پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 610 |
| تعداد مقالات | 9,027 |
| تعداد مشاهده مقاله | 67,082,781 |
| تعداد دریافت فایل اصل مقاله | 7,656,193 |
Observer-based intelligent adaptive iterative time-varying controller for nonlinear of chronic myelogenous leukemia dynamics | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 15 آذر 1403 اصل مقاله (602.44 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2024.30354.4386 | ||
| نویسندگان | ||
| Reza Ghasemi* ؛ Bita Sadat Ghazanfarpour | ||
| Electrical Engineering Department, University of Qom, Qom, Iran | ||
| تاریخ دریافت: 22 فروردین 1402، تاریخ بازنگری: 22 آبان 1402، تاریخ پذیرش: 10 اسفند 1402 | ||
| چکیده | ||
| An adaptive controller for a time-varying non-linear non-affine system is designed based on the observer for chronic Myelogenous leukaemia (CML) as a blood cancer. Compared to recent research that concentrates on designing controllers for exact models of CML, our approach deals with designing controllers for nonlinear uncertain models in which the function of the system is unknown. This approach deals with the nonlinear observer-based design to reduce both the hardware and sensors for parameter estimation of the diseased. In the proposed method for designing a suitable controller, fuzzy systems are used as a general approximator and also their parameters are calculated in such a way that the stability of the closed-loop system is guaranteed. Compared to the investigated methodologies that concentrate on the designing controller for the known dynamical models, the proposed approach deals with the unknown nonlinear model of Nonlinear of Chronic Myelogenous Leukemia. Furthermore, instead of approximating the unknown function of the disease, this approach concentrates on the approximation of the control input to decrease computational values. This method is a supplementary tool for specialists who study in this field. Furthermore, one of the most important advantages of the proposed method is that the dynamics of systems are uncertain. Simulation results show the effectiveness of the proposed method. | ||
| کلیدواژه‌ها | ||
| Adaptive Controller؛ Cancer؛ Chronic Myelogenous Leukemia؛ Observer؛ Fuzzy System؛ Nonlinear Model | ||
| مراجع | ||
|
[1] K.O. Bangsgaard, M. Andersen, V. Skov, L. Kjar, H.C. Hasselbalch, and J.T. Ottesen, Dynamics of competing heterogeneous clones in blood cancers explains multiple observations: A mathematical modeling approach, Math. Biosci. Engin. 17 (2020), no. 6, 7645–7670. [2] N. Bellomo and L. Preziosi, Modeling and mathematical problems related to tumor evolution and its interaction with the immune system, Math. Comput. Model. 32 (2000), no. 3, 413–452. [3] M. Charles and L. Sawyers, Chronic myeloid leukemia, New England J. Med. 340 (1999), no. 1, 1330–1340. [4] C.I-U. Chen, H.T. Maecker, and P.P. Lee, Development and dynamics of robust T-cell responses to CML, Blood 111 (2008), no. 1, 5342–5349. [5] M.W.N. Deininger, The molecular biology of chronic myeloid leukemia, Blood 96 (2000), no. 10, 3343–3356. [6] S. Faderl, The biology of chronic myeloid leukemia, New England J. Med. 341 (1999), no. 1, 164–172. [7] M.G. Farajzadeh, A. Tayarany, and S.K. Hosseini Sani, An efficient method for controlling of CML treatment system, J. Soft Comput. Inf. Technol. 5 (2016), no. 1, 53–61. [8] A. Ghaffari, Mathematical modeling and Lyapunov-based drug administration in cancer chemotherapy, Iran. J. Electric. Electron. Engin. 5 (2009), no. 3, 151–158. [9] J.M. Goldman, Chronic myeloid leukemia—advances in biology and new approaches to treatment, New England J. Med. 349 (2003), no. 1, 1451–1464. [10] P.S. Kim, P.P. Lee, and D. Levy, Dynamics and potential impact of the immune response to chronic myelogenous leukemia, PLOS Comput. Bio. 4 (2008), no. 6, 1–17. [11] Leukemia and Lymphoma Society pamphlet, [Online]. Available: http://www.leukemialymphoma.org/attachments/National/br-1114197910.pdf, March 2005. [12] B.J.D. Michael and W.N. Deininger, Specific targeted therapy of chronic myelogenous leukemia with imatinib, Pharmacol. Rev. 55 (2003), 401–423. [13] X.R. Minlin Wang, Neural network observer-based optimal tracking control for multi-motor servomechanism with backlash, Proc. 2015 Chinese Intell. Syst. Conf., Volume 2, Springer Berlin Heidelberg, 2016. [14] H. Moorea, A mathematical model for chronic myelogenous leukemia (CML) and T cell interaction, J. Theore. Bio. 227 (2004), no. 4, 513–523. [15] S. Nanda, Optimal control of treatment in a mathematical model of chronic myelogenous leukemia, Math. Biosci. 210 (2007), no. 1, 143–156. [16] D. Paquin, Strategic treatment interruptions during imatinib treatment of chronic myelogenous leukemia, Bull. Math. Bio. 73 (2009), no. 5, 1082–1100. [17] L.G. Parajdi, F. Patrulescu, R. Precup, and I.S. Haplea, Two numerical methods for solving a nonlinear system of integral equations of mixed Volterra-Fredholm type arising from a control problem related to leukemia, J. Appl. Anal. Comput. 13 (2023), no. 4, 1797-–1812. [18] M.M. Peet, New computational tools for modeling chronic myelogenous leukemia, Math. Modell. Natural Phen. 4 (2009), no. 1, 119–139. [19] M.K. Radhakant Padhi, An optimal dynamic inversion-based neuro adaptive approach for the treatment of chronic myelogenous leukemia, Comput. Meth. Programs Biomed. 87 (2007), no. 3, 208–224. [20] M.R. Rahimi Khoygani and R. Ghasemi, Neural estimation using a stable discrete-time MLP observer for a class of discrete-time uncertain MIMO nonlinear systems, Nonlinear Dyn. 84 (2016), no. 4, 2517–2533. [21] S. Rooka and R. Ghasemi, Fuzzy fractional sliding mode observer design for a class of nonlinear dynamics of the cancer disease, Int. J. Autom. Control 12 (2018), no. 1, 62–77. [22] C. Woywod, F.X. Gruber, R.A. Engh, and T. Fl˚a, Dynamical models of mutated chronic myelogenous leukemia cells for a post-imatinib treatment scenario: Response to dasatinib or nilotinib therapy, PLoS ONE 12 (2017), no. 7, 1–45. | ||
|
آمار تعداد مشاهده مقاله: 30 تعداد دریافت فایل اصل مقاله: 37 |
||