文档介绍：基于自适应神经模糊系统的人工心脏搏动流控制系统的仿真研究
摘要心脏病重症患者最有效的治疗手段是心脏移植,但由于供体的缺乏限制了该技术的推广。目前,人工心脏,作为一种心室辅助手段,已广泛地应用于重症心衰患者的治疗或等待移植的过渡桥梁。为了适应人体的生理需求,人工心脏需要产生搏动的血流。本文采用自适应神经模糊推理算法(ANFIS), 针对人工心脏的搏动流控制系统进行了数值研究。
本文首先主要针对人工心脏的研究意义进行阐述,概括描述了人工心在的发展历史及展望。其次对无刷直流电机的结构,工作原理,数学模型,运动方程等做了详细论述,主要是为无刷电机转速控制模型的建立提供理论依据。再次介绍模糊控制的结构与原理和隶属度函数以及ANFIS的结构与原理,并详细地介绍Matlab中的anfis工具箱。最后结合无刷直流电机和模糊控制及ANFIS的理论知识对电机本体与电机控制部分进行仿真,并对分析其仿真结果。
仿真结果证明ANFIS可以将神经网络方法和模糊逻辑方法融合在一起,借助神经网络的信息存贮能力和学习能力,在对广泛选择的样本进行学习后,优化控制规则、各语言变量的隶属函数及每条规则的输出函数。在此基础上搭建的电机控制系统具有良好的控制性,适用于人工心脏的仿真。,转速的峰值为8000rpm,其平滑波动范围为4500rpm--5500rpm,仿真后的波形与给定一致。
关键词人工心脏无刷直流电机模糊控制系统 ANFIS
Research on a Pulsatile Flow Control System for
Artificial Hearts Using Adaptive Neural Fuzzy Algorithm
Abstract Most effective in patients with severe heart disease treatment is heart transplant, but due to lack of donor limits the promotion of the technology. At present, the artificial heart, as a ventricular assist means, has been widely used in the treatment of patients with severe heart failure or a bridge waiting for a transplant. In order to meet the body's physiological needs, need to generate artificial heart pulsating flow. In this paper, adaptive neural fuzzy inference algorithm (ANFIS), for the artificial heart beat flow control system is numerically studied.
This paper focuses artificial heart research significance elaborate, general description of the artificial heart in the history of the development and prospects. Second, the structure of the brushless DC motor, working principle, mathematical model, the equations of motion, and so do a detailed discussion, primarily for the brushless motor speed control model provides a theoretical basis. Reintroduce the structure of fuzzy control theory and the membership function and the ANFIS structure and principle, and a detailed description of anfis toolbox in Matlab. Finally, brushless DC motor and fuzzy control and ANFIS theoretical knowledge of the motor body and motor control part of th