List of publications

Thesis:

  1. Ferramosca A., Model Predictive Control for systems with changing setpoints. University of Seville, Spain. 2011.

Special Issued Edited:

  1. A. Ferramosca and T. Faulwasser. Model Predictive Control for Energy Systems: Economic and Distributed Approaches. Optimal Control Applications and Methods, 41(1), 2020.

Internation Journals:

  1. Alves dos Santos, M., Ferramosca, A., & Raffo, G. V. (2024). Set-point tracking MPC with avoidance features. Automatica, 159, 111390. DOI: 10.1016/j.automatica.2023.111390
  2. Alarcón, M. A., Alarcón, R. G., González, A. H., & Ferramosca, A. (2023). A scenario-based economic-stochastic model predictive control for the management of microgrids. Sustainable Energy, Grids and Networks, 101205. DOI: 10.1016/j.segan.2023.101205
  3. Luque, A., Mazzoleni, M., Zamora-Polo, F., Ferramosca, A., Lama, J. R., & Previdi, F. (2023). Determining the Importance of Physicochemical Properties in the Perceived Quality of Wines. IEEE Access. DOI: 10.1109/ACCESS.2023.3325676
  4. Comelli, R., González, A. H., Ferramosca, A., Olaru, S., Seron, M. M., & Kofman, E. (2023). Simplified design of practically stable MPC schemes. Systems & Control Letters, 180, 105626.
  5. Santos, M. A., Ferramosca, A., & Raffo, G. V. (2023). Nonlinear Model Predictive Control Schemes for Obstacle Avoidance. Journal of Control, Automation and Electrical Systems, 1-16.
  6. Sereno, J. E., D’Jorge, A., Ferramosca, A., Hernandez-Vargas, E. A., & González, A. H. (2023). Switched NMPC for epidemiological and social-economic control objectives in SIR-type systems. Annual Reviews in Control, 56, 100901.
  7. Sereno Mesa, J. E., Ferramosca, A., González, A. H., & D’Jorge, A. (2023). Impacts of Quantifying Social Distancing Measures on Mpc Performance for Sir-Type Systems. LATIN AMERICAN APPLIED RESEARCH, 53(4), 417-422.
  8. Previtali, D., Mazzoleni, M., Ferramosca, A., & Previdi, F. (2023). GLISp-r: a preference-based optimization algorithm with convergence guarantees. Computational Optimization and Applications, 1-38.
  9. Sánchez, I. J., D’Jorge, A., Limache, A. C., González, A. H., & Ferramosca, A. (2023). Tracking periodic parametric references using model predictive control. International Journal of Robust and Nonlinear Control.
  10. G.B. Caceres, A. Ferramosca, P. Millan, and M. Pereira (2023). Model predictive control structures for periodic on-off irrigation. IEEE Access, pages 1–1.
  11. Anderson, A. L., Abuin, P., Ferramosca, A., Hernandez‐Vargas, E. A., & Gonzalez, A. H. (2023). Cyclic control equilibria for switched systems with applications to ecological systems. International Journal of Robust and Nonlinear Control, 33(9), 5159-5175. DOI: 10.1002/rnc.5951
  12. Sereno, J., Anderson, A., Ferramosca, A., Hernandez-Vargas, E. A., & González, A. H. (2022). Minimizing the epidemic final size while containing the infected peak prevalence in SIR systems. Automatica, 144, 110496.
  13. Alarcon, M. A., Alarcon, R. G., González, A. H, & Ferramosca, A. (2022). Economic model predictive control for energy managment of a microgrid connected to the main electric grid. Journal of Process Control, 117, 40-52.
  14. D’Jorge A., Anderson A., Ferramosca A., González A. H., and Actis M. On stability of nonzero set-point for nonlinear impulsive control systems. Systems & Control Letters, 165, 105244. DOI: 10.1016/j.sysconle.2022.105244
  15. Luque, A., Mazzoleni, M., Carrasco, A., & Ferramosca, A. (2021). Visualizing Classification Results: Confusion Star and Confusion Gear. IEEE Access (Volume 10). DOI: 10.1109/ACCESS.2021.3137630
