PDC Control of Time Delay Fuzzy T-S modeled HIV-1 System through Drug Dosage

[1]Joly, M., J. M. Pinto (2006). “Role of Mathematical Modeling on the Optimal Control of HIV-1 Pathogenesis”, PROCESS SYSTEMS ENGINEERING 52(3).

[2]Tanaka, K., H. O. Wang (2001). “FUZZY CONTROL SYSTEMS DESIGN AND ANALYSIS”, John Wiley & Sons.

[3]Kwon, O.M., et al. (2012). “Augmented Lyapunov– Krasovskii functional approaches to robust stability criteria for uncertain Takagi–Sugeno fuzzy systems with time-varying delays”, Fuzzy Sets and Systems 201: 1–19.

[4]Caetano, M. A. L., et al. (2008, June). “Optimal medication in HIV seropositive patient treatment using fuzzy cost function.” 2008 American Control Conference, Seattle, Washington, USA.

[5]Brandt, M. E., G. Chen (2001,July). “Feedback Control of a Biodynamical Model of HIV-1.” IEEE Transactions on Biomedical Engineering 48(7).

[6] Craig, I., X. Xia(2005,February). “Can HIV/AIDS Be Controlled? Applying control engineering concepts outside traditional fields.” IEEE Control Systems Magazine.

[7] Costanza, V., et al. (2009). “A closed-loop approach to antiretroviral therapies for HIV infection. “ Biomedical Signal Processing and Control 4: 139–148.

[8] Mhawej, M. J., et al. (2009). “Apoptosis characterizes immunological failure of HIV infected patients. “ Control Engineering Practice17: 798–804.

[9] Xia, X., (2003). “Estimation of HIV/AIDS parameters . “ Automatica 39: 1983 – 1988.

[10] Xia, X.,(2007). “Modeling of HIV infection: Vaccine readiness, drug effectiveness and therapeutical failures. “ Journal of Process Control 17: 253–260.

[11] Biafore, F. L., C. E. D’Attellis (2005,September). “Exact Linearisation and Control of a HIV-1 Predator-Prey Model. “ Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference , Shanghai, China.

[12] Ge, S. S., et al. (2005,March). “Nonlinear Control of a Dynamic Model of HIV-1. “ IEEE Transactions on Biomedical Engineering 52(3).

[13] Jeffrey, A. M., X. Xia (2003,November). “When to Initiate HIV Therapy: A Control Theoretic Approach. “ IEEE Transactions on Biomedical Engineering 50(11).

[14] Elaiw, A. M., (2010). “Global properties of a class of HIV models. “ Nonlinear Analysis: Real World Applications 11: 2253_2263.

[15] Zurakowski, R., et al. (2004). “HIV treatment scheduling via robust nonlinear model predictive control. “ IEEE 2004 5th Asian Control Conference.

[16] Chang, H., A. Astolfi (2007,July). “Control of the HIV Infection Dynamics with a Reduced Second Order Model.“ Proceedings of the 2007 American Control Conference, New York City, USA.

[17] Chang, H., A. Astolfi (2009). “Enhancement of the immune system in HIV dynamics by output feedback. “ Automatica 45: 1765_1770.

[18] Chang, H.J., et al. (2004,December). “Control of Immune Response of HIV Infection Model by Gradual Reduction of Drug Dose. “ 43rd IEEE Conference on Decision and Control.

[19] Yongqi, L., S. Zhendong (2010,July). “Backward Bifurcation in an HIV Model with Two Target Cells.” Proceedings of the 29th Chinese Control Conference, Beijing, China.

[20] Chen, B. S., et al. (2010,July). “B. S. The Applications of Stochastic Regulation Control to HIV Therapy.“ Proceedings of the Ninth International Conference on Machine Learning and Cybernetics, Qingdao.

[21] Ledzewicz, U., H. Schattler (2002). “On optimal controls for a general mathematical model for chemotherapy of HIV. “ IEEE.

[22] Ko, J. H., et al.(2006,March). “Optimized Structured Treatment Interruption for HIV Therapy and Its Performance Analysis on Controllability.“ IEEE Transactions on Biomedical Engineering 53(3).

