基于自适应分数阶优化器的人工呼吸器最佳倾斜控制器设计

Debasis Acharya, Dushmanta Kumar Das
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摘要

人工呼吸机是医疗领域中重要的呼吸支持系统,尤其适用于危重病人。确保呼吸机保持预定的气道压力至关重要,因为压力变化可能会对大脑和肺部造成伤害。因此,实现精确的压力跟踪是设计压力控制呼吸机(PCV)最佳控制器的首要目标。为满足这一需求,我们提出了一种新方法:为 PCV 系统量身定制的混合整数倾斜分数阶积分和整数阶推导控制器。该控制器不同参数的增益采用自适应混沌搜索分数阶顶峰优化算法进行优化,并辅以基于高斯的突变算子。此外,控制器的设计还能最大限度地减少输出信号的振荡,从而降低物理风险并减小所需执行器的尺寸。优化控制器的功效在各种情况下都得到了进一步检验,包括不同年龄组患者的不同肺阻力和顺应性。此外,还将气管导管阻力对气压的影响作为 PCV 系统的潜在干扰进行了评估。通过综合测试,所提出的控制器在将气道压力精确跟踪到所需水平方面表现出卓越的性能。在所有评估案例中,所提出的控制器结构和配套算法均优于现有解决方案。值得注意的是,在系统响应时间、过冲和稳定时间方面都有所改进。这凸显了采用先进控制策略对提高医疗环境中 PCV 系统的功能性和安全性的重要意义。
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An adaptive fractional order optimizer based optimal tilted controller design for artificial ventilator
Artificial ventilators are vital respiratory support systems in the field of medical care, especially for patients in critical condition. It is crucial to make sure the ventilator keeps the intended airway pressure because variations might be harmful to the brain and lungs. Thus, achieving accurate pressure tracking is a primary objective in designing optimal controllers for pressure‐controlled ventilators (PCVs). To address this need, a novel approach is proposed: a mixed integer tilted fractional order integral and integer order derivation controller tailored for PCV systems. The gains of different parameters of the proposed controller are optimized using an adaptive chaotic search fractional order class topper optimization algorithm, augmented with a Gaussian‐based mutation operator. Moreover, the controller is designed to minimize oscillations in its output signal, thereby mitigating physical risks and reducing the size of actuators required. The efficacy of the optimized controller is further examined across various scenarios, including different lung resistances and compliances across different age groups of patients. Additionally, the impact of endotracheal tube resistance on air pressure is assessed as a potential disturbance in the PCV system. Through comprehensive testing, the proposed controller demonstrates superior performance in accurately tracking airway pressure to the desired levels. Across all evaluated cases, the proposed controller structure and accompanying algorithm outperform existing solutions. Notably, improvements are observed in system response time, overshoot, and settling time. This underscores the significance of employing advanced control strategies to enhancing the functionality and safety of PCV systems in medical settings.
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