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Adaptive control for anesthesia based on a simple fractional-order model

机译:基于简单分数阶模型的麻醉自适应控制

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This article addresses the problem of designing an adaptive control for anesthesia. A simple fractional-order model is first proposed for anesthesia controller design. Parallel to this model, an identification algorithm is designed relying on Lyapunov stability theory to estimate the parameters in this model, and shown its ability to capture the behavior of the PK/PD model of the depth of anesthesia. Then an MRAC for anesthesia based on this simple model is designed, ensuring the stability and the convergence of the tracking error to zero. Fundamental to these designs is the Lyapunov Theory available in the literature and the extension of Barbalat Lemma for the integer-order systems to fractional-order systems proven in this paper. Simulations illustrate the effectiveness and robustness of the proposed control.
机译:本文解决了设计麻醉的自适应控件的问题。首先提出了一种简单的分数阶模型用于麻醉控制器设计。与该模型并行,设计了一种基于Lyapunov稳定性理论的识别算法,以估计该模型中的参数,并显示了其捕获麻醉深度PK / PD模型行为的能力。然后,基于此简单模型设计了用于麻醉的MRAC,以确保跟踪误差的稳定性和收敛性为零。这些设计的基础是文献中可用的李雅普诺夫理论,并将Barbalat Lemma从整数阶系统扩展到本文证明的分数阶系统。仿真说明了所提出控制的有效性和鲁棒性。

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