  16. P. Chanfreut, J. M. Maestre, A. Ferramosca, F. J. Muros, and E. F. Camacho. Distributed model predictive control for tracking: A coalitional clustering approach. IEEE Transactions on Automatic Control, 2021. DOI: 10.1109/TAC.2021.3133486
  17. Eva Masero, José M Maestre, Antonio Ferramosca, Mario Francisco, and Eduardo F Camacho. Robust coalitional model predictive control with predicted topology transitions. IEEE Transactions on Control of Network Systems, 8(4), 1869-1880. 2021. DOI: 10.1109/TCNS.2021.3088806.
  18. I. Sanzhez A. D’jorge, G. V. Ra˙o, A. H. Gonzalez, and A. Ferramosca. Nonlinear Model Predictive Path Following Controller with Obstacle Avoidance. Journal of Intelligent and Robotic Systems, 102(16):1–18, 2021. DOI: 10.1007/s10846-021-01373-7.
  19. Anderson Alejandro, Gonzalez Alejandro H., Ferramosca Antonio, Hernandez-Vargas Esteban A. (2021). Discrete-time MPC for switched systems with applications to biomedical problems. Communications in nonlinear science and numerical simulations, 95(2):–, 2021. DOI: 10.1016/j.cnsns.2020.105586
  20. Pablo Abuin, Alejandro Anderson, Antonio Ferramosca, Esteban A Hernandez-Vargas, and Alejandro H Gonzalez. Dynamical characterization of antiviral effects in covid-19. Annual Reviews in Control, 2021. DOI: 10.1016/j.arcontrol.2021.05.001.
  21. P. Abuin, A. Anderson, A. Ferramosca, E. A. Hernandez-Vargas, and A. H. González. Characterization of SARS-CoV-2 Dynamics in Host. Annual Reviews in Control, 50:457–468, 2021. DOI: 10.1016/j.arcontrol.2020.9.008.
  22. P. Abuin, P.S. Rivadeneira, A. Ferramosca, and A. H. González. Artificial pancreas under stable pulsatile MPC: improving the closed-loop performance. Journal of Process Control, 2020. vol. 92, p. 246-260, ISSN: 0959-1524, doi: 10.1016/j.jprocont.2020.06.009
  23. A. H. González, P.S. Rivadeneira, A. Ferramosca, N. Magdelaine, and C. H. Moog. Stable Impulsive Zone MPC for Type 1 Diabetic Patients based on a long-term model. Optimal Control Applications and Methods, 2020. vol. November/December 2020, p. 2115-2136, ISSN: 0143-2087, doi: 10.1002/oca.2647
  24. A. Ferramosca and T. Faulwasser. Editorial Model Predictive Control for Energy Systems: Economic and Distributed Approaches. Optimal Control Applications and Methods, 41(1):1–2, 2020. Special Issue: MPC for Energy Systems. Economic and Distributed Approach. Guest Editors: A. Ferramosca and T. Faulwasser.
  25. A. D’Jorge, B. F. Santoro, A. Anderson, A. H. González, and A. Ferramosca. Stochastic model predictive control for tracking linear systems. Optimal Control Applications and Methods, 41(1):65–83, 2020. Special Issue: MPC for Energy Systems. Economic and Distributed Approach. Guest Editors: A. Ferramosca and T. Faulwasser.
  26. D. Limon, A. Ferramosca, I. Alvarado, and T. Alamo. Nonlinear MPC for tracking piece-wise constant reference signals. IEEE Transactions on Automatic Control, 2018. DOI: 10.1109/TAC.2018.2798803.
  27. A. D’Jorge, A. Anderson, A. H. González, and A. Ferramosca. A robust Economic MPC for Changing Economic Criterion. International Journal of Robust and Nonlinear Control, 2018. DOI: 10.1002/rnc.4243
  28. A. Anderson, A. H. González, A. Ferramosca, and E. Kofman. Finite-time convergence results in robust Model Predictive Control. Optimal Control Applications and Methods, 2018. DOI: 10.1002/oca.2430.
  29. A. Anderson, A. H. González, A. Ferramosca, A. D’Jorge, and E. Kofman. Robust MPC suitable for closed-loop re-identification, based on probabilistic invariant sets. Systems & Control Letters, 118(8):84–93, 2018.
