Control of tumor growth by modern control methodologies

György Eigner, L. Kovács

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The role of modern control engineering in physiological controls cannot be questioned. However, practitioners have to face with many challenges in the field. The imprecise information of the state variables of the system to be controlled, significant inter- and intra-patient variability, limitations regard to the applied sampling frequency are just a few of them. The current study investigates a possible solution for those issues related to control of tumor growth. In order to describe the parameter variabilities Linear Parameter Varying (LPV) method has been used and extended by applying Tensor Product (TP) model transformation. We formulated the goals of the control by using Linear Matrix Inequalities (LMI). Parallel Distributed Control can be used based on the state-feedback gains obtained through LMI optimization. The unmeasurable states can be estimated by using Extended Kalman Filtering. By using these techniques we were able to realize a control framework which enforces our original nonlinear system to behave as a given reference system within limitations. We have found that the developed control framework operates satisfactory by reaching all of the determined goals of the control.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018 - THETA 21st Edition, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538622049
DOIs
Publication statusPublished - Jul 3 2018
Event21st IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018 - Cluj-Napoca, Romania
Duration: May 24 2018May 26 2018

Other

Other21st IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018
CountryRomania
CityCluj-Napoca
Period5/24/185/26/18

Fingerprint

Tumor Growth
Tumors
Methodology
Linear matrix inequalities
Matrix Inequality
Linear Inequalities
Extended Kalman Filtering
Product Model
Distributed Control
Model Transformation
State Feedback
Tensor Product
State feedback
Tensors
Nonlinear Systems
Nonlinear systems
Engineering
Sampling
Optimization

Keywords

  • Linear Matrix Inequality
  • Linear Parameter Varying
  • Parallel Distribution Control
  • Tensor Model transformation
  • tumor control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

Cite this

Eigner, G., & Kovács, L. (2018). Control of tumor growth by modern control methodologies. In 2018 IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018 - THETA 21st Edition, Proceedings (pp. 1-6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AQTR.2018.8402782

Control of tumor growth by modern control methodologies. / Eigner, György; Kovács, L.

2018 IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018 - THETA 21st Edition, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-6.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Eigner, G & Kovács, L 2018, Control of tumor growth by modern control methodologies. in 2018 IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018 - THETA 21st Edition, Proceedings. Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 21st IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018, Cluj-Napoca, Romania, 5/24/18. https://doi.org/10.1109/AQTR.2018.8402782
Eigner G, Kovács L. Control of tumor growth by modern control methodologies. In 2018 IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018 - THETA 21st Edition, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-6 https://doi.org/10.1109/AQTR.2018.8402782
Eigner, György ; Kovács, L. / Control of tumor growth by modern control methodologies. 2018 IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018 - THETA 21st Edition, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-6
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