Stable nonlinear model predictive control with a changing economic criterion

References

• Amrit, R., Rawlings, J. B., & Angeli, D. (2011). Economic optimization using model predictive control with a terminal cost. Annual Reviews in Control, 35(2), 178–186. https://doi.org/10.1016/j.arcontrol.2011.10.011
   Web of Science ®Google Scholar
• Angeli, D., Amrit, R., & Rawlings, J. B. (2011). On average performance and stability of economic model predictive control. IEEE Transactions on Automatic Control, 57(7), 1615–1626. https://doi.org/10.1109/TAC.2011.2179349
   Web of Science ®Google Scholar
• Cui, J., Chai, T., & Liu, X. (2020). Deep-neural-network-based economic model predictive control for ultrasupercritical power plant. IEEE Transactions on Industrial Informatics, 16(9), 5905–5913. https://doi.org/10.1109/TII.9424
   Web of Science ®Google Scholar
• Darby, M. L., Nikolaou, M., Jones, J., & Nicholson, D. (2011). RTO: An overview and assessment of current practice. Journal of Process Control, 21(6), 874–884. https://doi.org/10.1016/j.jprocont.2011.03.009
   Web of Science ®Google Scholar
• de Oliveira, R. D., Guedes, M. N., Matias, J., & Le Roux, G. A. C. (2021). Nonlinear predictive control of a bioreactor by surrogate model approximation of flux balance analysis. Industrial & Engineering Chemistry Research, 60(40), 14464–14475. https://doi.org/10.1021/acs.iecr.1c01242
   Web of Science ®Google Scholar
• Diehl, M., Amrit, R., & Rawlings, J. B. (2010). A Lyapunov function for economic optimizing model predictive control. IEEE Transactions on Automatic Control, 56(3), 703–707. https://doi.org/10.1109/TAC.2010.2101291
   Web of Science ®Google Scholar
• D'jorge, A., Anderson, A., González, A. H., & Ferramosca, A. (2018). A robust economic MPC for changing economic criterion. International Journal of Robust and Nonlinear Control, 28(15), 4404–4423. https://doi.org/10.1002/rnc.4243
   Web of Science ®Google Scholar
• Ellis, M., & Christofides, P. D. (2014). Economic model predictive control with time-varying objective function for nonlinear process systems. AIChE Journal, 60(2), 507–519. https://doi.org/10.1002/aic.v60.2
   Web of Science ®Google Scholar
• Ellis, M., Durand, H., & Christofides, P. D. (2014). A tutorial review of economic model predictive control methods. Journal of Process Control, 24(8), 1156–1178. https://doi.org/10.1016/j.jprocont.2014.03.010
   Web of Science ®Google Scholar
• Ellis, M., Liu, J., & Christofides, P. D. (2017). Economic model predictive control: Theory, formulations and chemical process applications. Springer.
   Google Scholar
• Fagiano, L., & Teel, A. R. (2013). Generalized terminal state constraint for model predictive control. Automatica, 49(9), 2622–2631. https://doi.org/10.1016/j.automatica.2013.05.019
   Web of Science ®Google Scholar
• Falugi, P. (2015). Model predictive control for tracking randomly varying references. International Journal of Control, 88(4), 745–753. https://doi.org/10.1080/00207179.2014.972464
   Web of Science ®Google Scholar
• Ferramosca, A., Limon, D., & Camacho, E. F. (2014). Economic MPC for a changing economic criterion for linear systems. IEEE Transactions on Automatic Control, 59(10), 2657–2667. https://doi.org/10.1109/TAC.2014.2326013
   Web of Science ®Google Scholar
• Griffith, D. W., Zavala, V. M., & Biegler, L. T. (2017). Robustly stable economic NMPC for non-dissipative stage costs. Journal of Process Control, 57, 116–126. https://doi.org/10.1016/j.jprocont.2017.06.016
   Web of Science ®Google Scholar
• Gros, S., & Zanon, M. (2022). Economic MPC of Markov decision processes: Dissipativity in undiscounted infinite-horizon optimal control. Automatica, 146. https://doi.org/10.1016/j.automatica.2022.110602
   Web of Science ®Google Scholar
• Grüne, L. (2013). Economic receding horizon control without terminal constraints. Automatica, 49(3), 725–734. https://doi.org/10.1016/j.automatica.2012.12.003
   Web of Science ®Google Scholar
• Grüne, L., & Stieler, M. (2014). Asymptotic stability and transient optimality of economic MPC without terminal conditions. Journal of Process Control, 24(8), 1187–1196. https://doi.org/10.1016/j.jprocont.2014.05.003
   Web of Science ®Google Scholar
• He, D., Li, H., & Du, H. (2021). Lexicographic multi-objective MPC for constrained nonlinear systems with changing objective prioritization. Automatica, 125, Article 109433. https://doi.org/10.1016/j.automatica.2020.109433
   Web of Science ®Google Scholar
• He, D., Qiu, T., & Lu, L. (2019). Input-to-state stability of contractive EMPC of non-linear systems with bounded disturbances[J]. IET Control Theory & Applications, 13(5), 651–658. https://doi.org/10.1049/cth2.v13.5
   Web of Science ®Google Scholar
• He, D., Sun, J., & Yu, L. (2016). Economic MPC with a contractive constraint for nonlinear systems. International Journal of Robust and Nonlinear Control, 26(18), 4072–4087. https://doi.org/10.1002/rnc.v26.18
   Web of Science ®Google Scholar