  30. P. S. Rivadeneira, A. Ferramosca, and A. H. González. Control Strategies for Non-zero Set-point Regulation of Linear Impulsive Systems. IEEE Transactions on Automatic Control, 2018. doi: 10.1109/TAC.2017.2776598.
  31. M. A. Santos, B. S. Rego, G. V. Raffo, and A. Ferramosca. Suspended Load Path Tracking Control Strategy using a Tilt-rotor UAV. Journal of Advanced Transportation, 2017.
  32. A. I. Hinojosa, A. Ferramosca, A. H. González, and D. Odloak. One-layer gradient based MPC+RTO of a propylene/propane splitter. Computers and Chemical Engineering, 106:160–170, 2017.
  33. J. L. Godoy, A. Ferramosca, and A. H. González. Economic performance assessment and monitoring in LP-DMC type controller applications. Journal of Process Control, 57:26–37, 2017.
  34. A. Ferramosca, A. H. González, and D. Limon. Offset-free multi-model Economic Model Predictive Control for Changing Economic Criterion. Journal of Process Control, 54:1–13, 2017.
  35. A. D’Jorge, A. Ferramosca, and A. H. González. A robust gradient-based MPC for integrating Real Time Optimizer (RTO) with control. Journal of Process Control, 54:65–80, 2017.
  36. G. A. Bustos, A. Ferramosca, J. L. Godoy, and A. H. González. Application of Model Predictive Control suitable for closed-loop re-identification to a polymerization reactor. Journal of Process Control, (44):1–13, 2016.
  37. A. Anderson, A. Ferramosca, A. H. González, and E. Kofman. Probabilistic Invariant Sets for Closed-Loop Re-Identification. IEEE Latin America Transactions, 14(6):2744–2751, 2016.
  38. A. Ferramosca, D. Limon, E.F. Camacho, Economic MPC for changing economic criterion for linear systems. IEEE Transaction on Automatic Control. 59 (10), pp: 2657-2667. 2014.
  39. A. Ferramosca, A.H. González, D. Limon, G. A. Bustos, J. L. Godoy, J. L. Marchetti. On Economic Optimality of Model Predictive Control. IEEE Latin America Transaction. 12 (7), pp.: 1234-1241. 2014.
  40. A. H. González, A. Ferramosca, G.A. Bustos, J.L. Marchetti, M. Fiacchini, D. Odloak. Model Predictive Control suitable for closed-loop re-identification. System and Control Letters, 69 (7), pp: 23-33. 2014.
  41. T. Alamo, A. Ferramosca, A.H. González, D. Limon, D. Odloak. A gradient-based strategy for the one-layer RTO+MPC controller. Journal of Process Control, 24(4), pp: 435-447. 2014.
  42. G. Marchetti, A. Ferramosca, A.H. González. Steady-State Target Optimization Designs for Integrating Real-Time Optimization and Model Predictive Control. Journal of Process Control 24(1), pp: 129-145. 2014.
  43. A. Ferramosca, D. Limon, I. Alvarado, E.F. Camacho, Cooperative distributed MPC for tracking. AUTOMATICA: 49(4), pp.: 906-914. 2013.
  44. A. Ferramosca, J. K. Gruber, D. Limon, E.F. Camacho, Control Predictivo para seguimiento de sistemas no lineales. Aplicación a una planta piloto. Revista Iberoamericana de Automática e Informática Industrial, 10 (1): 18-29.
  45. A. Ferramosca, D. Limon, I. Alvarado, A.H. Gonzalez, E.F. Camacho, Robust MPC for tracking zone regions based on nominal predictions. Journal of Process Control, 22 (10): 1966-1974. 2012.
  46. A. Ferramosca., D. Limon, I. Alvarado, T. Alamo, E.F. Camacho, Optimal MPC for tracking of constrained linear systems. International Journal of System Science. 42 (8):1265-1276. 2011.
  47. A. Ferramosca, D. Limon, A.H. Gonzalez, D. Odloak, E.F. Camacho, MPC for tracking zone regions. Journal of Process Control 20 (4), pp. 506-516. 2010.
  48. A. Ferramosca, D. Limon, I. Alvarado, T. Alamo, E.F. Camacho, MPC for tracking with optimal closed-loop performance. Automatica, 45 (8), pp. 1975-1978. 2009.

