基于大腦狀態(tài)指數(shù)的粒子群優(yōu)化-模糊麻醉閉環(huán)控制
發(fā)布時(shí)間：2018-08-17 11:23
【摘要】：針對(duì)麻醉用藥的個(gè)體差異,術(shù)中麻醉維持的復(fù)雜性和不確定性,以及當(dāng)前監(jiān)測(cè)手段存在的缺陷,傳統(tǒng)麻醉深度PID控制器不能滿足其非線性控制需要,而以往麻醉深度(DOA)模糊控制器的規(guī)則完全依賴于經(jīng)驗(yàn)調(diào)節(jié),因此無(wú)法達(dá)到預(yù)期的控制效果。本研究建立了以大腦狀態(tài)指數(shù)(CSI)為反饋?zhàn)兞康哪：樽黹]環(huán)控制系統(tǒng),并采用粒子群算法同時(shí)優(yōu)化基于CSI的變化和異丙酚輸出率之間的模糊控制規(guī)則和隸屬度函數(shù)。通過(guò)系統(tǒng)仿真將CSI值的目標(biāo)設(shè)定在40和30,并加入高斯噪聲以模擬臨床干擾。實(shí)驗(yàn)表明,該系統(tǒng)能準(zhǔn)確、快速、平穩(wěn)地達(dá)到CSI預(yù)設(shè)值,且在噪聲干擾下,無(wú)明顯擾動(dòng)。經(jīng)粒子群優(yōu)化(PSO)過(guò)的基于CSI模糊控制器應(yīng)用在DOA閉環(huán)控制系統(tǒng)具有較好的穩(wěn)定性及魯棒性。
[Abstract]:In view of the individual differences in anesthetic use, the complexity and uncertainty of anesthetic maintenance during operation, and the defects of current monitoring methods, the traditional PID controller for anesthetic depth can not meet its nonlinear control needs. In the past, the rule of (DOA) fuzzy controller for anesthetic depth was completely dependent on experience adjustment, so it could not achieve the desired control effect. In this study, a fuzzy closed loop control system based on cerebral state index (CSI) was established. Particle swarm optimization (PSO) was used to optimize the fuzzy control rules and membership function based on CSI and propofol output rate simultaneously. The target of CSI is set at 40 and 30 by system simulation, and Gao Si noise is added to simulate clinical interference. The experimental results show that the system can reach the CSI preset accurately, quickly and smoothly, and there is no obvious disturbance under the noise disturbance. The application of CSI fuzzy controller based on CSI fuzzy controller based on particle swarm optimization (PSO) (PSO) overpass has good stability and robustness in DOA closed-loop control system.
【作者單位】： 中南大學(xué)地球科學(xué)與信息物理學(xué)院;中南大學(xué)湘雅醫(yī)院麻醉科;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(81171053)
【分類號(hào)】：R312;R614
本文編號(hào)：2187472
[Abstract]:In view of the individual differences in anesthetic use, the complexity and uncertainty of anesthetic maintenance during operation, and the defects of current monitoring methods, the traditional PID controller for anesthetic depth can not meet its nonlinear control needs. In the past, the rule of (DOA) fuzzy controller for anesthetic depth was completely dependent on experience adjustment, so it could not achieve the desired control effect. In this study, a fuzzy closed loop control system based on cerebral state index (CSI) was established. Particle swarm optimization (PSO) was used to optimize the fuzzy control rules and membership function based on CSI and propofol output rate simultaneously. The target of CSI is set at 40 and 30 by system simulation, and Gao Si noise is added to simulate clinical interference. The experimental results show that the system can reach the CSI preset accurately, quickly and smoothly, and there is no obvious disturbance under the noise disturbance. The application of CSI fuzzy controller based on CSI fuzzy controller based on particle swarm optimization (PSO) (PSO) overpass has good stability and robustness in DOA closed-loop control system.
【作者單位】： 中南大學(xué)地球科學(xué)與信息物理學(xué)院;中南大學(xué)湘雅醫(yī)院麻醉科;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(81171053)
【分類號(hào)】：R312;R614
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，本文編號(hào)：2187472
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