期刊文献+

模糊RBF神经网络在麻醉深度控制系统中的应用 被引量:2

Application of Fuzzy RBF Neural Network Control System in Depth of Anesthesia
下载PDF
导出
摘要 麻醉深度通常用病人的平均动脉压(MAP)值来直接反应和度量。针对平均动脉压的时变、非线性特点,提出了基于模糊RBF神经网络的麻醉深度PID控制系统。通过采用模糊RBF神经网络对检测到的平均动脉压值进行模糊化处理及神经网络辨识,从而在线整定PID控制器各个参数,以获得更好的控制效果。MATLAB仿真结果表明模糊RBF神经网络用于麻醉深度控制具有良好的动态响应性能。 In the perioperative process,the patient's mean arterial pressure(MAP) value was used to reflect the anesthesia depth.As the mean arterial pressure was a time-varying and nonlinear variable,fuzzy RBF neural network control system in depth of anesthesia was studied.The detected MAP value was fuzzily processed and identified by fuzzy RBF neural so that PID controller tuned various parameters on-line by fuzzy RBF neural network.Fuzzy RBF neural network controller performance simulation was realized by software MATLAB,the results showed that the fuzzy RBF neural network control system for anesthesia depth control has better dynamic responses performance.
出处 《西华大学学报(自然科学版)》 CAS 2012年第2期58-61,共4页 Journal of Xihua University:Natural Science Edition
关键词 模糊控制 RBF神经网络 PID 平均动脉压 fuzzy control RBF neural network PID mean artery pressure
  • 相关文献

参考文献5

二级参考文献27

共引文献32

同被引文献22

  • 1于布为.理想麻醉状态与麻醉深度监测[J].广东医学,2005,26(6):723-724. 被引量:31
  • 2陈杭,王选,陈新忠,葛霁光.基于PID闭环控制算法的麻醉靶控输注给药的研究[J].中国生物医学工程学报,2007,26(2):204-207. 被引量:8
  • 3庄心良,曾因明,陈伯銮.现代麻醉学[M].北京:人民卫生出版社,2004∶ 7.
  • 4LOCHER S, STADLER K S, BOEHLEN T, et al. A new closed-loop control system for isoflurance using bispectral index outpertbrms manual control [ J ]. Anesthesiology, 2004, 101 (3): 591-602.
  • 5B1BIAN S, DUMONT G A, BLACK I, et al. Closed-loop target- controlled infusion system: Stability and performance aspects [J]. Mil Med, 2015, 180(3): 96-103.
  • 6BRUHN J, MYLES P S, SNEYD R, et al. Depth of anesthesia monitoring: what's available, what's validated and what's next? [ J ]. Br J Anesth, 2006, 97: 85-94.
  • 7GUO Z G, J]A X P, WANG X Y, et al. Bispectral index for monitoring anesthetic depth in patients with severe burns receiving target-controlled infusion of remifentanil and propofol [J ]. Genet Mol Res, 2015, 14(3): 7597-7603.
  • 8GLEN J B, ENGBERS F H. The influence of target concentration, equilibration rate constant (ke0) and pharmacokinetic model on the initial propofol dose delivered in effect-site target-controlled infusion[ J ]. Anansthesia, 2016, 71 (3): 306-314.
  • 9ASTRLM K J, HAGGLUND T. Revising the Ziegler-Nichols step response method for PID control [ J]. J Process Control, 2004, 14 (6): 635-650.
  • 10李成利,黄存柱,苗建.基于模糊神经网络的温度控制系统设计[J].微计算机信息,2010,26(7):75-76. 被引量:4

引证文献2

二级引证文献13

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部