【摘要】 在高精度恒温系统温度控制中,为了克服温度这种被控对象因其纯滞后、非线性和大惯性特性以及被控对象参数的时变性对精度的影响,采用了BP神经模糊PID控制器代替模糊控制,使推理速度加快,并通过在系统运行时不断地增加和完善模糊控制规则,不断提高系统控制的精度。仿真分析结果表明,经过BP神经网络优化学习后,系统具有良好的控制性能和自适应能力,很好地满足了大滞后系统对高精度控温与快速性的要求。更多还原

【Abstract】 In order to overcome the effects of temperature on the precision,as a result of this charged object of its time delay,nonlinear,inertial characteristics and time-varying of the charged object,the fuzzy controler was replaced by BP neural-fuzzy PID controller.The reasoning was speeded up,the fuzzy control rules was increased continusly,and the accuracy of the system control was improved when the system was running.Simulation analysis result shows that the control system has good performance of adaptive capacity,high-precision temperature control,and it meets the requirements of rapid in large time delay system.更多还原