Optimized Integral Super-Twisting Sliding Mode Control for Acute Leukemia Therapy
This paper presents an optimized nonlinear controller, the Integral Super-Twisting Sliding Mode Control (ISTSMC), for acute leukemia therapy. To enhance its performance, we introduce the RedFox Optimization Algorithm, a nature-inspired technique based on the hunting behavior of red foxes. This algor...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/7/1077 |
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| Summary: | This paper presents an optimized nonlinear controller, the Integral Super-Twisting Sliding Mode Control (ISTSMC), for acute leukemia therapy. To enhance its performance, we introduce the RedFox Optimization Algorithm, a nature-inspired technique based on the hunting behavior of red foxes. This algorithm is utilized to fine-tune the controller parameters, ensuring optimal achievement of control objectives. We discuss the fundamentals of ISTSMC, Sliding Mode Control, and Synergetic Control, detailing their optimization methodology using the RedFox Algorithm. The effectiveness of ISTSMC is evaluated through numerical simulations and compared with traditional Sliding Mode Control (SMC) and Synergetic Control (SC). The results demonstrate that ISTSMC achieves superior performance with a steady state error of 53.85, a settling time of 59.60, and a transient time of 4.7942, significantly outperforming SMC and SC. Additionally, ISTSMC reduces leukemic cell levels to a safe threshold more efficiently while maintaining healthy cell populations within acceptable limits. These improvements highlight the potential of ISTSMC in optimizing chemotherapy administration, ensuring better patient outcomes while minimizing side effects. |
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| ISSN: | 2227-7390 |