ass日本风韵熟妇pics男人扒开女人屁屁桶到爽|扒开胸露出奶头亲吻视频|邻居少妇的诱惑|人人妻在线播放|日日摸夜夜摸狠狠摸婷婷|制服 丝袜 人妻|激情熟妇中文字幕|看黄色欧美特一级|日本av人妻系列|高潮对白av,丰满岳妇乱熟妇之荡,日本丰满熟妇乱又伦,日韩欧美一区二区三区在线

基于補償自適應(yīng)控制算法的車輛狀態(tài)參數(shù)估計
CSTR:
作者:
作者單位:

作者簡介:

通訊作者:

中圖分類號:

基金項目:

國家自然科學基金資助項目(51175043,、51205022)


Estimation of Vehicle Status Parameters Based on Compensation Adaptive Control Algorithm
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 圖/表
  • |
  • 訪問統(tǒng)計
  • |
  • 參考文獻
  • |
  • 相似文獻
  • |
  • 引證文獻
  • |
  • 資源附件
  • |
  • 文章評論
    摘要:

    為實現(xiàn)用于車輛動力學穩(wěn)定性控制的狀態(tài)參數(shù)準確估計,基于自適應(yīng)控制理論,針對三自由度車輛動力學模型,,提出一種補償更新律自適應(yīng)控制估計方法,該方法能夠?qū)崿F(xiàn)對縱向車速,、車輛質(zhì)量及轉(zhuǎn)動慣量的估計,。通過原地起步直線加速工況和雙移線工況的仿真和硬件在環(huán)仿真試驗,,表明該方法能夠?qū)崿F(xiàn)對運動狀態(tài)的快速跟蹤及參數(shù)的準確估計,,滿足車輛在線估計需求,。

    Abstract:

    Accurate estimation of vehicle status parameters is important to vehicle stability control. Combination of 3-DOF vehicle dynamics model and adaptive control algorithm, proposed a method that modifies adaptive law through compensation was proposed to estimate vehicle parameters correctly. Bases on the method, the vehicle dynamics model was simplified to reduce the calculation burden and improve the real time performance. The starting and acceleration driving conditon and double lane change conditon were designed for the simulation and the hardware-in-loop test. Finally, both the simulation results and hardware-in-loop test results indicate that the proposed method could estimate the vehicle mass and moment of inertia more precisely and faster compared to the adaptive algorithm without compensation and satisfy the requirement of vehicle online estimation.

    參考文獻
    相似文獻
    引證文獻
引用本文

林 程,周逢軍,徐志峰,曹萬科,董愛道.基于補償自適應(yīng)控制算法的車輛狀態(tài)參數(shù)估計[J].農(nóng)業(yè)機械學報,2014,45(11):1-8. Lin Cheng, Zhou Fengjun, Xu Zhifeng, Cao Wanke, Dong Aidao. Estimation of Vehicle Status Parameters Based on Compensation Adaptive Control Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(11):1-8.

復制
分享
文章指標
  • 點擊次數(shù):
  • 下載次數(shù):
  • HTML閱讀次數(shù):
  • 引用次數(shù):
歷史
  • 收稿日期:2013-12-13
  • 最后修改日期:
  • 錄用日期:
  • 在線發(fā)布日期: 2014-11-10
  • 出版日期:
文章二維碼