Books Chapters:

  1. Pérez, M., Abuin, P., Actis, M., Ferramosca, A., Hernandez-Vargas, E. A., & González, A. H. (2022). Optimal control strategies to tailor antivirals for acute infectious diseases in the host: a study case of COVID-19. In Feedback Control for Personalized Medicine (pp. 11-39). Academic Press. DOI: 10.1016/B978-0-32-390171-0.00011-1
  2. P. S. Rivadeneira, J. L. Godoy, J. E. Sereno, P. Abuin, A. Ferramosca, and A. H. González. Impulsive mpc schemes for biomedical processes. application to type 1 diabetes. In Ahmad Taher Azar, editor, Control applications for Biomedical Engineering Systems, pages 391–449. ELSEVIER, 2020.

  3. R. Ledesma, J.M. Rubio, A. Ferramosca, C. Paetz. Sistemas domóticos inalámbricos. Z-Wave. Domótica para Ingenieros, pp:101-130. Ediciones Paraninfo.

  4. A. Ferramosca, A. Cooperative MPC with guaranteed exponential stability. Distributed Model Predictive Control Made Easy, pp:585-600. Springer. 2013.

  5. A. Ferramosca, D. Limon, A.H. González. Cooperative Distributed MPC integrating a Steady State Target Optimizer (SSTO). Distributed Model Predictive Control Made Easy, pp: 569-584. Springer. 2013.

  6. D. Limon, A. Ferramosca, I. Alvarado, T. Alamo, E.F. Camacho, MPC for tracking of constrained nonlinear systems. Nonlinear Model Predictive Control – Towards New Challenging Applications, pp: 315-323 Springer, 2009.

  7. D. Limon, T. Alamo, D. M. Raimondo, D. Muñoz de la Peña, J.M. Bravo, A. Ferramosca and E.F. Camacho. Input-to-State Stability: a Unifying Framework for Robust Model Predictive Control. Nonlinear Model Predictive Control – Towards New Challenging Applications, pp:1-26 Springer, 2009.

 International Conferences:

  1. Sonzogni, B., Manzano, J.M., Polver, M., Previdi, F., & Ferramosca, A. (2023). Choki –based MPC for blood-glucose regulation in artificial pancreas with probabilistic constraints. In 62nd Conference on Decision and Control, CDC 2023. Singapore December 13-15 2023. 
  2. Sonzogni, G., Mazzoleni, M., Polver, M., Ferramosca, A., & Previdi, F. (2023). Notch Filter Design with Stability Guarantees for Mechanical Resonance Suppression in SISO LTI Two-Mass Drive Systems. In 62nd Conference on Decision and Control, CDC 2023. Singapore December 13-15 2023. 
  3. Sonzogni, B., Manzano, J.M., Polver, M., Previdi, F., & Ferramosca, A. (2023). Choki –based MPC for blood-glucose regulation in artificial pancreas. IFAC-PapersOnLine 56 (2), 9672-9677. In 2023 IFAC World Congress, Yokohama, Japan, July 2023. 

