Model-based Angiogenic Inhibition of Tumor Growth using Feedback Linearization

被引:0
|
作者
Szeles, Annamaria [1 ]
Drexler, Daniel Andras [1 ]
Sapi, Johanna [2 ]
Harmati, Istvan [1 ]
Kovacs, Levente [2 ]
机构
[1] Budapest Univ Technol & Econ, Dept Control Engn & Informat Technol, H-1117 Budapest, Hungary
[2] Obuda Univ, John von Neumann Fac Informat, H-1034 Budapest, Hungary
关键词
RESISTANCE; THERAPY;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the last decades beside conventional cancer treatment methods, molecular targeted therapies show prosperous results. These therapies have limited side-effects, and in comparison to chemotherapy, tumorous cells show lower tendency of becoming resistant to the applied antiangiogenic drugs. In clinical research, antiangiogenic therapy is one of the most promising cancer treatment methods. Using a simplified model of the reference dynamical model for tumor growth under angiogenic inhibition from the literature, exact linearization is performed in the paper to handle the nonlinear behavior of the model. Two different control methods are applied on the linearized model: flat control and switching control. Simulations are performed on the nonlinear model to show the characteristics of the therapies carried out using the presented control methods.
引用
收藏
页码:2054 / 2059
页数:6
相关论文
共 50 条
  • [1] Model-based angiogenic inhibition of tumor growth using adaptive fuzzy techniques
    Szeles, Annamária
    Drexler, Dániel András
    Sápi, Johanna
    Harmati, István
    Kovács, Levente
    Periodica polytechnica Electrical engineering and computer science, 2014, 58 (01): : 29 - 36
  • [2] Model-based angiogenic inhibition of tumor growth using modern robust control method
    Kovacs, Levente
    Szeles, Annamaria
    Sapi, Johanna
    Drexler, Daniel A.
    Rudas, Imre
    Harmati, Istvan
    Sapi, Zoltan
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2014, 114 (03) : E98 - E110
  • [3] A minimal model of tumor growth with angiogenic inhibition using bevacizumab
    Drexler, Daniel Andras
    Sapi, Johanna
    Kovacs, Levente
    2017 IEEE 15TH INTERNATIONAL SYMPOSIUM ON APPLIED MACHINE INTELLIGENCE AND INFORMATICS (SAMI), 2017, : 185 - 190
  • [4] Model-based feedforward position control of constant curvature continuum robots using feedback linearization
    Falkenhahn, Valentin
    Hildebrandt, Alexander
    Neumann, Ruediger
    Sawodny, Oliver
    2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2015, : 762 - 767
  • [5] Positive nonlinear control of tumor growth using angiogenic inhibition
    Drexler, Daniel Andras
    Sapi, Johanna
    Kovacs, Levente
    IFAC PAPERSONLINE, 2017, 50 (01): : 15068 - 15073
  • [6] Statistical mechanics model of angiogenic tumor growth
    Ferreira, Antonio Luis
    Lipowska, Dorota
    Lipowski, Adam
    PHYSICAL REVIEW E, 2012, 85 (01):
  • [7] Biological pest control using a model-based robust feedback
    Puebla, Hector
    Roy, Priti Kumar
    Velasco-Perez, Alejandra
    Gonzalez-Brambila, Margarita M.
    IET SYSTEMS BIOLOGY, 2018, 12 (06) : 233 - 240
  • [8] Fuzzy model-based predictive control by instantaneous linearization
    Abonyi, J
    Nagy, L
    Szeifert, F
    FUZZY SETS AND SYSTEMS, 2001, 120 (01) : 109 - 122
  • [9] Towards Model-Based Characterization of Biomechanical Tumor Growth Phenotypes
    Abler, Daniel
    Buechler, Philippe
    Rockne, Russell C.
    MATHEMATICAL AND COMPUTATIONAL ONCOLOGY, ISMCO 2019, 2019, 11826 : 75 - 86
  • [10] A fault monitoring approach using model-based and neural network techniques applied to input–output feedback linearization control induction motor
    Imadeddine Harzelli
    Arezki Menacer
    Tarek Ameid
    Journal of Ambient Intelligence and Humanized Computing, 2020, 11 : 2519 - 2538