Regular Papers

International Journal of Control, Automation and Systems 2018; 16(4): 1805-1813

Published online July 11, 2018

https://doi.org/10.1007/s12555-017-0271-3

© The International Journal of Control, Automation, and Systems

Estimation of CD4+ T Cell Count Parameters in HIV/AIDS Patients Based on Real-time Nonlinear Receding Horizon Control

Fei Sun and Kamran Turkoglu*

San Jose State University

Abstract

An increasing number of control techniques are introduced to HIV infection problem to explore the options of helping clinical testing, optimizing drug treatments and to study the drug resistance. In such cases, complete/accurate knowledge of the HIV model and/or parameters is critical not only to monitor the dynamics of the system, but also to adjust the therapy accordingly. In those studies, existence of any type of unknown parameters imposes severe set-backs and becomes problematic for the treatment of the patients. In this work, we develop a real-time nonlinear receding horizon control approach to aid such scenarios and to estimate unknown constant/time-varying parameters of nonlinear HIV system models. For this purpose, the estimation procedure is reduced to a series of finite-time optimization problem which can be solved by backwards sweep Riccati method in real time without employing any iterative techniques. The simulation results demonstrate that proposed algorithm is able to estimate, effectively, unknown constant/time-varying parameters of HIV/AIDS model with disturbance and provide a unique, adaptive solution to an important open problem."

Keywords Adpative control, HIV model, nonlinear receding horizon control, parameter estimation.

Article

Regular Papers

International Journal of Control, Automation and Systems 2018; 16(4): 1805-1813

Published online August 1, 2018 https://doi.org/10.1007/s12555-017-0271-3

Copyright © The International Journal of Control, Automation, and Systems.

Estimation of CD4+ T Cell Count Parameters in HIV/AIDS Patients Based on Real-time Nonlinear Receding Horizon Control

Fei Sun and Kamran Turkoglu*

San Jose State University

Abstract

An increasing number of control techniques are introduced to HIV infection problem to explore the options of helping clinical testing, optimizing drug treatments and to study the drug resistance. In such cases, complete/accurate knowledge of the HIV model and/or parameters is critical not only to monitor the dynamics of the system, but also to adjust the therapy accordingly. In those studies, existence of any type of unknown parameters imposes severe set-backs and becomes problematic for the treatment of the patients. In this work, we develop a real-time nonlinear receding horizon control approach to aid such scenarios and to estimate unknown constant/time-varying parameters of nonlinear HIV system models. For this purpose, the estimation procedure is reduced to a series of finite-time optimization problem which can be solved by backwards sweep Riccati method in real time without employing any iterative techniques. The simulation results demonstrate that proposed algorithm is able to estimate, effectively, unknown constant/time-varying parameters of HIV/AIDS model with disturbance and provide a unique, adaptive solution to an important open problem."

Keywords: Adpative control, HIV model, nonlinear receding horizon control, parameter estimation.

IJCAS
July 2024

Vol. 22, No. 7, pp. 2055~2340

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