  4. Polver, M., Sonzogni, B., Mazzoleni. M., Previdi, F., & Ferramosca, A. (2023). Artificial Pancreas under a Zone Model Predictive Control based on Gaussian Process models: toward the personalization of the closed loop. IFAC-PapersOnLine 56 (2), 9642-9647. In 2023 IFAC World Congress, Yokohama, Japan, July 2023.

  5. G. Galuppini, L. Magni, A. Ferramosca. Nonlinear MPC for tracking piecewise-constant reference signals: the positive semidefinite stage cost case. IFAC-PapersOnLine, 56(1), 210-215. 12th IFAC Symposium on Nonlinear Control Systems, NOLCOS 2023. Canberra, Australia, January 4-6 2023.

  6. P. Abuin, A. Ferramosca, A. H. González. MPC-based artificial pancreas accounting for circadian variability of insulin sensitivity. 2022 10th International Conference on Systems and Control (ICSC), pages 582–587. IEEE, Marseille, France, November, 23-25 2022.

  7. P. Abuin, A. Ferramosca, C. Toffanin, L. Magni, A. H. González. Artificial Pancreas under periodic MPC for trajectory tracking: handling circadian variability of insulin sensitivity. IFAC-PapersOnLine, 55(16):196–201. In 18th IFAC Workshop on Control Applications and Optimization, CAO 2022, pages 208–213. IFAC, Paris, France, July, 18-22 2022.
  8. A. H. González, A. Ferramosca, E. A. Hernandez-Vargas.  Optimal single interval control for SIR-type systems. IFAC-PapersOnLine, 55(16):202–207. In 18th IFAC Workshop on Control Applications and Optimization, CAO 2022, pages 208–213. IFAC, July, 18-22 2022.
  9. J. E. Sereno, A. D’Jorge, A. Ferramosca, E. A. Hernandez-Vargas, and A. H. González. Model predictive control for optimal social distancing in a type SIR-switched model. IFAC-PapersOnLine, 54(15):251–256. In 11th IFAC Symposium on Biological and Medical Systems, BMS 2021, pages 251–256. IFAC, September, 19-22 2021.
  10. Marcelo A. Santos, Antonio Ferramosca, and Guilherme V. Raffo. Tracking nonlinear model predictive control for obstacle avoidance. In 2021 Latin American Robotics Symposium (LARS), 2021 Brazilian Symposium on Robotics (SBR), and 2021 Workshop on Robotics in Education (WRE), pages 30–35. IEEE, 2021.
  11. Marcelo A. Santos, Antonio Ferramosca, and Guilherme V. Raffo. Energy-aware model predictive control with obstacle avoidance. In 2021 International Conference on Unmanned Aircraft Systems (ICUAS), pages 647–655. IEEE, 2021.
  12. Rodrigo G Alarcón, Martín A Alarcón, Alejandro H González, and Antonio Ferramosca. State-space modelling of a commercial lithium-ion battery. In RPIC 2021. XIX Edición de la XIX Reunión de Trabajo en Procesamiento de la Información y Control, pages 1–6. IEEE Argentina, November, 3-5 2021.
  13. Martín A Alarcón, Rodrigo G Alarcón, Alejandro H González, and Antonio Ferramosca. Economic model predictive control for energy management in a hybrid storage microgrid. In RPIC 2021. XIX Edición de la XIX Reunión de Trabajo en Procesamiento de la Información y Control, pages 1–6. IEEE Argentina, November, 3-5 2021.
  14. J. D. Vergara-Diertrich, A. Ferramosca, V. Mirasierra, J. E. Normey-Rico, and D. Limon. A Modifier-Adaptation Approach to the One-Layer Economic MPC. IFAC-PapersOnLine, 53(2):6957–6962. In 21th IFAC World Congress, Berlin, Germany, July, 11-17 2020.
  15. Alarcón, Martin, Alarcón, Rodrigo, Alejandro H. González, Ferramosca, Antonio (2020). Modelling a residential microgrid for energy management. In: 27º Congreso Argentino de Control Automatica, AADECA 2020. p. 1-6, Buenos Aires, Argentina, Ottobre 2020.
