ALGORITHMS TO RESTORE THE INPUT EFFECTS OF DYNAMIC SYSTEMS IN CONDITIONS OF UNCERTAINTY

Kholkhodjaev  Boxodir Asatullaevich

207

The algorithms are provided for restoring the effects of input under uncertainty conditions. Different algorithms are considered for restoring the input behavior in an undefined dynamic system. An algorithm of finding a pseudo-return matrix using direct numerical analysis of the recurrent type was used to make the procedure of restoring the input effects stable. The above-mentioned algorithms allow increasing the accuracy of determining input effects in the presence of disturbances.

Название журналаTechnical science and innovation
Номер выпуска2020,№4(06)
Количество просмотров 207

Ссылка в интернете

DOI

Дата создание в систему UzSCI 05-05-2021

Количество прочтений 206

Дата публикации 20-11-2020

Язык статьиIngliz

Страницы150-154

Ключевые слова

dynamic system

Uncertainty

input recovery

English

The algorithms are provided for restoring the effects of input under uncertainty conditions. Different algorithms are considered for restoring the input behavior in an undefined dynamic system. An algorithm of finding a pseudo-return matrix using direct numerical analysis of the recurrent type was used to make the procedure of restoring the input effects stable. The above-mentioned algorithms allow increasing the accuracy of determining input effects in the presence of disturbances.

Ключевые слова

dynamic system

Uncertainty

input recovery

№ Имя автора Должность Наименование организации

1 Kholkhodjaev B.A. doktorant TDTU

№ Название ссылки

1 1. Miroshnik I.V. Theory of automatic control. Linear systems. - St. Petersburg: Peter, 2005. -- 336 p.

2 2. Methods of the classical and modern theory of automatic control. The textbook in 3 volumes / Ed. N.D. Yegupova. - M.: Publishing House of MSTU. Bauman, 2000.

3 3. Korovin S.K. State observers for linear systems with uncertainty. Monograph. -M.: Fizmatlit, 2007. 224 p.

4 4. Grigorev V.V., Juravlyova N.V., Luk'yanova G.V., Sergeev K.A. Synthesis of automatic control systems by model control method. SPb: SPbGITMO, 2007. – 108 p.

5 5. Krasnova S. A., Utkin V. A. Cascade synthesis of observers of the state of dynamical systems. –M.: Nauka, 2006. –272 p.

6 6. Ilyin A.V., Korovin S.K., Fomichev V.V. Khladenka A. Observers for linear dynamical systems with uncertainty // Differ. Equations, 2005, Volume 41, Number 11, – pages. 1443-1457.

7 7. Igamberdiev H.Z., Yusupbekov A.N., Zaripov O.O. Regular methods for evaluating and managing dynamic objects in the face of uncertainty. - T.: TSTU, 2012. -- 320 p.

8 8. Igamberdiev, Husan Zakirovich; Rasulev, Aliakbar Khamidullayevich; Mamirov, Uktam FarkhodovichAlgorithms of Stable Evaluation of Initial Conditions for the Observing Device of Perturbations of the Linear System // International Journal of Advanced Research in Science, Engineering and Technology (IJARSET), Vol 5, Issue 3, 2018. –PP. 5373-5377. http://www.ijarset.com/upload/2018/march/12-IJARSET-UKTAM.pdf.

9 9. Yusupbekov N.R., Igamberdiev H.Z., Mamirov U.F. Algorithms of sustainable estimation of unknown input signals in control systems // Journal of Multiple-Valued Logic and Soft Computing, Vol. 33, Issue 1-2, 2019, –PP. 1-10.

10 10. Igamberdiyev H.Z., Yusupbekov A.N., Zaripov O.O., Sevinov J.U. Algorithms of adaptive identification of uncertain operated objects in dynamical models // Procedia computer science. 2017, Vol. 120. - PP. 854-861.

11 11. Charles L. Lawson, Richard J. Hanson. Solving least squares problems / Philadelphia: SIAM, c1995. -337 p.

12 12. Zhdanov A.I. Introduction to methods for solving ill-posed problems: -Iz. Samara state. Aerospace University, 2006. -87 p.

13 13. Gantmacher F. R., Brenner J. L. Applications of the Theory of Matrices. – Courier Corporation, 2005.

