温度控制在大工业生产过程中具有重要作用,但是目前一些常规控制器往往存在着超调量大,滞后时间长等缺点。针对这些缺点,提出一种新型的智能温度控制器。该控制器充分利用了CMAC神经网络学习速度快和遗传算法能快速跳出局部最优的特点。仿真结果表明新型控制器具有稳定性好、控制准确、学习速度快等特点。 Temperature control plays an important role in the process of large industrial production, but some conventional controllers often have the disadvantages of large overshoot and long lag time. In response to these shortcomings, a new type of intelligent temperature controller is proposed. The controller makes full use of CMAC neural network learning speed and genetic algorithms can quickly jump out of the local optimal features. The simulation results show that the new controller has the characteristics of good stability, accurate control and fast learning speed.