  16. Alarcón, Martin, Alarcón, Rodrigo, González, Alejandro H., Ferramosca, Antonio (2020). Economic Model Predictive Control for energy management in a microgrid. In: 27º Congreso Argentino de Control Automatico, AADECA 2020. p. 1-6, Buenos Aires, Argentina, Ottobre 2020.
  17. Sanchez, Ignacio, D’Jorge, Agustina, Limache, Alejandro, González, Alejandro H., Ferramosca, Antonio (2020). Model Predictive Periodic Output Path Following. In: 27º Congreso Argentino de Control Automatica, AADECA 2020. p. 1-6, Buenos Aires, Argentina, Ottobre 2020.
  18. Abuin, Pablo, Sereno, Juan, Ferramosca, Antonio, González, Alejandro H. (2020). Closed-loop MPC-based artificial pancreas: Handling circadian variability of insulin sensitivity. In: 27º Congreso Argentino de Control Automatica, AADECA 2020. p. 1-6, Buenos Aires, Argentina, Ottobre 2020
  19. A. Anderson, A. H. González, A. Ferramosca, and E. Hernández-Vargas. Discrete-time switching MPC with applications to mitigate resistance in viral infections. IFAC-PapersOnLine, 53(2):16043–16048. In 21th IFAC World Congress, Berlin, Germany, July, 11-17 2020. Invited Session.
  20. I. Sanchez, A. Ferramosca, G. Raffo, A. H. González, and A.D’Jorge. Obstacle Avoiding Path Following based on Nonlinear Model Predictive Control using Artificial Variables. In 19th International Conference on Advanced Robotics (ICAR), Belo Horizonte, Brasil, December, 2-6 2019.
  21. I. Sanchez, A.D’Jorge, A. Ferramosca, G. Raffo, and A. H. González. Model Predictive Path Following and Trajectory Tracking Control using Artificial Variables for Constrained Vehicles. In 18th Workshop on Information Processing and Control (RPIC), Bahia Blanca, Argentina, September, 18-20 2019.
  22. I. B. P. Nascimento, A. Ferramosca, L. Pimenta, and G. Raffo. NMPC Strategy for a Quadrotor UAV in a 3D Unknown Environment. In 19th International Conference on Advanced Robotics (ICAR), Belo Horizonte, Brasil, December, 2-6 2019.
  23. I. B. P. Nascimento, A. Ferramosca, L. Pimenta, and G. Raffo. NMPC Strategy for a Quadrotor UAV in a 3D Unknown Environment. In Anais do 14º Simpósio Brasileiro de Automação Inteligente SBAI 2019, Ouro Preto, Brasil, October, 27-30 2019.
  24. P. Abuin, J. L. Godoy, P. S. Rivadeneira, A. Ferramosca, and A. H. González. Control by pulses under MPC schemes, with applications to artificial pancreas. In 18th Workshop on Information Processing and Control (RPIC), Bahia Blanca, Argentina, September, 18-20 2019.
  25. M. Santos, A. Ferramosca, and G. V. Raffo. Tube-based MPC with Nonlinear Control for Load Transportation using a UAV. IFAC-PapersOnLine, 51(25):459–465. In 9th IFAC Symposium on Robust Control Design, ROCOND 2018, September, 1-3 2018.
  26. A. D’Jorge, A. Anderson, A. H. González, and A. Ferramosca. Robust and Stochastic MPC for tracking: a performance comparison. In 26º Congreso Argentino de Control Automático, AADECA 2018, November, 7-9 2018.
  27. A. Anderson, A. D’Jorge, A. Ferramosca, E. Kofman, and A. H. González. i-Steps Closed-Loop Sets for Constrained Linear Systems under Model Predictive Control. In 26º Congreso Argentino de Control Automático, AADECA 2018, November, 7-9 2018.
  28. A. Anderson, A. H. González, A. Ferramosca, and E. Kofman. Finite-time convergence results in robust Model Predictive Control. In European Control Conference, ECC 2018, June 12-15 2018.
