519.6:629.7.02 Software environment dgsSynchCAD for modeling and computer-aided heuristic optimization of throttle synchronizing hydrosystems

Bushuev A. Y. (Bauman Moscow State Technical University), Ivanov M. Y., Korotaev D. V. (LLC Scientific-production association «INKOR»), Resh G. F.

SYNCHRONIZATION SYSTEM, HYDRAULIC CYLINDER, UNREGULATED THROTTLE, MATHEMATICAL MODELING, FINITE DIFFERENCE METHOD, LAGRANGE’S EQUATION OF THE SECOND KIND, HEURISTIC OPTIMIZATION, GENETIC ALGORITHM, CLASS DIAGRAM, COMPUTATIONAL EXPERIMENT


doi: 10.18698/2309-3684-2020-1-103117


A software environment was developed for computer-aided design of optimal throttle hydraulic synchronization systems of actuators of various functional purposes operating under conditions of external alternating-sign force effects. The criterion of an optimization procedure was the minimization of a mismatch time of relative movement of actuators during operation. A compute core of an object-oriented code was constructed on the basis of a dynamic mathematical model of a synchronization system consisting of four power cylinders. A model problem was solved with the help of the created software environment. This model problem demonstrated the efficiency of the proposed multidimensional optimization process. The methodology was based on the use of the well-known heuristic method (binary coded genetic algorithm) and the subsequent improvement (in the sense of a given objective functional) of the obtained solution by a method on the basis of the Hooke-Jeeves algorithm. Recommendations on the practical application of the software and mathematical support for achieving the best convergence to the extreme value of a vector of controlled parameters were formulated.


[1] Popov D.N. Mekhanika gidro- i pnevmoprivodov [Mechanics of Hydraulic and Pneumatic Actuators]. Moscow, BMSTU Publ., 2002, 320 p.
[2] Casey B., Tumarkin M. How to Synchronize Hydraulic Cylinders. Published by HydraulicSupermarket.com, 2006, p. 8. Available at: https://www.hydraulicsupermarket.com/synchronization.html
[3] Artemenko Y.N., Karpenko A.P., Belonozhko P.P. Features of manipulator dynamics modeling into account a movable platform. Series Studies in Systems, Decision and Control, 2016, vol. 49, pp. 177–190.
[4] Artemenko Y.N., Karpenko A.P., Belonozhko P.P. Synthesis of control of hinged bodies relative motion ensuring move of orientable body to necessary absolute position. Series Studies in Systems, Decision and Control, 2017, vol. 95, pp. 231–239.
[5] Ivanov M.Yu., Novikov A.E., Resh G.F. Vestnik MGTU im. N.E. Baumana. Ser. Mashinostroenie — Herald of the Bauman Moscow State Technical University. Series mechanical engineering, 2017, no. 2, pp. 54–65.
[6] Melnikova V.G., Kotsur O.S., Shcheglov G.A. Trudy ISP RAN — Proc. ISP RAS, 2017, vol. 29, iss. 1, pp. 53–70.
[7] Melnikova V.G. Trudy ISP RAN — Proc. ISP RAS, 2018, vol. 30, iss. 6, pp. 315–328.
[8] Bushuev A.Yu., Ivanov M.Yu., Korotaev D.V. Minimization of a mismatch time of movement of actuators of a throttle synchronization system. Journal of Physics: Conference Series, 2018, vol. 1141, iss. 1.
[9] Sakharov M., Karpenko A. A new way of decomposing search domain in a global optimization problem. Advances in intelligent systems and computing, 2018, vol. 679, pp. 398–402.
[10] Agasiev T., Karpenko A. The Program System for Automated Parameter Tuning of Optimization Algorithms. Procedia computer science, 2017, vol. 103, pp. 347–354.
[11] Bushuev A.Yu., Ryauzov S.S. Matematicheskoe modelirovanie i chislennye metody — Mathematical Modeling and Computational Methods, 2019, no. 4, pp. 3–14.
[12] Bushuev A.Yu., Maremshaova A.A. Matematicheskoe modelirovanie i chislennye metody — Mathematical Modeling and Computational Methods, 2018, no. 3, pp. 22–37.
[13] Sakharov M., Karpenko A. Performance investigation of mind evolutionary computation algorithm and some of its modifications. Advances in intelligeng systems and computing, 2016, vol. 450, pp. 475–486.
[14] Karpenko A.P. Sovremennye algoritmy poiskovoj optimizacii. Algoritmy, vdohnovlyonnye prirodoj [Modern Search Optimization Algorithms. Nature-Inspired Algorithms]. Moscow, BMSTU Publ., 2017, 446 p.
[15] Weise T. Global Optimization Algorithms: Theory and Application, 2009, p. 820. Available at: http://www.it-weise.de/projects/book.pdf.
[16] Ivashko A.G., Tsyganova M.S., Karjakin I.Yu. Vestnik TyumGU — Herald of the Tyumen State, 2009, vol. 6, pp. 197–202.
[17] Kelley C.T. Iterative Methods for Optimization. North Carolina, North Carolina State University Raleigh, 1995, 188 p.


Бушуев А.Ю., Иванов М.Ю., Коротаев Д.В., Реш Г.Ф. Программная среда dgsSynchCAD для моделирования и автоматизированной эвристической оптимизации дроссельных гидросистем синхронизации. Математическое моделирование и численные методы. 2020. № 1. с 103–117.



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