. Pourkargar D.B., Shahrokhi M., Optimal fuzzy synchronization of generalized Lorenz chaotic systems, The Journal of Mathematics and Computer Science, 2011; 2(1):27-36 (Invited Paper) Link

Conference Proceedings Papers

  1. Bagheri A., Cabral T.O., Pourkargar D.B., Learning-based estimation and predictive control of an ammonia synthesis reactor, In Proceedings of the American Control Conference (ACC), Denver, CO, 2025; 2311-2316 Link

  2. Ebrahimi A., Pourkargar D.B., An adaptive distributed architecture for state estimation and control of integrated process networks during operational transitions, In Proceedings of the American Control Conference (ACC), Denver, CO, 2025; 3267-3272 Link

  3. Cabral T.O., Pourkargar D.B., Nonlinear model predictive control of a modular hydrogen-ammonia and renewable energy generation system, In Proceedings of the American Control Conference (ACC), Denver, CO, 2025; 2402-2407 Link

  4. Marmolejo C.E.V., Pourkargar D.B., Nonlinear model predictive control of a particulate polysilicon reactor system for enhanced solar cell production, IFAC-PapersOnLine, 58(14): 531-537, 2024 Link

  5. Ebrahimi A., Pourkargar D.B., Distributed estimation and control of process networks using adaptive community detection, IFAC-PapersOnLine, 58(14): 754-760, 2024 Link

  6. Cabral T.O., Bagheri A., Pourkargar D.B., Learning-based model predictive control of an ammonia synthesis reactor, In Proceedings of the American Control Conference (ACC), 45-50, 2024 Link

  7. Ebrahimi A., Pourkargar D.B., Distributed model predictive control of integrated process networks based on an adaptive community detection approach, In Proceedings of the American Control Conference (ACC), 208-213, 2024 Link

  8. Bagheri A., Patrignani A., Ghanbarian B., Pourkargar D.B., A physics-informed machine learning approach to predict soil water content for agricultural decision-making, In Proceedings of the American Control Conference (ACC), 2-7, 2024 Link

  9. Sundberg B., Pourkargar D.B., Cyberattack awareness and resiliency of integrated moving horizon estimation and model predictive control of complex process networks, In Proceedings of the American Control Conference (ACC), 3815-3820, 2023 Link

  10. Hinkel P., Pourkargar D.B., An integrated moving horizon estimation and model predictive control framework for semi-closed greenhouse systems, In Proceedings of the IEEE Conference on Control Technology and Applications (CCTA), 699-705, 2022 Link

  11. Pourkargar D.B., Jogwar S.S., Distributed model predictive control of integrated process networks: Optimal decomposition for varying operating point, In Proceedings of the American Control Conference (ACC), 801-807, 2021 Link

  12. Pourkargar D.B., Armaou A., Control of semilinear dissipative distributed parameter systems with minimum feedback information, In Proceedings of the American Control Conference (ACC), 2685-2691, 2020 Link

  13. Moharir M., Pourkargar D.B., Almansoori A., Daoutidis P., Decomposition and distributed control of integrated lumped and distributed parameter process networks, In Proceedings of the IEEE Conference on Decision and Control (CDC), 2908-2913, 2018 (Invited Paper) Link

  14. Pourkargar D.B., Almansoori A., Daoutidis, P., Distributed model predictive control of process networks: Impact of control architecture, IFAC-PapersOnLine, 50(1):12452-12457, 2017 Link

  15. Pourkargar D.B., Armaou A., Spatiotemporal response shaping of transport-reaction processes via adaptive reduced order models, In Proceedings of the American Control Conference (ACC), 4157-4162, 2016 Link

  16. Pourkargar D.B., Armaou A., Adaptive control of chemical distributed parameter systems, IFAC-PapersOnLine, 48(8):682-687, 2015 Link

  17. Pourkargar D.B., Armaou A., Low-dimensional adaptive output feedback controller design for transport-reaction processes, In Proceedings of the European Control Conference (ECC), 879-884, 2015 Link

  18. Pourkargar D.B., Armaou A., Wave motion suppression in the presence of unknown parameters using recursively updated empirical basis functions, In Proceedings of the American Control Conference (ACC), 2619-2624, 2015 Link

  19. Pourkargar D.B., Armaou A., Output tracking of spatiotemporal thermal dynamics in transport-reaction processes via adaptive model reduction, In Proceedings of the American Control Conference (ACC), 3364-3370, 2014 Link

  20. Pourkargar D.B., Armaou A., Feedback control of linear distributed parameter systems via adaptive model reduction in the presence of device network communication constraints, In Proceedings of the American Control Conference (ACC), 1667-1673, 2014 (Invited Paper) Link

  21. Pourkargar D.B., Armaou A., A refined adaptive model reduction approach for control of fast evolving distributed parameter systems, In Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems (MTNS), 140-147, 2014 (Invited Paper) Link

  22. Pourkargar D.B., Armaou A., Control of dissipative partial differential equation systems using APOD based dynamic observer designs, In Proceedings of the American Control Conference (ACC), 502-508, 2013 (O. Hugo Schuck Best Paper Award in the Application Category, American Automatic Control Council, 2014) Link

© 2025 by Davood B. Pourkargar                                  

    Tim Taylor Department of Chemical Engineering

    Carl R. Ice College of Engineering, Kansas State University

KSU logo white.png
bottom of page