The condition for the maximum of the generalized power function in the problem of forming a multi-mode control law with limitation

Andrey Kostoglotov; Sergey Lazarenko; Alexander Agapov; Zoya Lyashchenko

doi:10.1051/e3sconf/202021001003

All issues

Volume 210 (2020)

E3S Web Conf., 210 (2020) 01003

References

Open Access

Issue		E3S Web Conf. Volume 210, 2020 Innovative Technologies in Science and Education (ITSE-2020)


Article Number		01003
Number of page(s)		9
Section		Environmental Engineering
DOI		https://doi.org/10.1051/e3sconf/202021001003
Published online		04 December 2020

S. N. Vasiliev, Yu. I. Kudinov, F. F. Pashchenko, I. S. Durgaryan, A. Yu. Kelina, I. Yu. Kudinov, et al., Intelligent control systems and fuzzy regulators, Part II. Learning fuzzy regulators fuzzy PID regulators Sensors and systems, 3(211), 3-12 (2017) [Google Scholar]
B. Wang, J. Xu, B. Cao, Q. Li, Q. Yang, Adaptive Mode Control Strategy of a Multimode Hybrid Energy Storage System. Energy Procedia, 88, 627-633 (2016) ISSN 1876-6102, https://doi.org/10.1016/j.egypro.2016.06.089. [CrossRef] [Google Scholar]
H. I. Jaafar, Z. Mohamed, M. A. Shamsudin, N. A. Mohd Subha, L. Ramli, A. M. Abdullahi, Model reference command shaping for vibration control of multimode flexible systems with application to a double-pendulum overhead crane. Mechanical Systems and Signal Processing, 115, 677-695 (2019) ISSN 0888-3270, https://doi.org/10.1016/j.ymssp.2018.06.005. [CrossRef] [Google Scholar]
H. Wu, J. Zhao, Self-adaptive deep learning for multimode process monitoring, Computers & Chemical Engineering, 141, 107024 (2020) ISSN 0098-1354, https://doi.org/10.1016/j.compchemeng.2020.107024. [CrossRef] [Google Scholar]
S. Nüesch, A. G. Stefanopoulou, Multimode combustion in a mild hybrid electric vehicle. Part 1: Supervisory control, Control Engineering Practice, 57, 99-110 (2016) ISSN 0967-0661, https://doi.org/10.1016/j.conengprac.2016.09.002. [CrossRef] [Google Scholar]
T. Hausberger, A. Kugi, A. Eder, W. Kemmetmüller, High-speed nonlinear model predictive control of an interleaved switching DC/DC-converter, Control Engineering Practice, 103, 104576 (2020) ISSN 0967-0661, https://doi.org/10.1016/j.conengprac.2020.104576. [CrossRef] [Google Scholar]
J. B. Rawlings, D. Q. Mayne, M. Diehl, Model Predictive Control: Theory, Computation, and Design (Nob Hill Publishing, 2017) [Google Scholar]
S. Vazquez, J. Rodriguez, M. Rivera, L. G. Franquelo, M. Norambuena, “Model Predictive Control for Power Converters and Drives: Advances and Trends,” in IEEE Transactions on Industrial Electronics, 64(2), 935-947 (2017) doi: 10.1109/TIE.2016.2625238. [CrossRef] [Google Scholar]
W. Kemmetmüller, S. Eberharter, A. Kugi, Quasi optimal feedforward control of a very low frequency high-voltage test system, IFAC Proceedings Volumes, 47(3), 11623-11628 (2014) ISSN 1474-6670, ISBN 9783902823625, https://doi.org/10.3182/20140824-6-ZA-1003.00356. [CrossRef] [Google Scholar]
A. A. Kostoglotov, S. V. Lazarenko, I. V. Deryabkin, Combined maximum principle as the part of intellectualization of control systems for a suspension of vehicles. Advances in Intelligent Systems and Computing, 679, 150 (2017) [CrossRef] [Google Scholar]
A. Kostoglotov, S. Lazarenko, I. Deryabkin, O. Manaenkova, A. Kuzin, I. Pugachev, Fuzzy control laws in the basis of solutions of synthesis problems of the combined maximum principle. Advances in Intelligent Systems and Computing 679, 322-329 (2018) [CrossRef] [Google Scholar]
A. Kostoglotov, S. Lazarenko, I. Deryabkin, A. Yachmenov, O. Kuznetcova, Combined maximum principle as the basis of intellectualization of control systems for a suspension of vehicles. Advances in Intelligent Systems and Computing, 679, 150-155 (2018) [CrossRef] [Google Scholar]
A. Kostoglotov, V. Taran, V. Trofimenko, Fuzzy topological approach to a solid control task. Advances in Intelligent Systems and Computing, 874, 373-381 (2019) [CrossRef] [Google Scholar]
A. Kostoglotov, S. Lazarenko, A. Agapov, Z. Lyaschenko, I. Pavlova, Designing the knowledge base for the intelligent inertial regulator based on quasi-optimal synthesis of controls using the combined maximum principle. Advances in Intelligent Systems and Computing, 874, 190-200 (2019) [CrossRef] [Google Scholar]
I. Anan’evskii, S. Reshmin, Decomposition-based continuous control of mechanical systems. Journal of Computer and Systems Sciences International, 53, 473-486. (2014) 10.1134/S1064230714040029. [CrossRef] [Google Scholar]
W. Nakpim, S. V. Meleshko, Conservation laws of the one-dimensional equations of relativistic gas dynamics in Lagrangian coordinates. International Journal of Non-Linear Mechanics, 124, 103496 (2020) https://doi.org/10.1016/j.ijnonlinmec.2020.103496. [CrossRef] [Google Scholar]

