Suppression of tumor growth using nonlinear control and self-organization algorithm
https://doi.org/10.25881/18110193_2022_3_4
Abstract
Here we describe building a control impact intended to medically suppress tumor growth. The synthesis of control has been carried out using the method of linearization of a nonlinear system with state feedback. As a result of the study, a control law was obtained that provides the system with local stability, which translates into cessation of tumor growth in physical sense. The adequacy of the tumor growth model is achieved by constructing it using a self-organization algorithm with trend reservation. Linear trends are applied in the control law, while non-linear self-organizing models are used to test the treatment outcome. The results of mathematical modeling confirmed the effectiveness of the solutions obtained.
About the Authors
M. O. Raskolova
Lomonosov Moscow State University
Russian Federation
Russian Federation
PhD
Moscow
V. N. Afanasiev
National Research University Higher School of Economics
Russian Federation
Russian Federation
DSc, Professor
Moscow
K. A. Neusypin
BMSTU
Russian Federation
Russian Federation
DSc, Professor
Moscow
M. S. Selezneva
BMSTU
Russian Federation
Russian Federation
PhD
Moscow
References
1. Magni P, Simeoni M, Poggesi L, Rocchetti M, De Nicolao G. A mathematical model to study effectsof drugs administration on tumor growth dynamica. Mathematical biosciences. 2006; 200(2): 127-151.
2. Bru A, Albertos S, Subiza JL, Garcia-Asenjo JL, Bru I. The universal dynamics of tumor growth. Biophysical journal. 2003; 85(5): 2948-2961.
3. Weekes SL, Barker B, Bober S, Cisneros K, Cline J, Thompson A, Hlarky L, Hahnfeldt P, Enderfing H. A multicompartment mathematical model of cancer stem coll-driven tumor growth dynamics. Bulletin of mathematical biology. 2014; 76(7): 1762-1782.
4. Ivahnenko AG, Myuller JYA. Samoorganizaciya prognoziruyushchih modelej. Kiev: Tekhnika, 1985. 385 р. (In Russ.)
5. Neusypin KA, Proletarsky AV, Shen Kai, et al. Aircraft self-organization algorithm with redundant trend. Journal of Nanjing University of Science and Technology. 2014; 5: 602–607.
6. Afanas’ev VN. Upravlenie nelinejnymi neopredelennymi dinamicheskimi ob»ektami. M.: Librokom, 2015. (In Russ.)
7. Neusypin KA. Razrabotka modificirovannyh algoritmov samoorganizacii dlya korrekcii navigacionnoj informacii. Avtomatizaciya i sovremennye tekhnologii. M.: Mashinostroenie, 2009; 1: 37-39. (In Russ.)
Review
For citations:
Raskolova M.O., Afanasiev V.N., Neusypin K.A., Selezneva M.S. Suppression of tumor growth using nonlinear control and self-organization algorithm. Medical Doctor and Information Technologies. 2022;(3):4-13. (In Russ.) https://doi.org/10.25881/18110193_2022_3_4
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