RESEARCH ON FRACTIONAL ORDER TIME DOMAIN SUBSPACE MODEL OF PEMFC BASED ON ALMBO ALGORITHM

被引：0
|
作者：
Sun C. [1 ]
Qi Z. [1 ]
Ye W. [1 ]
Shan L. [1 ]
机构：
[1] School of Automation, Nanjing University of Science and Technology, Nanjing
来源：
Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2023年 / 44卷 / 01期
关键词：
ALMBO; global optimization; parameter identification; proton exchange membrane fuel cell;
D O I：
10.19912/j.0254-0096.tynxb.2021-0971
中图分类号：
学科分类号：
摘要：
The power generation process of proton exchange membrane fuel cell （PEMFC） is complex to describe，this paper，considering the fractional order characteristics of PEMFC system，proposes an optimization based fractional order time domain subspace identification method，and establishes a fractional order state space model of PEMFC. The fractional differential theory is combined with subspace identification method，and Poisson filter is used to filter the input and output data. The weight matrix is introduced to improve the accuracy of identification. Then，a mutation reverse learning adaptive monarch butterfly optimization algorithm （ALMBO） is proposed for the identification of fractional order and other parameters. The mutation reverse learning strategy is introduced into the transfer operator，and the adaptive weight is integrated to improve the optimization accuracy and prevent falling into the local optimal solution. Finally，the simulation results verify the effectiveness of the algorithm，and the identification model can accurately describe the dynamic process of PEMFC. © 2023 Science Press. All rights reserved.
引用
收藏
页码：467 / 474
页数：7
相关论文
共 18 条
  • [1] PEM fuel cell fractional order modeling and identification［J］, IFAC proceedings volumes, 47, 3, pp. 2125-2131, (2014)
  • [2] WANG Z L, YANG D S, ZHANG H G., Stability analysis on a class of nonlinear fractional- order systems［J］, Nonlinear dynamics, 86, 2, pp. 1023-1033, (2016)
  • [3] Fractional order PID controller design for supply manifold pressure control of proton exchange membrane fuel cell［J］, Chemical product and process modeling, 14, 3, pp. 524-531, (2019)
  • [4] LIANG S，, Et al., Dynamic thermal modeling of PEMFC based on fractional order theory［J］, Control and decision, 15, 5, pp. 1078-1081, (2015)
  • [5] Experimental verification of on- chip CMOS fractional-order capacitor emulators［J］, Electronics letters, 52, 15, pp. 1298-1300, (2016)
  • [6] XUE C S，, QI Z D., Research on PEMFC fractional impedance characteristic modeling［C］, Proceedings of the 30th China Conference on Control and Decision Making, (2018)
  • [7] Research on electrical characteristics of state space modeling and parameter identifying of PEMFC, 34th Chinese Control Conference, (2015)
  • [8] BIAN H J, Et al., Research on PEMFC fractional model based on an improved genetic algorithm, 34th Chinese Control Conference, (2015)
  • [9] HU C., Research on PEMFC fractional order state space modeling and adaptive control［D］, (2017)
  • [10] GODOY E，, BETHOUX O，, Et al., Frequential identification of a proton exchange membrane fuel cell （PEMFC）fractional order model［J］, IFAC proceedings volumes, 21, 3, pp. 214-220, (2014)
12