• He, D., & Xu, S. (2021). Lyapunov-based EMPC of constrained nonlinear systems with changing economic costs. Asian Journal of Control, 23(4), 1772–1781. https://doi.org/10.1002/asjc.v23.4
   Web of Science ®Google Scholar
• Heidarinejad, M., Liu, J., & Christofides, P. D. (2012). Economic model predictive control of nonlinear process systems using Lyapunov techniques. AIChE Journal, 58(3), 855–870. https://doi.org/10.1002/aic.v58.3
   Web of Science ®Google Scholar
• Köhler, J., Müller, M. A., & Allgöwer, F. (2019). A nonlinear model predictive control framework using reference generic terminal ingredients. IEEE Transactions on Automatic Control, 65(8), 3576–3583. https://doi.org/10.1109/TAC.9
   Web of Science ®Google Scholar
• Köhler, J., Müller, M. A., & Allgöwer, F. (2020). A nonlinear tracking model predictive control scheme for dynamic target signals. Automatica, 118. https://doi.org/10.1016/j.automatica.2020.109030
   Web of Science ®Google Scholar
• Limon, D., Alamo, T., de la Peña, D. M., Zeilinger, M. N., Jones, C. N., & Pereira, M. (2016). MPC for tracking periodic references. IEEE Transactions on Automatic Control, 61(4), 1123–1128. https://doi.org/10.1109/TAC.2015.2461811
   Web of Science ®Google Scholar
• Limón, D., Alvarado, I., Alamo, T., & Camacho, E. F. (2008). MPC for tracking piecewise constant references for constrained linear systems. Automatica, 44(9), 2382–2387. https://doi.org/10.1016/j.automatica.2008.01.023
   Web of Science ®Google Scholar
• Limón, D., Ferramosca, A., Alvarado, I., & Alamo, T. (2018). Nonlinear MPC for tracking piece-wise constant reference signals. IEEE Transactions on Automatic Control, 63(11), 3735–3750. https://doi.org/10.1109/TAC.2018.2798803
   Web of Science ®Google Scholar
• Limon, D., Pereira, M., De La Peña, D. M., Alamo, T., & J. M. Grosso (2014). Single-layer economic model predictive control for periodic operation. Journal of Process Control, 24(8), 1207–1224. https://doi.org/10.1016/j.jprocont.2014.03.013
   Web of Science ®Google Scholar
• Lopez, J. A., Bucala, V., & Villar, M. A. (2010). Application of dynamic optimization techniques for poly (β-hydroxybutyrate) production in a fed-batch bioreactor. Industrial & Engineering Chemistry Research, 49(4), 1762–1769. https://doi.org/10.1021/ie9006547
   Web of Science ®Google Scholar
• Magni, L., & Scattolini, R. (2007). Robustness and robust design of MPC for nonlinear systems. In Assessment and future directions of nonlinear model predictive control (pp. 239–254). Springer.
   Google Scholar
• Magni, L., Scattolini, R., & Tanelli, M. (2008). Switched model predictive control for performance enhancement. International Journal of Control, 81(12), 1859–1869. https://doi.org/10.1080/00207170801910417
   Web of Science ®Google Scholar
• Müller, M. A., & Allgöwer, F. (2012). Improving performance in model predictive control: Switching cost functionals under average dwell-time. Automatica, 48(2), 402–409. https://doi.org/10.1016/j.automatica.2011.11.005
   Web of Science ®Google Scholar
• Müller, M. A., Angeli, D., Allgöwer, F., Amrit, R., & Rawlings, J. B. (2014). Convergence in economic model predictive control with average constraints. Automatica, 50(12), 3100–3111. https://doi.org/10.1016/j.automatica.2014.10.059
   Web of Science ®Google Scholar
• Munteanu, I., Bratcu, A. I., Cutululis, N. A., & CeangĂ, E. (2008). Optimal control of wind energy systems: towards a global approach. Springer.
   Google Scholar
• Rao, C. V. (2013). Exploiting market fluctuations and price volatility through feedback control. Computers & Chemical Engineering, 51, 181–186. https://doi.org/10.1016/j.compchemeng.2012.06.022
   Web of Science ®Google Scholar
• Rawlings, J. B., & Amrit, R. (2009). Optimizing process economic performance using model predictive control. In Nonlinear model predictive control (pp. 119–138). Springer.
   Google Scholar
• Rawlings, J. B., & Mayne, D. Q. (2009). Model predictive control theory and design. Nob Hill Publishing, LLC.
   Google Scholar
• Tian, H., Lu, Q., Gopaluni, B. R., Zavala, V. M., & Olson, J. A. (2019). An economic model predictive control framework for mechanical pulping processes. Control Engineering Practice, 85, 100–109. https://doi.org/10.1016/j.conengprac.2019.01.008
   Web of Science ®Google Scholar
• Wang, Z., & Hu, G. (2018). Economic MPC of nonlinear systems with nonmonotonic Lyapunov functions and its application to HVAC control. International Journal of Robust and Nonlinear Control, 28(6), 2513–2527. https://doi.org/10.1002/rnc.4033
   Web of Science ®Google Scholar
• Zavala, V. M. (2015). A multiobjective optimization perspective on the stability of economic MPC. IFAC-PapersOnLine, 48(8), 974–980. https://doi.org/10.1016/j.ifacol.2015.09.096
   Google Scholar
• Zhao, H., Shen, J., Li, Y., & Bentsman, J. (2017). Preference adjustable multi-objective NMPC: An unreachable prioritized point tracking method. ISA Transactions, 66, 134–142. https://doi.org/10.1016/j.isatra.2016.09.020
   PubMed Web of Science ®Google Scholar