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Neuro–Fuzzy Controller and Its Real Time Application

机译:神经模糊控制器及其实时应用

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Essence of the paper is to combine fuzzy logic and neural networks together, obtaining a robust, hardware friendly neuro-fuzzy controller suitable for real time application. Here, a simple rule base has been implemented on the Xilinx SPARTAN 3AN FPGA development board to bolster the feasibility and superiority of the neuro-fuzzy system (NFS) over fuzzy system (FS). Finally, the neuro-fuzzy controller has been realized to govern a classic control system problem of reference tracking like speed control of a separately excited dc motor using armature voltage control topology. Simulation results along with emulation testing have together concreted the effectiveness and superiority of such hybrid controller in real time applications.
机译:本文的实质是将模糊逻辑和神经网络结合在一起,以获得适用于实时应用的鲁棒,硬件友好的神经模糊控制器。在这里,已经在Xilinx SPARTAN 3AN FPGA开发板上实现了一个简单的规则库,以增强神经模糊系统(NFS)优于模糊系统(FS)的可行性和优越性。最后,已经实现了神经模糊控制器来控制参考跟踪的经典控制系统问题,例如使用电枢电压控制拓扑结构对单独励磁的直流电动机进行速度控制。仿真结果和仿真测试共同证明了这种混合控制器在实时应用中的有效性和优越性。

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