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首页> 外文期刊>International journal of hydrogen energy >Proton exchange membrane fuel cell-powered bidirectional DC motor control based on adaptive sliding-mode technique with neural network estimation
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Proton exchange membrane fuel cell-powered bidirectional DC motor control based on adaptive sliding-mode technique with neural network estimation

机译：质子交换膜燃料电池供电的双向直流电直流电直流电直流电直流电直流电机控制，具有神经网络估计的自适应滑模技术

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摘要

Proton exchange membrane fuel cell (PEMFC), according to its merits of high energy density, zero emission, and low noise, has been widely applied in industrial appliances. A full bridge converter is used to implement PEMFC-powered DC motor bidirectional rotation in this paper. For the sake of the regulations of DC motor angular velocity as well as bus voltage, an adaptive backstepping sliding-mode control (ABSMC) technique integrated with Chebyshev neural network (CNN) is proposed. Based on the equivalent-circuit method, the control-oriented model of the PEMFC-powered motor system is structured. By constructing Lyapunov function, the adaptive laws and control laws can be obtained to achieve bus voltage and angular velocity regulations simultaneously. Moreover, the proposed neural network is applied to estimate the uncertainties of the system through orthogonal basis Chebyshev polynomials. To highlight the advantages of proposed technique, a proportional-integral (PI) control was introduced subsequently and two controllers were compared via numerical simulations. The simulation results demonstrate that CNN estimation method in conjunction with backstepping sliding-mode shows fast and accurate response even though the existence of system uncertainties and external disturbances. (C) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
机译：质子交换膜燃料电池（PEMFC），根据其高能量密度，零排放和低噪声的优点，已广泛应用于工业用具。完整的桥接器转换器用于在本文中实现PEMFC供电的直流电机双向旋转。为DC电动机角速度的规定以及总线电压，提出了一种与Chebyshev神经网络（CNN）集成的自适应背杆式滑模控制（ABSMC）技术。基于等效电路方法，结构化的PEMFC动力电机系统的面向控制的模型。通过构建Lyapunov函数，可以获得自适应法律和控制定律以同时实现总线电压和角速度规范。此外，所提出的神经网络被应用于通过正交基流的Chebyshev多项式估计系统的不确定性。为了突出所提出的技术的优点，随后引入比例积分（PI）控制，通过数值模拟比较两个控制器。仿真结果表明，即使存在系统不确定性和外部干扰，CNN估计方法也与反向滑模的结合显示了快速准确的响应。 （c）2020氢能源出版物LLC。 elsevier有限公司出版。保留所有权利。

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