基于软切换的电动机模糊神经网络控制器研究

Research on Fuzzy Neural Network Controller for Motor Based on Soft Wwitching

作为第三代控制理论的模糊逻辑控制和神经网络控制等智能策略虽已在电动机控制中得到了应用,但由于这两种智能控制策略各有明显的优点和缺点,单独使用一般都达不到理想效果,因此需将其结合应用组成控制器,常见的形式之一即为并联切换型模糊神经网络控制器[1]。然而,由模糊逻辑和神经网络并联而成的控制系统,如何实现切换控制一直是控制界研究的难点和热点[2]。设计出合适的切换控制,可以明显改善控制系统的性能,获得比连续控制更好的控制效果。为此,研究了将模糊软切换控制技术[3]引入并联切换型模糊神经网络控制器,该方案能使控制系统实现无扰平稳切换,取得较好的动、稳态性能,其有效性已通过电机控制的仿真得到验证。

As the third generation control theory, fuzzy logic control and neural network control, intelligent motor control strategy has been applied, but because of these two kinds of intelligent control strategies have obvious advantages and disadvantages, alone generally cannot reach the ideal effect, because of the need to combine the application controller. One of the common forms is the parallel switching type fuzzy. Neural network controller however, control system by fuzzy logic and neural network in parallel form, how to realize the switching control is always the hot and difficult control field. To design an appropriate switching control, can greatly improve the performance of the control system, To obtain better control effect than continuous control. Therefore, the research of the fuzzy control technology of soft switching into parallel switching type fuzzy neural network controller, this scheme can make the control system to realize the smooth switching without disturbance, better dynamic and static performance, its effectiveness has been through the simulation of motor control has been verified.