【摘要】 针对射频消融温度控制系统中存在的非线性、时变性和滞后性特点，将自适应神经网络模糊推理系统(Adaptive-Network-based Fuzzy Inference Systems, ANFIS)应用于射频电极温度控制，并探讨其控制效果。通过MATLAB构建射频电极温度控制系统模型，对ANFIS、PID和Fuzzy-PID三种控制在模拟实际使用、目标温度从初始55℃变化至60℃、加热到20-24s之间加入±1℃干扰等三种不同条件下，进行仿真比较。仿真结果表明，相较于PID和Fuzzy-PID,ANFIS在射频电极温度控制中具有更好的响应速度和抗干扰能力，在面对复杂的温度变化和外部干扰时，ANFIS能够更加精准地调节温度，使其稳定到达目标温度。更多还原

【Abstract】 In view of the nonlinear, time-varying and hysteretic characteristics existing in the radiofrequency ablation temperature control system, the Adaptive-Network-based Fuzzy Inference Systems(ANFIS) is applied to the temperature control of the radiofrequency electrode, and its control effect is explored. Build a temperature control system model for RF electrodes using MATLAB,and compare the simulation experiments of ANFIS,PID,and Fuzzy PID control under three different conditions: simulating actual use, target temperature changing from initial 55 ℃ to 60 ℃,and adding ± 1 ℃ interference between heating and 20-24 seconds. The simulation results show that compared to PID and Fuzzy PID,ANFIS has better fast response and anti-interference ability in RF electrode temperature control. When facing complex temperature changes and external interference, ANFIS can more accurately adjust the temperature, making it stable to reach the target temperature.更多还原