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在设计模糊控制器时，考虑到偏差和偏差变化在不同的控制阶段由不同的作用，利用神 经网络对模糊控制器的参数进行调整，达到优化模糊控制器的作用．通过对具有纯滞后的二阶系 统进行的仿真试验表明，与常规的模糊控制器相比，改进后的控制器对被控对象的参数的变化具有 更强的适应性．
In the design of fuzzy controller, taking into account changes in bias and deviation in different control stages by different roles, the use of neural network parameters of the fuzzy controller to adjust, to optimize the role of fuzzy controller. The simulation results of the second-order system with pure hysteresis shows that the improved controller has more adaptability to the change of the controlled object’s parameters than the conventional fuzzy controller.