DOI: 10.15507/2658-4123.032.202202.279-294
Developing a Quasi-Optimal, in Terms of Transition Time and Energy Consumption, Closed-Loop Control System for an Electrical Installation
Valeriy S. Khoroshavin
Professor of the Chair of Electric Drive and Industrial Equipment Automation, Vyatka State University (36 Moskovskaya St., Kirov 610000, Russian Federation), Dr.Sci. (Engr.), ORCID: https://orcid.org/0000-0002-4355-3866, Researcher ID: G-5298-2018, This email address is being protected from spambots. You need JavaScript enabled to view it.
Viktor S. Grudinin
Associate Professor of the Chair of Electric Drive and Industrial Equipment Automation, Vyatka State University (36 Moskovskaya St., Kirov 610000, Russian Federation), Cand.Sci. (Engr.), ORCID: https://orcid.org/0000-0002-1615-6195, Researcher ID: G-5550-2018, This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Introduction. The efficiency and normal work of electrotechnological processes and installations in their operation dynamic modes is characterized by the time of transition from initial to final state, low energy consumption, accuracy in transients and stability of the desired final state. It is proposed, from a single position on the basis of special optimal control, to combine transition and stabilization systems both in terms of determining the control algorithm with minimal energy consumption in the function of the object states and determining the parameters and conditions of movement with minimal deviation from a given trajectory providing the optimal transmission time and energy saving in a stable closed system of an object control.
Materials and Methods. The principle of maximum is used as the main method for finding optimal program control, which for the study of special modes was supplemented with the apparatus of the position generality conditions for nonlinear objects with the coordinate space expansion, taking into account the occurrence of time and optimality criterion. The position generality apparatus is also used to solve energy-saving problems through using linearization in a large source object. Quasi-optimality in terms of transition time and energy consumption is achieved through minimizing energy according to the program motion parameter, which has a contradictory effect on the transition time and control amplitude.
Results. To assess computational difficulties, transition time, energy saving, accuracy and stability, an example of inertial object control according to various criteria is given. The structure of a closed quasi-optimal system with stationary feedback, which is simple in technical implementation, is obtained.
Discussion and Conclusion. The formalization of the approach to the construction of quasi-optimal systems based on the position generality allows it to be used in multi-criteria optimization tasks and computer-aided design systems for energy-intensive industrial, transport, and agricultural electrical installations.
Keywords: electrical installation, optimal control, time transition, energy consumption, program motion, maximum principle, special control, position generality conditions, stability
Conflict of interest: The authors declare no conflict of interest.
For citation: Khoroshavin V.S., Grudinin V.S. Developing a Quasi-Optimal, in Terms of Transition Time and Energy Consumption, Closed-Loop Control System for an Electrical Installation. Engineering Technologies and Systems. 2022;32(2):279‒294. doi: https://doi.org/10.15507/2658-4123.032.202202.279-294
Contribution of the authors:
V. S. Khoroshavin – problem statement and choice of solution methods.
V. S. Grudinin – material analysis and process modeling.
All authors have read and approved the final manuscript.
Submitted 25.01.2022; approved after reviewing 11.02.2022;
accepted for publication 03.03.2022
REFERENCES
1. Domanov V.I., Pevcheva E.V. Analysis of the Greenhouse Complex Main Power Grid Nodes and the Ways to Reduce Energy Consumption. Industrial Automatic Control Systems and Controllers. 2017;(3):3‒10. Available at: https://www.elibrary.ru/item.asp?id=29115500 (accessed 20.01.2022). (In Russ., abstract in Eng.)
2. Lovchakov V.I. Approximation Approach to Synthesis of Control Systems Based on Optimal Program Control. News of the Tula State University. Technical Sciences. 2017;(3):225‒236. Available at: https://clck.ru/h7ejP (accessed 20.01.2022). (In Russ., abstract in Eng.)
3. Nikol’skii M.S. Singular Sets of Extremal Controls in Optimal Control Problems. Proceedings of the Steklov Institute of Mathematics. 2019;304:236‒240. doi: https://doi.org/10.4213/tm3970
4. Tsintsadze Z. [Computation of Particularly Optimal Control in Quasi-Linear Controlled Systems with Mixed Constraints]. Kompyuternye nauki i telekommunikatsii. 2005;(2):71‒73. Available at: http://gesj.internet-academy.org.ge/ru/list_aut_artic_ru.php?b_sec=&list_aut=1248 (accessed 24.01.2022). (In Russ.)
5. Gao Z. On Discrete Time Optimal Control: A Closed-Form Solution. In: Proceeding of the 2004 American Control Conference (30 June – 2 July 2004). Boston; 2004. p. 52‒58. Available at: https://folk.ntnu.no/skoge/prost/proceedings/acc04/Papers/0009_WeA02.6.pdf (accessed 24.01.2022).