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[1] S. N. Vasiliev, Yu. I. Kudinov, F. F. Pashchenko, I. S. Durgaryan, A. Yu. Kelina, I. Yu. Kudinov, et al., Intelligent control systems and fuzzy regulators, Part II. Learning fuzzy regulators fuzzy PID regulators Sensors and systems, 3(211), 3-12 (2017) [Google Scholar]

[2] B. Wang, J. Xu, B. Cao, Q. Li, Q. Yang, Adaptive Mode Control Strategy of a Multimode Hybrid Energy Storage System. Energy Procedia, 88, 627-633 (2016) ISSN 1876-6102, https://doi.org/10.1016/j.egypro.2016.06.089. [CrossRef] [Google Scholar]

[3] H. I. Jaafar, Z. Mohamed, M. A. Shamsudin, N. A. Mohd Subha, L. Ramli, A. M. Abdullahi, Model reference command shaping for vibration control of multimode flexible systems with application to a double-pendulum overhead crane. Mechanical Systems and Signal Processing, 115, 677-695 (2019) ISSN 0888-3270, https://doi.org/10.1016/j.ymssp.2018.06.005. [CrossRef] [Google Scholar]

[4] H. Wu, J. Zhao, Self-adaptive deep learning for multimode process monitoring, Computers & Chemical Engineering, 141, 107024 (2020) ISSN 0098-1354, https://doi.org/10.1016/j.compchemeng.2020.107024. [CrossRef] [Google Scholar]

[5] S. Nüesch, A. G. Stefanopoulou, Multimode combustion in a mild hybrid electric vehicle. Part 1: Supervisory control, Control Engineering Practice, 57, 99-110 (2016) ISSN 0967-0661, https://doi.org/10.1016/j.conengprac.2016.09.002. [CrossRef] [Google Scholar]

[6] T. Hausberger, A. Kugi, A. Eder, W. Kemmetmüller, High-speed nonlinear model predictive control of an interleaved switching DC/DC-converter, Control Engineering Practice, 103, 104576 (2020) ISSN 0967-0661, https://doi.org/10.1016/j.conengprac.2020.104576. [CrossRef] [Google Scholar]

[7] J. B. Rawlings, D. Q. Mayne, M. Diehl, Model Predictive Control: Theory, Computation, and Design (Nob Hill Publishing, 2017) [Google Scholar]

[8] S. Vazquez, J. Rodriguez, M. Rivera, L. G. Franquelo, M. Norambuena, “Model Predictive Control for Power Converters and Drives: Advances and Trends,” in IEEE Transactions on Industrial Electronics, 64(2), 935-947 (2017) doi: 10.1109/TIE.2016.2625238. [CrossRef] [Google Scholar]

[9] W. Kemmetmüller, S. Eberharter, A. Kugi, Quasi optimal feedforward control of a very low frequency high-voltage test system, IFAC Proceedings Volumes, 47(3), 11623-11628 (2014) ISSN 1474-6670, ISBN 9783902823625, https://doi.org/10.3182/20140824-6-ZA-1003.00356. [CrossRef] [Google Scholar]

[10] A. A. Kostoglotov, S. V. Lazarenko, I. V. Deryabkin, Combined maximum principle as the part of intellectualization of control systems for a suspension of vehicles. Advances in Intelligent Systems and Computing, 679, 150 (2017) [CrossRef] [Google Scholar]

[11] A. Kostoglotov, S. Lazarenko, I. Deryabkin, O. Manaenkova, A. Kuzin, I. Pugachev, Fuzzy control laws in the basis of solutions of synthesis problems of the combined maximum principle. Advances in Intelligent Systems and Computing 679, 322-329 (2018) [CrossRef] [Google Scholar]

[12] A. Kostoglotov, S. Lazarenko, I. Deryabkin, A. Yachmenov, O. Kuznetcova, Combined maximum principle as the basis of intellectualization of control systems for a suspension of vehicles. Advances in Intelligent Systems and Computing, 679, 150-155 (2018) [CrossRef] [Google Scholar]

[13] A. Kostoglotov, V. Taran, V. Trofimenko, Fuzzy topological approach to a solid control task. Advances in Intelligent Systems and Computing, 874, 373-381 (2019) [CrossRef] [Google Scholar]

[14] A. Kostoglotov, S. Lazarenko, A. Agapov, Z. Lyaschenko, I. Pavlova, Designing the knowledge base for the intelligent inertial regulator based on quasi-optimal synthesis of controls using the combined maximum principle. Advances in Intelligent Systems and Computing, 874, 190-200 (2019) [CrossRef] [Google Scholar]

[15] I. Anan’evskii, S. Reshmin, Decomposition-based continuous control of mechanical systems. Journal of Computer and Systems Sciences International, 53, 473-486. (2014) 10.1134/S1064230714040029. [CrossRef] [Google Scholar]

[16] W. Nakpim, S. V. Meleshko, Conservation laws of the one-dimensional equations of relativistic gas dynamics in Lagrangian coordinates. International Journal of Non-Linear Mechanics, 124, 103496 (2020) https://doi.org/10.1016/j.ijnonlinmec.2020.103496. [CrossRef] [Google Scholar]