[23] Chang, H., A. Astolfi (2008,April). “Control of HIV Infection Dynamics. “ IEEE CONTROL SYSTEMS MAGAZINE.

[24] Pannocchia, G., et al. (2010,May). “A Model Predictive Control Strategy Toward Optimal Structured Treatment Interruptions in Anti-HIV Therapy. “ IEEE Transactions on Biomedical Engineering 57( 5).

[25] Mhawej, M. J., et al. (2010). “Control of the HIV infection and drug dosage. “ Biomedical Signal Processing and Control 5: 45–52.

[26] Barao, M., J.M. Lemos (2007). “Nonlinear control of HIV-1 infection with a singular perturbation model.” Biomedical Signal Processing and Control 2: 248–257.

[27] Gumel, A.B., S.M. Moghadas (2004). “HIV control in vivo: Dynamical analysis. “ Communications in Nonlinear Science and Numerical Simulation 9: 561–568.

[28] Orellana, J. M. (2010). “Optimal drug scheduling for HIV therapy efficiency improvement . “ Biomedical Signal Processing and Control.

[29] Wu, J., M. Zhang (2010,June) “A Game Theoretical Approach to Optimal Control of Dual Drug Delivery for HIV Infection Treatment. “ IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics 40(3).

[30] Velichenko, V. V., D. A. Pritykin (2006). “Numerical Methods of Optimal Control of the HIV-Infection Dynamics.“ Journal of Computer and Systems Sciences International 45(6): 894–905.

[31] Luo, R., et al. (2009,June). “A Generalized Multi-strain Model of HIV Evolution with Implications for Drug-resistance Management.” 2009 American Control Conference Hyatt Regency Riverfront, St. Louis, MO, USA.

[32] Rong L., et al. (2007). “Modeling within-host HIV-1 dynamics and the evolution of drug resistance: Trade-offs between viral enzyme function and drug susceptibility . “ Journal of Theoretical Biology 247: 804–818.

[33] Banks, H. T., et al. (2005). “An SDRE Based Estimator Approach for HIV Feedback Control. “.

[34] Adams, B.M., et al. (2005). “Model Fitting and Prediction with HIV Treatment Interruption Data.”.

[35] Stan, G. B., et al. (2007). “Modelling the influence of activation-induced apoptosis of CD41 and CD81 T cells on the immune system response of a HIV-infected patient. “ IET Systems Biology.

[36] Singh, G. B. “Computational Modeling and Prediction of the Human Immunodeficiency Virus (HIV) Strains. “ IEEE.

[37] Shechter, S. M., et al. (2004). “MODELING THE PROGRESSION AND TREATMENT OF HIV.“ Proceedings of the IEEE 2004 Winter Simulation Conference.

[38] Spagnuolo, A. M., et al. (2004,September). “Modeling HIV-1 Dynamics and the Effects of Decreasing Activated Infected T-cell Count by Filtration.“ Proceedings of the 26th Annual International Conference of the IEEE EMBS, San Francisco, CA, USA.

[39] Marwala, T., B. Crossingham (2008). “Neuro-Rough Models for Modelling HIV.“ 2008 IEEE International Conference on Systems, Man and Cybernetics (SMC 2008).

[40] Ding, Y., H. Ye (2009). “A fractional-order differential equation model of HIV infection of CD4C T-cells.“ Mathematical and Computer Modeling 50: 386_392.

[41]Roy, P. K., et al. (2009,August). “HIV model with intracellular delay -a mathematical study.” 5th Annual IEEE Conference on Automation Science and Engineering Bangalore, India.

[42]Banks, H.T., et al. (2007). “Time delay systems with distribution dependent dynamics.” Annual Reviews in Control 31: 17–26.

[43]Banks, H.T., et al. (2003). “Incorporation of variability into the modeling of viral delays in HIV infection dynamics.” Mathematical Biosciences 183: 63–91.

[44]Lv, C., Z. Yuan (2009). “Stability analysis of delay differential equation models of HIV-1 therapy for fighting a virus with another virus.” Journal of Mathematical Analysis and Applications 352: 672–683.