6. Zhang H., Xie Y., Xiao G., et al. A Simple Discrete-Time Tracking Differentiator and Its Application to Speed and Position Detection System for a Maglev Train. IEEE Transactions on Control Systems Technology. 2018;27(4):1728‒1734. doi: https://doi.org/10.1109/TCST.2018.2832139
7. Filimonov N.B. The Problem of Quality of Control Processes: Change of an Optimizing Paradigm. Mechatronics, Automation, Management. 2010;(12):2‒10. Available at: https://www.elibrary.ru/item.asp?id=15510887 (accessed 20.01.2022). (In Russ., abstract in Eng.)
8. Tabunshchikov Yu.A., Brodach M.M. [Experimental Study of Optimal Energy Management]. Ventilation, Heating, Air Conditioning, Heat Supply and Building Thermal Physics. 2006;(1):32‒36.Available at: https://www.abok.ru/for_spec/articles.php?nid=3132 (accessed 20.01.2022). (In Russ.)
9. Pleshivtseva Yu.E., Popov A.V., Dyakonov A.I. Two-Dimensional Problem of Optimal with Respect to Typical Quality Criteria Control of through Induction Heating Processes. Samara State Technical University Bulletin. Technical Sciences Series. 2014;(2):148‒163. Available at: https://journals.eco-vector.com/1991-8542/article/view/19977/16230 (accessed 25.01.2022). (In Russ., abstract in Eng.)
10. Panferov V.I., Anisimova Ye.Yu., Nagornaya A.N. [On the Optimal Management of the Thermal Regime of Buildings]. Bulletin of South Ural State University. Power Engineering Series. 2007;(20):3‒9. Available at: https://cyberleninka.ru/article/n/ob-optimalnom-upravlenii-teplovym-rezhimom-zdaniy (accessed 20.01.2022). (In Russ., abstract in Eng.)
11. Biyik E., Kahraman A. A Predictive Control Strategy for Optimal Management of Peak Load, Thermal Comfort, Energy Storage and Renewables in Multi-Zone Buildings. Journal of Building Engineering. 2019;25. Available at: https://app.dimensions.ai/details/publication/pub.1117015634 (accessed 20.01.2022).
12. Khoroshavin V.S. Comparing Optimal Control Algorithms by Time and Minimum Resources Heat. News of the Tula State University. Technical Sciences. 2020;(7):211‒216. Available at: https://www.elibrary.ru/item.asp?id=43895260 (accessed 20.01.2022). (In Russ., abstract in Eng.)
13. Khoroshavin V.S., Grudinin V.S. Synthesis of Programmed Motion Based on Special Optimal Control. Mechatronics, Automation, Control. 2021;22(8):395‒403. (In Russ., abstract in Eng.) doi: https://doi.org/10.17587/mau.22.395-403
14. Dubrovin V.S., Nikulin V.V. [A Way of Constructing Controlled Function Generators]. High Tech in Earth Space Research. 2013;5(2):16‒23. Available at: https://www.elibrary.ru/item.asp?id=22897398 (accessed 24.01.2022). (In Russ.)
15. Moreau L., Aeyels D. Periodic Output Feedback Stabilization of Single-Input Single-Output Continuous-Time Systems with Odd Relative Degree. Systems & Control Letters. 2004;51(5):395‒406. doi: https://doi.org/10.1016/j.sysconle.2003.10.001
16. Shumafov M.M. Stabilization of Linear Control Systems. Pole Assignment Problem. A Survey. Vestnik SPbGU. Matematika. Mekhanika. Astronomiya. 2019;6(4):564‒591. (In Russ., abstract in Eng.) doi: https://doi.org/10.21638/11701/spbu01.2019.404
17. Borkovskaya I.M., Pyzhkova O.N. The Problems of Control and Stabilization for Hybrid Dynamic Systems. Trudy BGTU. Seriya 3: Fiziko-matematicheskie nauki i informatika. 2018;(2):5‒9. Available at: https://elibrary.ru/item.asp?id=36367417 (accessed 24.01.2022). (In Russ., abstract in Eng.)
18. Kolesnikov V.L., Brakovich A.I., Zhuk Ya.A. [Solving Pareto-Optimal Multicriteria Problems]. Trudy BGTU. Seriya 3: Fiziko-matematicheskie nauki i informatika. 2014;(6):128‒130. Available at: https://elibrary.ru/item.asp?id=27707178 (accessed 24.01.2022). (In Russ.)
19. Mahmoud M.S., AL-Sunni F.M. Control and Optimization of Distributed Generation Systems. Cham: Springer; 2015. 578 p. doi: https://doi.org/10.1007/978-3-319-16910-1_1 (accessed 20.01.2022).
20. Shamshiri R.R., Jones J.W., Thorp K.R., et al. Review of Optimum Temperature, Humidity, and Vapour Pressure Deficit for Microclimate Evaluation and Control in Greenhouse Cultivation of Tomato: a Review. International Agrophysics. 2018;(32):287‒302. doi: https://doi.org/10.1515/intag-2017-0005
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