用鲸鱼算法优化模糊分数阶PID，精准调控麻醉深度。
Advanced DOA Regulation with a Whale-Optimized Fractional Order Fuzzy PID Framework
- 结合模糊逻辑与分数阶控制，自适应调节参数
- 响应更快（2.5分钟），稳态误差更小（0.5）
- 适合临床智能麻醉系统，提升患者安全
本研究提出一种基于鲸鱼优化算法（WOA）的分数阶模糊PID（FOFPID）控制器，用于将双谱指数（BIS）维持在40至60的理想范围。该控制器融合模糊逻辑以适应个体生理差异，并利用分数阶动力学实现精细调节，动态调整控制增益。通过WOA优化控制器参数，包括分数阶阶数和模糊隶属函数，显著提升性能。在8种不同患者模型上测试显示，相比标准分数阶PID（FOPID）控制器，FOFPID的调节时间缩短至2.5分钟（原3.2分钟），稳态误差降低至0.5（原1.2）。结果表明其具有优异的鲁棒性与精度，为自动化麻醉给药提供可扩展的人工智能解决方案，有望改善临床实践与患者预后。
原文摘要 · Abstract (English)
This study introduces a Fractional Order Fuzzy PID (FOFPID) controller that uses the Whale Optimization Algorithm (WOA) to manage the Bispectral Index (BIS), keeping it within the ideal range of forty to sixty. The FOFPID controller combines fuzzy logic for adapting to changes and fractional order dynamics for fine tuning. This allows it to adjust its control gains to handle a person's unique physiology. The WOA helps fine tune the controller's parameters, including the fractional orders and the fuzzy membership functions, which boosts its performance. Tested on models of eight different patient profiles, the FOFPID controller performed better than a standard Fractional Order PID (FOPID) controller. It achieved faster settling times, at two and a half minutes versus three point two minutes, and had a lower steady state error, at zero point five versus one point two. These outcomes show the FOFPID's excellent strength and accuracy. It offers a scalable, artificial intelligence driven solution for automated anesthesia delivery that could enhance clinical practice and improve patient results.
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