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LabVIEW-based Classic, Fuzzy and Neural Controllers Algorithm Design Applied to a Level Control Prototype

机译:基于LabVIEW的经典,模糊和神经控制器算法设计应用于电平控制原型

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This work presents the algorithm design of classic control, fuzzy control and neural control applied to a level control prototype. Classic control systems use PI and PID control actions; in order to tune such actions, Ziegler and Nichols oscillating method was used. It was designed a proportional, derivative and incremental fuzzy control system. As well, an inverse mode neural controller and an intern model neural controller are presented. As a first stage, simulation results were obtained using Matlab. Afterwards, an experimental implementation for each controller was carried out using LabVIEW based virtual instruments; a comparison between the functionalities of the presented controllers is done. Finally, the neural control system was implemented in an FPGA and the performance was compared to the one implemented in the LabVIEW virtual instruments.
机译:该工作介绍了应用于电平控制原型的经典控制,模糊控制和神经控制的算法设计。 经典控制系统使用PI和PID控制操作; 为了调整这些动作,使用Ziegler和Nichols振荡方法。 它设计了一种比例,衍生和增量模糊控制系统。 同样,提出了逆模式神经控制器和实习模型神经控制器。 作为第一阶段,使用MATLAB获得模拟结果。 之后,使用基于LabView的虚拟仪器进行每个控制器的实验实现; 所提出的控制器功能之间的比较完成。 最后,神经控制系统在FPGA中实现,并将性能与LabVIEW虚拟仪器中实现的。

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