Safe optimal control of cancer using a Control Barrier Function technique
Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved..
This paper addresses the problem of designing a safe and optimal control strategy for typical cancer using the Control Barrier Function (CBF) technique. Cancer is a complex and highly dynamic disease characterized by uncontrolled cell growth and proliferation. By formulating the cancer dynamics as a control system, this study introduces a CBF-based controller that guides the cancerous tissue towards safe and controlled behaviors. The controller is designed to simultaneously optimize treatment efficacy and patient safety. The methodology involves modeling the cancer growth dynamics, incorporating relevant biological constraints, and designing the CBF-based controller to regulate the tumor's evolution within acceptable bounds. Simulation results demonstrate the effectiveness of the CBF-based strategy in achieving safe and optimal cancer control. The controller showcases the ability to drive the cancerous tissue towards desired states while respecting predefined safety constraints.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:369 |
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| Enthalten in: |
Mathematical biosciences - 369(2024) vom: 15. Feb., Seite 109142 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Ahmadi, Zahra [VerfasserIn] |
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| Links: |
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| Themen: |
Cancer therapy |
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| Anmerkungen: |
Date Completed 21.02.2024 Date Revised 21.02.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.mbs.2024.109142 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a This paper addresses the problem of designing a safe and optimal control strategy for typical cancer using the Control Barrier Function (CBF) technique. Cancer is a complex and highly dynamic disease characterized by uncontrolled cell growth and proliferation. By formulating the cancer dynamics as a control system, this study introduces a CBF-based controller that guides the cancerous tissue towards safe and controlled behaviors. The controller is designed to simultaneously optimize treatment efficacy and patient safety. The methodology involves modeling the cancer growth dynamics, incorporating relevant biological constraints, and designing the CBF-based controller to regulate the tumor's evolution within acceptable bounds. Simulation results demonstrate the effectiveness of the CBF-based strategy in achieving safe and optimal cancer control. The controller showcases the ability to drive the cancerous tissue towards desired states while respecting predefined safety constraints | ||
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