  29. P. S. Rivadaneira, M. A. Caicedo, A. H. González, and A. Ferramosca. Impulsive Zone Model Predictive Control (iZMPC) for Therapeutic Treatments: Application to HIV Dynamic (I). In 56th Conference on Decision and Control, CDC 2017, Melbourne, Australia, December, 12-15 2017. Invited Session.
  30. A. H. González, P. S. Rivadaneira, A. Ferramosca, N. Magdaleine, and Claude H. Moog. Impulsive Zone MPC for Type I Diabetic Patients based on a long-term model. IFAC-PapersOnLine, 50(1):14729–14734. In 20th IFAC World Congress, Toulouse, France, July, 9-14 2017.
  31. B. F. Santoro, A. Ferramosca, A. H. González, and D. Odloak. A zone control strategy for stochastic model predictive control. In 2016 American Control Conference, ACC 2016, July 6-8 2016.
  32. P. S. Rivadeneira, A. H. González, and A. Ferramosca. Impulsive zone model predictive control with application to type i diabetic patients. In IEEE Multi-Conference on Systems and Control, MSC 2016, September 19-22 2016.
  33. J. L. Godoy, A. Ferramosca, A. H. González, G. A. Bustos, and J. E. Normey-Rico. Tuning Methodology for Industrial Predictive Controllers Applied to Natural Gas Processing Unit. In IEEE Multi-Conference on Systems and Control, MSC 2016, September 19-22 2016.
  34. A. D’Jorge, A. Anderson, A. H. González, and A. Ferramosca. A Robust Economic MPC for Changing Economic Criterion. In IEEE Multi-Conference on Systems and Control, MSC 2016, September 19-22 2016.
  35. A. Anderson, A.H. González, , and A. Ferramosca E. Kofman. Extended MPC for closed-loop re-identification based on probabilistic invariant sets. In 25th Argentinean Conference on Automatic Control, AADECA 2016, November, 1-3 2016.
  36. P. S. Rivadeneira, A. Ferramosca, and A. H. González. Mpc with state window target control in linear impulsive systems. IFAC-PapersOnLine, 48(23):507–512. In 5th Conference on Nonlinear Model Predictive Control, NMPC’15, September 17-20 2015.
  37. A. Ferramosca A., A.H. González, D. Limon. Economic optimality in MPC: a comparative study. American Control Conference 2015.
  38. A. D’Jorge, A. Ferramosca, and A. H. González. A robust gradient-based MPC for integrating real time optimizer (RTO) with control. In 16th Workshop on Information Processing and Control (RPIC), October 2015.
  39. A. Anderson, A. Ferramosca, A.H. González, and E. Kofman. Probabilistic invariant set for closed-loop re-identification. In 16th Workshop on Information Processing and Control (RPIC), October 2015.
  40. A. Ferramosca A., A.H. González, D. Limon, G. A. Bustos, J. L. Godoy, J. L. Marchetti. On Economic Optimality of Model Predictive Control. AADECA 2014.
  41. A. Ferramosca A., A. H. González., D. Limon, D. Odloak, One-layer robust MPC: a multi-model approach. IFAC World Conference 2014.
  42. D. Limon, T. Alamo, A. Ferramosca, A. H. González, D. Odloak. Integrating the RTO in the MPC: an adaptive gradient-based approach. European Control Conference, ECC’ 2013.
  43. A. H. González, A. Ferramosca, G. A. Bustos, J. L. Marchetti. Model predictive control suitable for closed-loop re-identification. American Control Conference, ACC’ 2013.
  44. G. A. Bustos, A. H. González, A. Ferramosca, and J. L. Marchetti. Application of model predictive control suitable for closed loop re-identification to a polymerization reactor. In 15th Workshop on Information Processing and Control (RPIC), 2013.
