Design and implementation of a RBF-based PI Controller for PMSM Drives

Phan-Thanh Nguyen, M. Nguyen
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Abstract

This work presents a hardware implementation of a RBF NN (Radial Basis Function Neural Network), then use this RBF NN to design a PI controller for PMSM (Permanent Magnet Synchronous Motor) drives. In this paper, firstly, the mathematical model of PMSM drives and the architecture of the RBF NN which consists of an input layer, a hidden layer of nonlinear processing neurons with Gaussian function and an output layer are described. Secondly, a very high speed IC hardware description language (VHDL) is adopted to describe the behavior of the RBF - PI Controller, and the data type applies 32bit length Q24 format and 2's complement operation. Additionally, finite state machine (FSM) is applied for reducing the hardware resource usage. Thirdly, to verify the correctness of the designed VHDL code for computing the RBF-PI, based on electronic design automation (EDA) simulator link, a co-simulation work is constructed by Simulink and ModelSim which the input stimuli and output responses are run in Simulink and the computation of the RBF-PI is performed in ModelSim. Finally, some simulation results validate the effectiveness of the proposed RBF-based PI (RBF-PI) Controller for PMSM Drives.
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基于rbf的永磁同步电机PI控制器的设计与实现
本文提出了一种径向基函数神经网络的硬件实现,然后利用该RBF神经网络设计了永磁同步电机驱动的PI控制器。本文首先描述了永磁同步电机驱动的数学模型和由输入层、高斯函数非线性处理神经元隐含层和输出层组成的RBF神经网络的结构。其次,采用非常高速的IC硬件描述语言(VHDL)来描述RBF - PI控制器的行为,数据类型采用32位长度Q24格式和2的补码运算。此外,还采用有限状态机(FSM)来减少硬件资源的使用。第三,为了验证所设计的计算RBF-PI的VHDL代码的正确性,基于EDA (electronic design automation, EDA)模拟器链接,利用Simulink和ModelSim构建了一个联合仿真工作,在Simulink中运行输入刺激和输出响应,在ModelSim中计算RBF-PI。最后,仿真结果验证了所提出的基于rbf的PI (RBF-PI)控制器在永磁同步电机驱动中的有效性。
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