Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
Quality-cost optimal control in Lotka-Volterra populations model. / Babadzanjanz , L. K.; Pototskaya, I. Y.; Pupysheva , Y. Y.; Saakyan , M. A. T.
19th International Multidisciplinary Scientific GeoConference SGEM 2019: Conference proceedings. 2019. София : STEF92 Technology Ltd., 2019. стр. 3-10 (International Multidisciplinary Scientific GeoConference-SGEM; Том 19, № 5.1).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
}
TY - GEN
T1 - Quality-cost optimal control in Lotka-Volterra populations model
AU - Babadzanjanz , L. K.
AU - Pototskaya, I. Y.
AU - Pupysheva , Y. Y.
AU - Saakyan , M. A. T.
N1 - Conference code: 19
PY - 2019
Y1 - 2019
N2 - The aim of this article is the studying of the “predator-prey” populations controlled interaction. The well-known Lotka-Volterra system ([1], [3], [5-15]) with control is used as a mathematical model. A complete research of this model is done: From its parameters identification to the choice of optimal control. The identification numerical algorithms are based on the Taylor series method. This method application is reasonable in this case, because right sides of the considered ODEs system can be presented in polynomial form. To select the best control, a number of algorithms based on the direct search are proposed. They allow to find the optimal ratio between the time, cost and accuracy of the perturbed system's returning to the equilibrium point. These algorithms are: The control's work areas constructing algorithm; the algorithm for the constructing a dependence the control’s cost of the distance to the target point; the algorithm for the constructing a dependence the distance of the control’s cost. The algorithms are implemented in the Matlab package and are tested on model examples. Analysis of the test results allows us to see changes in the system dynamics because of control, to compare control influences and choose from them the optimal one for the “quality-cost” balance.
AB - The aim of this article is the studying of the “predator-prey” populations controlled interaction. The well-known Lotka-Volterra system ([1], [3], [5-15]) with control is used as a mathematical model. A complete research of this model is done: From its parameters identification to the choice of optimal control. The identification numerical algorithms are based on the Taylor series method. This method application is reasonable in this case, because right sides of the considered ODEs system can be presented in polynomial form. To select the best control, a number of algorithms based on the direct search are proposed. They allow to find the optimal ratio between the time, cost and accuracy of the perturbed system's returning to the equilibrium point. These algorithms are: The control's work areas constructing algorithm; the algorithm for the constructing a dependence the control’s cost of the distance to the target point; the algorithm for the constructing a dependence the distance of the control’s cost. The algorithms are implemented in the Matlab package and are tested on model examples. Analysis of the test results allows us to see changes in the system dynamics because of control, to compare control influences and choose from them the optimal one for the “quality-cost” balance.
KW - ODE numerical integration
KW - Optimal control
KW - Parameters identification
KW - The Lotka-Volterra model
KW - The Taylor series method
UR - http://www.scopus.com/inward/record.url?scp=85073367908&partnerID=8YFLogxK
UR - https://www.elibrary.ru/item.asp?id=42460142
U2 - 10.5593/sgem2019/5.1/S20.001
DO - 10.5593/sgem2019/5.1/S20.001
M3 - Conference contribution
T3 - International Multidisciplinary Scientific GeoConference-SGEM
SP - 3
EP - 10
BT - 19th International Multidisciplinary Scientific GeoConference SGEM 2019
PB - STEF92 Technology Ltd.
CY - София
T2 - 19th International Multidisciplinary Scientific Geoconference, SGEM 2019
Y2 - 9 December 2019 through 11 December 2019
ER -
ID: 49648417