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

基于局部線性化的汽車質(zhì)心側偏角估計
CSTR:
作者:
作者單位:

作者簡介:

通訊作者:

中圖分類號:

基金項目:

國家高技術研究發(fā)展計劃(863計劃)資助項目(2009AA11Z216);國家自然科學基金資助項目(50908008)


Estimation of Vehicle Sideslip Angle Based on Local Linearization
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:

    對于汽車側偏角估計,,現(xiàn)有非線性狀態(tài)觀測器反饋增益的設計大多采用解析法,但其僅適用于表達式較簡單的輪胎模型,。提出一種基于局部線性化設計狀態(tài)觀測器反饋增益的數(shù)值方法,,使得采用精度更高,、表達式更復雜的輪胎模型成為可能。將非線性系統(tǒng)在狀態(tài)變量空間中離散化,,采用數(shù)值計算獲得若干個工作點處的反饋增益,。為便于實時觀測應用,這些離散的反饋增益值被擬合為關于狀態(tài)變量的函數(shù),。在一個高精度的車輛動力學實時仿真環(huán)境中驗證了所提出側偏角估計方法的有效性及其對參數(shù)變化的魯棒性,。仿真結果表明,所提出估計方法估計精度較高,,具有較好的魯棒性,。

    Abstract:

    A numerical methodology for designing observer feedback gains based on local linearization was proposed to make employing tire models with a higher accuracy and more complicated expressions become possible. The proposed methodology was implemented by discretization of the nonlinear system in the state space and calculation of the feedback gains at a certain given number of operating points using numerical approaches. The gains at discretized operating points were fitted to the expressions with respect to state variables to facilitate realtime observation and implementations. The effectiveness and parameter variation robustness of the proposed methodology were evaluated in a highfidelity vehicle dynamics simulation environment, and the simulation results show that the proposed methodology has a high estimation accuracy and good robustness.

    參考文獻
    相似文獻
    引證文獻
引用本文

丁能根,李丹華,許景,王健,余貴珍.基于局部線性化的汽車質(zhì)心側偏角估計[J].農(nóng)業(yè)機械學報,2012,43(1):6-11. Ding Nenggen, Li Danhua, Xu Jing, Wang Jian, Yu Guizhen. Estimation of Vehicle Sideslip Angle Based on Local Linearization[J]. Transactions of the Chinese Society for Agricultural Machinery,2012,43(1):6-11.

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:
  • 最后修改日期:
  • 錄用日期:
  • 在線發(fā)布日期: 2012-01-12
  • 出版日期:
文章二維碼