【摘要】 控制过程中,对象常具有非线性、时滞、不确定性和参数时变的特点,而普通模糊控制器因控制规则固定,影响控制效果.针对这些问题,基于模糊神经网络的方法,设计一种模糊控制器,对学习算法进行推导,实现模糊控制规则的自生成和参数自调整.经仿真实验并根据其特点,将之应用于烧结控制过程,表明该控制器有良好的控制性能.更多还原

【Abstract】 During the process of control, there are some control objects with characteristics of nonlinearity, time lag, uncertainty and frequent changes of parameters. For these objects, fuzzy controller’s control effect is weakened because it’s control rules are fixed in advance. In order to improve this condition,the method of fuzzy neural network to design a fuzzy controller is used. A new learning algorithm is derived theoretically to realize the fuzzy rules’ automatic generating and parameter-tuning of network. The simulation experiment and application in sintering controlling based on the fuzzy controller’s features show that this controller has better performance.更多还原