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<p>This paper presents advanced control strategies for acute leukemia therapy by incorporating a nature-inspired optimization algorithm known as the RedFox Optimizer. Inspired by the hunting behavior of red foxes, this algorithm employs distance-estimation strategies to execute efficient and targeted jumps toward the optimal solution. The primary objective is to determine an optimal treatment strategy that minimizes leukemic cell populations while preserving healthy cells within safe physiological limits. The effectiveness of chemotherapy is modeled using a therapy function embedded within a dynamic leukemia model. To evaluate the performance of various control approaches, a numerical comparison is conducted among four nonlinear controllers: Impulsive Adaptive Sliding Mode Control, Adaptive Terminal Sliding Mode Control, Integral Super-Twisting Sliding Mode Control, and conventional Sliding Mode Control. Lyapunov stability theory is utilized to verify the stability of the proposed control frameworks. Simulation results confirm the effectiveness of the RedFox-optimized controllers in achieving therapeutic goals under both monotonic and non-monotonic therapy protocols.</p>

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RedFox optimized control designs for acute leukemia therapy

  • 期刊论文

  • 发表日期：

    2026年1月19日

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  • M. M. Butt,
  • A. Mughees,
  • F. Ahmed,
  • I. Ahmad

摘要

This paper presents advanced control strategies for acute leukemia therapy by incorporating a nature-inspired optimization algorithm known as the RedFox Optimizer. Inspired by the hunting behavior of red foxes, this algorithm employs distance-estimation strategies to execute efficient and targeted jumps toward the optimal solution. The primary objective is to determine an optimal treatment strategy that minimizes leukemic cell populations while preserving healthy cells within safe physiological limits. The effectiveness of chemotherapy is modeled using a therapy function embedded within a dynamic leukemia model. To evaluate the performance of various control approaches, a numerical comparison is conducted among four nonlinear controllers: Impulsive Adaptive Sliding Mode Control, Adaptive Terminal Sliding Mode Control, Integral Super-Twisting Sliding Mode Control, and conventional Sliding Mode Control. Lyapunov stability theory is utilized to verify the stability of the proposed control frameworks. Simulation results confirm the effectiveness of the RedFox-optimized controllers in achieving therapeutic goals under both monotonic and non-monotonic therapy protocols.