14 14. Horn R.A., Johnson C.R. Matrix analysis // Cambridge University Express. – 1985.

15 15. Zhukovsky E.L., Liptser R.Sh. On the calculation of pseudoinverse matrices // J. Comput. Math and math. physics. 1975, Volume 15, Number 2, Pages - 489–492.

16 16. Igamberdiyev H.Z., Mamirov U.F. Sustainable estimation of parameters and covariation of disturbance vectors in uncertain systems // Chemical Technology. Control and Management. 2018. № 3. – PP. 16-19.

17 17. Mamirov U.F. Algorithms of stable control of a matrix object in the conditions of parametric uncertainty // Chemical Technology. Control and Management. 2018. №. 1. – PP. 164-168.

В ожидании

№	Название ссылки
1	1. Miroshnik I.V. Theory of automatic control. Linear systems. - St. Petersburg: Peter, 2005. -- 336 p.
2	2. Methods of the classical and modern theory of automatic control. The textbook in 3 volumes / Ed. N.D. Yegupova. - M.: Publishing House of MSTU. Bauman, 2000.
3	3. Korovin S.K. State observers for linear systems with uncertainty. Monograph. -M.: Fizmatlit, 2007. 224 p.
4	4. Grigorev V.V., Juravlyova N.V., Luk'yanova G.V., Sergeev K.A. Synthesis of automatic control systems by model control method. SPb: SPbGITMO, 2007. – 108 p.
5	5. Krasnova S. A., Utkin V. A. Cascade synthesis of observers of the state of dynamical systems. –M.: Nauka, 2006. –272 p.
6	6. Ilyin A.V., Korovin S.K., Fomichev V.V. Khladenka A. Observers for linear dynamical systems with uncertainty // Differ. Equations, 2005, Volume 41, Number 11, – pages. 1443-1457.
7	7. Igamberdiev H.Z., Yusupbekov A.N., Zaripov O.O. Regular methods for evaluating and managing dynamic objects in the face of uncertainty. - T.: TSTU, 2012. -- 320 p.
8	8. Igamberdiev, Husan Zakirovich; Rasulev, Aliakbar Khamidullayevich; Mamirov, Uktam FarkhodovichAlgorithms of Stable Evaluation of Initial Conditions for the Observing Device of Perturbations of the Linear System // International Journal of Advanced Research in Science, Engineering and Technology (IJARSET), Vol 5, Issue 3, 2018. –PP. 5373-5377. http://www.ijarset.com/upload/2018/march/12-IJARSET-UKTAM.pdf.
9	9. Yusupbekov N.R., Igamberdiev H.Z., Mamirov U.F. Algorithms of sustainable estimation of unknown input signals in control systems // Journal of Multiple-Valued Logic and Soft Computing, Vol. 33, Issue 1-2, 2019, –PP. 1-10.
10	10. Igamberdiyev H.Z., Yusupbekov A.N., Zaripov O.O., Sevinov J.U. Algorithms of adaptive identification of uncertain operated objects in dynamical models // Procedia computer science. 2017, Vol. 120. - PP. 854-861.
11	11. Charles L. Lawson, Richard J. Hanson. Solving least squares problems / Philadelphia: SIAM, c1995. -337 p.
12	12. Zhdanov A.I. Introduction to methods for solving ill-posed problems: -Iz. Samara state. Aerospace University, 2006. -87 p.
13	13. Gantmacher F. R., Brenner J. L. Applications of the Theory of Matrices. – Courier Corporation, 2005.
14	14. Horn R.A., Johnson C.R. Matrix analysis // Cambridge University Express. – 1985.
15	15. Zhukovsky E.L., Liptser R.Sh. On the calculation of pseudoinverse matrices // J. Comput. Math and math. physics. 1975, Volume 15, Number 2, Pages - 489–492.
16	16. Igamberdiyev H.Z., Mamirov U.F. Sustainable estimation of parameters and covariation of disturbance vectors in uncertain systems // Chemical Technology. Control and Management. 2018. № 3. – PP. 16-19.
17	17. Mamirov U.F. Algorithms of stable control of a matrix object in the conditions of parametric uncertainty // Chemical Technology. Control and Management. 2018. №. 1. – PP. 164-168.