Scientific and Technical Journal


ISSN Print 2221-3937
ISSN Online 2221-3805
In solving problems of optimum design synthesis phase collector engines face a number of difficulties due to their characteristics. First of all it bahatoekstremalnoho minimyzyruyemoho functional. Another feature optimization problems SACs is their rigidity. This complicates the optimization process increases computation time and requires the application to address these problems new algorithms search for optimal solutions. Proponuyemyy approach to the design phase synthesis collector engines based on the combined algorithm involves sorting method orderly and evolutionary algorithm for finding the optimal values ​​of controlled variables. Controlled variables are divided into discrete and continuous variables varied. For discrete variable controlled variable set number of combinations (options). Then, for each option separately, using a genetic algorithm optimization is performed continuously variable variables. Then, by comparing selected the best option. Reducing the number of calculations for discrete controlled variables significantly reduces total time to search for the optimal solution. The study suggested approach for the project phase synthesis collector engines showed significant its adaptability to solve optimization problems and achieve the required level of technical requirements. The proposed algorithm is applied to subsystem optimal design phase collector engines. Examples geometry optimization of anchor collector output. The investigations have shown high effectiveness of the proposed combined algorithm for solving optimization problems.
1. Rastrigin L.A. Sovremennye printsipy upravleniya slozhnymi ob"ektami [Modern Principles of Management by Difficult Objects], (1980), Moscow, Russian Federation, Sovetskoe Radio, 232 p. (In Russian).
2. Vermishev Ju.H. Metody av-tomaticheskogo poiska reshenij pri proektiro-vanii slozhnyh tehnicheskih system [Methods for Automatic Search of Decisions at Planning of the Difficult Technical Systems], (1982), Moscow, Russian Federation, Radio i Ssvjaz', 152 p. (In Russian).
3. Pujlo G.V., and Pirkovskij S.N. Proektnyj sintez odnofaznyh kollektornyh dvigatelej s adaptaciej obobshhennogo pokazatelja kachest-va [Project Synthesis of Single-Phase Commu-tation Motor with Adaptation of the Generalized index of Quality], (2003), Elektroenergetichnі ta Elektromehanichnі Sistemi. Vіsnik NU “L'vіvs'ka polіtehnіka”, Lviv, Ukraine, No. 485, pp. 12 – 16 (In Russian).
4. Pirkovskij S.N. Opredelenie optimal'nyh razmerov odnofaznyh kollektornyh dvigatelej [Determination of Optimal Size of Single-Phase Commutation Motors], (2000), Odessa Ukraine, Trudy Odesskogo Politehnicheskogo Univer-siteta, Vyp. 1, pp.45 – 49 (In Russian).
5. Pujlo G.V., and Pirkovskij S.N. Paramet-richeskij sintez odnofaznogo kollektornogo dvi-gatelja peremennogo toka [Parametric Synthesis of Single-Phase Commutation Motor], (2002), Kharkov, Ukraine, NTU “HPІ”, Elektrotehnіka ta Elektromehanika, No. 2, pp. 56 – 59 (In Rus-sian).
6. Pirkovskij S.N. Ocenka kachestva odno-faznyh kollektornyh dvigatelej na stadii proekti-rovanija [Assessment of the Quality of Single-Phase Commutation Motors at the Design Stage.] (2003), Odessa, Ukraine, Trudy Odesskogo Politehnicheskogo Universiteta, Vyp. 1, pp. 45 – 49 (In Russian).
7. Mitchell M., (1996), An Introduction to Genetic Algorithm. MIT Press, pp. 45 – 49.
8. Kurejchik V.M. Geneticheskie algoritmy. Sostojanie. Problemy. Perspektivy [Genetic Al-gorithms. State. Problem. Prospects], (1999), Izvestija RAN. Teorija i Sistemy Upravlenija, No. 1, 175 p.
9. Batishhev D.I., Skidkina L.N., and Tra-peznikova N.V. Global'naja optimizacija s po-moshh'ju jevoljucionno - geneticheskih algo-ritmov [Global Optimization Using Evolutionary – Genetic Algorithms], (1994), Voronezh Russia, Mezhvuzovskij Sbornik, VGTU, pp. 34 – 39 (In Russian).
10. Bently P.J., and Wakefield J.P., (1997), Finding Acceptable Solution in the Pareto Op-timal Range using Multiobjective Genetic Algo-ritms. In Рroceeding of the 2nd On-Line World Conference on Soft Computing in Engineering Design and Manufacturing, pp. 74 –79.
11. Zizler E., and Thiele L., (1999), Mul-tiobbjective Evolutionary Algorithms: A Com-parative Case Study and the Strength Pareto Approach, IEEE Transactions on Evolutionary Computation, Vol. 3, No. 4, pp. 257 – 271.
12. Pujlo G.V., Pirkovskij S.N, and Procyna Z.P. Optimal'nyj parametricheskij sintez odno-faznyh kollektornyh dvigatelej na osnove ge-neticheskogo algoritma [Optimal Parametric Synthesis of Single-Phase Commutation Motors Based on Genetic Algorithm], 2004, Kiev, Ukraine, Elektromashinobuduvannja ta Еlek-troobladnannja, Vyp. 62, pp. 129 – 132
(In Russian).
13. Pirkovskij S.N., Babijchuk O.B., and Procyna Z.P. Proektnyj sintez odnofaznyh kollektornyh dvigatelej na osnove vektornogo pokazatelja kachestva [Project Synthesis of Sin-gle-Phase Commutation Motors on the Basis of Vectorial index of Quality], 2005, Kiev, Ukraine, Elektromashinobuduvannja ta Elek-troobladnannja, Vyp. 64, pp. 67 – 71 (In Russian).

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