[45]Xu, R., (2011). “Global dynamics of an HIV-1 infection model with distributed intracellular delays.” Computers and Mathematics with Applications 61: 2799–2805.

[46]Jiang, X., et al. (2008). “Analysis of stability and Hopf bifurcation for a delay-differential equation model of HIV infection of CD4+ T-cells.” Chaos, Solitons and Fractals 38: 447–460.

[47]Zhou, X., et al. (2008). “Analysis of stability and Hopf bifurcation for an HIV infection model with time delay .” Applied Mathematics and Computation 199: 23–38.

[48]Srivastava, P. Kr., P. Chandra, (2010). “Modeling the dynamics of HIV and CD4+T cells during primary infection.” Nonlinear Analysis: Real World Applications 11: 612_618.

[49]Nelson, P. W., et al. (2000). “A model of HIV-1 pathogenesis that includes an intracellular delay.” Mathematical Biosciences 163: 201-215.

[50]Wang, Y., et al. (2009). “Oscillatory viral dynamics in a delayed HIV pathogenesis model.” Mathematical Biosciences 219: 104–112.

[51]Nelson, P. W., A. S. Perelson (2002). “Mathematical analysis of delay differential equation models of HIV-1 infection.” Mathematical Biosciences 179: 73–94.

[52]Ouifki, R., G. Witten (2009). “Stability analysis of a model for HIV infection with RTI and three intracellular delays.” BioSystems 95: 1–6.

[53]Li, D., W. Ma, (2007). “Asymptotic properties of a HIV-1 infection model with time delay.” Journal of Mathematical Analysis and Applications 335: 683–691.

[54]Xu, R., (2011). “Global stability of an HIV-1 infection model with saturation infection and intracellular delay.” Journal of Mathematical Analysis and Applications 375: 75–81.

[55]Culshaw, R. V., S. Ruan (2000). “A delay-differential equation model of HIV infection of CD4+T-cells.” Mathematical Biosciences 165: 27-39.

[56]Guardiola, J., et al. (2003). “Simulating the Effect of Vaccine-Induced Immune Responses on HIV Infection .“ Human Immunology 64: 840–851.

[57]Hu, Z., et al. (2010). “Analysis of the dynamics of a delayed HIV pathogenesis model.“ Journal of Computational and Applied Mathematics 234: 461_476.

[58]Betechuoh, B. L., et al. (2008). “Computational Intelligence for HIV Modelling.” IEEE.

[59]Lin, F., et al. (2005,December). “Theory for a Control Architecture of Fuzzy Discrete Event Systems for Decision Making. “ Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005, Seville, Spain.

[60]Melgarejo, M. A., et al. (2006,July). “A Genetic- Fuzzy System Approach To Control a Model of the HIV Infection Dynamics. “ 2006 IEEE International Conference on Fuzzy Systems, Vancouver, BC, Canada.

[61]Abbasi, R., M. T. H. Beheshti, (2015)”Modeling and stability analysis of HIV-1 as a Time Delay Fuzzy T-S system via LMI’s.” in press, Applied Mathematical Modeling 39( 23–24): 7134-7154.

[62]Wodarz, D., (2007). “Killer cell dynamics: Mathematical and computational approaches to immunology.” springer.

[63]Lin, C., et al. (2007). “LMI Approach to Analysis and Control of Takagi-Sugeno Fuzzy Systems with Time Delay.” Springer.

[64]Nentwig, M., P. Mercorelli (2010). “A Matlab/Simulink Toolbox for Inversion of Local Linear Model Trees.” IAENG International Journal of Computer Science, 37:1, IJCS_37_1_03.

[65]Fletcher, C. V., et al. (2014,February) “Persistent HIV- 1 replication is associated with lower antiretroviral drug concentrations in lymphatic tissues .” PNAS 111(6):2307–2312.

[66]Ene, L., et al. (2011). “How much do antiretroviral drugs penetrate into the central nervous system?. “ Journal of Medicine and Life 4(4): 432.439.