  45. T. Alamo, A. Ferramosca, A. H. González, D. Limon, D. Odloak. A gradient based economic MPC suitable for industrial application. AADECA 2012.
  46. A. H. González, G. Bustos, A. Ferramosca, J. L. Marchetti. Model Predictive Control suitable for closed-loop re-identification. AADECA 2012.
  47. A. Ferramosca, D. Limon, A. H. González. Cooperative distributed MPC for tracking. Application to a four tanks system. AADECA 2012.
  48. T. Alamo, A. Ferramosca, A. H. González, D. Limon, D. Odloak. A gradient based strategy for integrating Real Time Optimizer (RTO) with Model Predictive Control (MPC). NMPC 2012.
  49. D. Limon, A. Ferramosca, T. Alamo, A. H. Gonález, D. Odloak. Model Predictive Control for changing economic targets. NMPC 2012.
  50. A. Ferramosca, D. Limon, J.B. Rawlings, E.F. Camacho, Cooperative distributed MPC for tracking. 18th of the IFAC World Congress. Milan, Italy. 28 August – 2 September, 2011.
  51. A. Ferramosca, J.B. Rawlings, D. Limon, E.F. Camacho, Economic MPC for a changing economic criterion. 49th IEEE Conference on Decision and Control, CDC ’10, Atlanta, Georgia, USA. 15-17 December 2010.
  52. D. Limon, I. Alvarado, A. Ferramosca, T. Alamo, E.F. Camacho, Enhanced robust NMPC based on nominal predictions. 8th IFAC Symposium on Nonlinear Control Systems, Nolcos 2010. Bologna, Italy. 1-3 September 2010.
  53. A. Ferramosca A., D. Limon, I. Alvarado, T. Alamo, E.F. Camacho, MPC for tracking of constrained nonlinear systems. 48th IEEE Conference on Decision and Control, CDC ’09, Shanghai, China. 16-18 December 2009.
  54. A. Ferramosca, D. Limon, A.H. Gonzalez, D. Odloak, E.F. Camacho, MPC for tracking target sets. 48th IEEE Conference on Decision and Control, CDC ’09, Shanghai, China. 16-18 December 2009.
  55. A. Ferramosca, D. Limon, F. Fele and E.F. Camacho, L-Band SBQP-based MPC for supermarket refrigeration systems. European Control Conference, ECC’09. Budapest, Hungary, 23-26 Agoust 2009.
  56. A. Ferramosca A., D. Limon, I. Alvarado, T. Alamo, E.F. Camacho, MPC for tracking with optimal closed-loop performance. 47th IEEE Conference on Decision and Control, Cancun, Mexico, December 9-11, 2008.
  57. D. Limon, A. Ferramosca, I. Alvarado, T. Alamo, E.F. Camacho, MPC for tracking of constrained nonlinear systems. 3rd International Worckshop on Assessment and Future Directions of Nonlinear Model Predictive Control, Pavia, Italia, September 5-9, 2008.
  58. I. Alvarado, D. Limon, A. Ferramosca, T. Alamo, E.F. Camacho, Robust tubed-based MPC for tracking applied to the quadruple-tank process. IEEE Multi-conference on Systems and Control, San Antonio (Texas), USA, September 3-5, 2008.
  59. A. Ferramosca, D. Limon, I. Alvarado, T. Alamo, E.F. Camacho, Optimal MPC for tracking of constrained linear systems. CONTROLO’2008, Vila Real, Portugal, July 21-23, 2008.
  60. A. Ferramosca, I. Alvarado, D. Limón, E. F. Camacho, MPC para el seguimiento del ángulo de cabeceo de un helicóptero.XXVIII Jornadas de Automática, September 05-07, Huelva, Spain, 2007.
  61. C. Aurora, M. Diehl, A. Ferramosca, L. Magni, A. Miotti, R. Scattolini, Nonlinear model predictive control for combined cycle power plants. IFAC NOLCOS 04, Stuttgart, Germany, September 01-03, 2004.
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