Abstract
Driven by the rapid development of economy, there are challenges for MPC strategies to meet stricter and higher requirements in practice [1, 2]. In order to enhance the control performance of MPC schemes, many significant ideas are proposed, such as the introduction of novel models, the combination with other algorithms, etc. [3,4,5,6,7,8].
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References
Dragicevic, T. (2018). Model predictive control of power converters for robust and fast operation of AC microgrids. IEEE Transactions on Power Electronics, 33(7), 6304–6317.
Dias, L. S., Pattison, R. C., Tsay, C., Baldea, M., & Ierapetritou, M. G. (2018). A simulation-based optimization framework for integrating scheduling and model predictive control, and its application to air separation units. Computers & Chemical Engineering, 113, 139–151.
Morstyn, T., Hredzak, B., Aguilera, R. P., & Agelidis, V. G. (2018). Model predictive control for distributed microgrid battery energy storage systems. IEEE Transactions on Control Systems Technology, 26(3), 1107–1114.
Papangelis, L., Debry, M. S., Prevost, T., Panciatici, P., & Van Cutsem, T. (2018). Decentralized model predictive control of voltage source converters for AC frequency containment. International Journal of Electrical Power & Energy Systems, 98, 342–349.
Huang, J. J., Yang, B., Guo, F. H., Wang, Z. F., Tong, X. Q., Zhang, A. M., et al. (2018). Priority sorting approach for modular multilevel converter based on simplified model predictive control. IEEE Transactions on Industrial Electronics, 65(6), 4819–4830.
Wang, X. F., Yang, L. X., Sun, Y., & Deng, K. (2017). Adaptive model predictive control of nonlinear systems with state-dependent uncertainties. International Journal of Robust and Nonlinear Control, 27(17), 4138–4153.
Gholaminejad, T., Khaki-Sedigh, A., & Bagheri, P. (2017). Direct adaptive model predictive control tuning based on the first-order plus dead time models. IET Control Theory and Applications, 11(16), 2858–2869.
Geyer, T., & Quevedo, D. E. (2015). Performance of multistep finite control set model predictive control for power electronics. IEEE Transactions on Power Electronics, 30(3), 1633–1644.
Albalawi, F., Durand, H., & Christofides, P. D. (2017). Process operational safety using model predictive control based on a process Safeness Index. Computers & Chemical Engineering, 104, 76–88.
Wang, Z. M., & Ong, C. J. (2017). Distributed model predictive control of linear discrete-time systems with local and global constraints. Automatica, 81, 184–195.
Bo, T. I., & Johansen, T. A. (2017). Battery power smoothing control in a marine electric power plant using nonlinear model predictive control. IEEE Transactions on Control Systems Technology, 25(4), 1449–1456.
Xu, Q. Q., & Dubljevic, S. (2017). Linear model predictive control for transport-reaction processes. AIChE Journal, 63(7), 2644–2659.
Johansen, T. A. (2017). Toward dependable embedded model predictive control. IEEE Systems Journal, 11(2), 1208–1219.
Zhang, R. D., & Gao, F. R. (2015). An improved decoupling structure based state space MPC design with improved performance. Systems & Control Letters, 75, 77–83.
Zhang, R. D., Zou, Q., Cao, Z. X., & Gao, F. R. (2017). Design of fractional order modeling based extended non-minimal state space MPC for temperature in an industrial electric heating furnace. Journal of Process Control, 56, 13–22.
Zhang, R. D., Lu, R. Q., Xue, A. K., & Gao, F. R. (2014). Predictive functional control for linear systems under partial actuator faults and application on an injection molding batch process. Industrial & Engineering Chemistry Research, 53(2), 723–731.
Zhang, R. D., Zou, H. B., Xue, A. K., & Gao, F. R. (2014). GA based predictive functional control for batch processes under actuator faults. Chemometrics and Intelligent Laboratory Systems, 137(15), 67–73.
Zhang, R. D., Lu, J. Y., Qu, H. Y., & Gao, F. R. (2014). State space model predictive fault-tolerant control for batch processes with partial actuator failure. Journal of Process Control, 24(5), 613–620.
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Zhang, R., Xue, A., Gao, F. (2019). Model Predictive Control Performance Optimized by Genetic Algorithm. In: Model Predictive Control. Springer, Singapore. https://doi.org/10.1007/978-981-13-0083-7_9
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DOI: https://doi.org/10.1007/978-981-13-0083-7_9
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