Loading...
| Friend's email | |
| Your name | |
| Your email | |
| enter code | |
This page was sent successfuly
- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 46811 (06)
- University: Sharif University of Technology
- Department: Chemical and Petroleum Engineering
- Advisor(s): Shahrokhi, Mohammd
- Abstract:
- This project presents algorithms for intelligent control of the viral load in a HIV-1 infection model. The first part of thesis was dedicated to the study of the three states model adopted to describe the HIV-1 infection. A sensitivity analysis of the model parameters was described and computer simulations were provided to show the influence of the parameters explicitly. Then, an internal model control based on neural networks was implemented on the introduced infection model with including the RTIs and PIs drugs efficacies as control input. A stable adaptive neuro-control approach was presented for affine in the control nonlinear dynamical systems, whose nonlinearities were assumed to be unknown. A resetting strategy garantees the boundedness away from zero of certain signals. In order to estimate unmeasurable system states, a neural network-based observer was proposed. Finally, the adaptive controller and abserver was designed to control the HIV-1 infection model. The results showed that the adaptive scheme was able to control the HIV-1 infection satisfactoriliy. The performance of adaptive controller was evaluated in presence of model uncertainty and the results showed that it is totally robust
- Keywords:
- Neural Network ; Adaptive Observer ; HIV Infection ; Antiretrovival Therapy ; Unknown Nonlinear System
Digital Object List
-
محتواي کتاب
- view
Bookmark