摘要
针对中车株洲电力机车有限公司设计的HXD1-C64电力机车,提出一种基于两阶段自适应Gauss配点重构的伪谱法,用于列车优化操纵问题高效快速求解.首先,建立了HXD1-C64电力机车优化操纵数学模型;然后,在推导Legendre-Gauss配点公式的基础上,给出控制变量两阶段自适应Gauss配点策略,第1阶段采用对分配点,第2阶段引入斜率变化分析对控制变量配点进行自适应细分和合并;最后,在运行时间最短目标下对HXD1-C64电力机车优化操纵进行仿真实验.结果显示,相较于控制变量参数化方法和传统高斯伪谱方法(Gauss pseudospectral method,GPM),改进方法获得了更优性能指标和牵引力控制品质,计算时间分别减少91.93%和33.88%,表明了所提方法的有效性.
A two-stage adaptive Gauss re-collocation pseudospectral approach is proposed for solving optimization operation problems of HXD1-C64 electric locomotive designed by CRRC(China Railway Rolling Stock Corporation)Zhuzhou Institute Co.,LTD.Firstly,the optimization operation mathematical model of HXD1-C64 electric locomotive is established.Next,the Legendre-Gauss collocation formula is derived and then a two-stage adaptive Gauss collocation strategy is given,where a dichotomy collocation is adopted in the first stage and a slope change rate analysis is introduced in the second stage to adaptively subdivide or eliminate control variable collocation points.Finally,the simulation tests are carried out on HXD1-C64 electric locomotive to achieve time minimum operation.Simulation results show that the improved method obtains better performance index and traction control quality,compared with the control variable parameterization algorithm and the traditional Gauss pseudospectral method(GPM),while the computational time decreases by 91.93%and 33.88%,respectively,revealing the effectiveness of the proposed approach.
作者
刘平
胡云卿
廖俊
樊力
黎向宇
刘兴高
LIU Ping;HU Yun-Qing;LIAO Jun;FAN Li;LI Xiang-Yu;LIU Xing-Gao(Key Laboratory of Industrial Wireless Network and Networked Control,Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing,College of Automation,Chongqing University of Posts and Telecommunications,Chongqing 400065;China Railway Rolling Stock Corporation(CRRC)Zhuzhou Institute Co.,LTD,Zhuzhou 412000;State Key Laboratory of Industry Control Technology,College of Control Science and Engineering,Zhejiang University,Hangzhou 310027)
出处
《自动化学报》
EI
CSCD
北大核心
2019年第12期2344-2354,共11页
Acta Automatica Sinica
基金
国家自然科学基金(61803060,51705050)
重庆市教委科学技术研究项目(KJQN201800635,KJQN201804306)
工业控制技术国家重点实验室(浙江大学)开放课题(ICT1900359)资助~~
