東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Real time control of an adaptive veh...

Murad, Mohannad.

Linked to FindBook

Google Book

Amazon

博客來

Real time control of an adaptive vehicular occupant restraint system using intelligent control techniques.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Real time control of an adaptive vehicular occupant restraint system using intelligent control techniques./
Author:	Murad, Mohannad.
Description:	136 p.
Notes:	Source: Dissertation Abstracts International, Volume: 70-10, Section: B, page: 6452.
Contained By:	Dissertation Abstracts International70-10B.
Subject:	Engineering, Automotive. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3381688
ISBN:	9781109426342

Real time control of an adaptive vehicular occupant restraint system using intelligent control techniques.
Murad, Mohannad.

Real time control of an adaptive vehicular occupant restraint system using intelligent control techniques. - 136 p.

Source: Dissertation Abstracts International, Volume: 70-10, Section: B, page: 6452.

Thesis (Ph.D.)--Oakland University, 2009.

Thousands of people die every year in car accidents. Existing restraint systems lack the capability of varying their output during the impact event. This research applies intelligent control techniques in the design of a real time controller for an adaptive restraint system to dramatically minimize occupant injuries during frontal crashes. The controller first task is to predict the maximum desired head and chest acceleration levels in a particular crash event. A methodology to develop a predictive Adaptive Neuro-Fuzzy Inference System (ANFIS) model to accomplish this aim is introduced. The controller's second task is to keep adjusting the restraint system continuously in order to maintain the actual head and chest accelerations below the targeted thresholds. Different configurations of fuzzy logic controllers FLCs are also designed to accomplish this aim. To optimize the FLCs, the controllers' parameters needed to be tuned. Tuning based on trial-and-error turned to be a tedious and time-consuming task and therefore a methodology to simplify the automatic tuning process of self organized FLCs is introduced. Due to the prohibitive cost of crash testing our system was designed and tested first with a lumped parameter model, second with a multi-body model and finally by using a complete crash simulation environment that link Madymo and Matlab.

ISBN: 9781109426342Subjects--Topical Terms:

1018477
Engineering, Automotive.

Real time control of an adaptive vehicular occupant restraint system using intelligent control techniques.
LDR:02342nam 2200301 4500 001 1403485
005 20111118095935.5
008 130515s2009 ||||||||||||||||| ||eng d
020 $a 9781109426342
035 $a (UMI)AAI3381688
035 $a AAI3381688
040 $a UMI $c UMI
100 1 $a Murad, Mohannad. $3 1682746
245 1 0 $a Real time control of an adaptive vehicular occupant restraint system using intelligent control techniques.
300 $a 136 p.
500 $a Source: Dissertation Abstracts International, Volume: 70-10, Section: B, page: 6452.
500 $a Advisers: Manohar Das; Ka D. Cheok.
502 $a Thesis (Ph.D.)--Oakland University, 2009.
520 $a Thousands of people die every year in car accidents. Existing restraint systems lack the capability of varying their output during the impact event. This research applies intelligent control techniques in the design of a real time controller for an adaptive restraint system to dramatically minimize occupant injuries during frontal crashes. The controller first task is to predict the maximum desired head and chest acceleration levels in a particular crash event. A methodology to develop a predictive Adaptive Neuro-Fuzzy Inference System (ANFIS) model to accomplish this aim is introduced. The controller's second task is to keep adjusting the restraint system continuously in order to maintain the actual head and chest accelerations below the targeted thresholds. Different configurations of fuzzy logic controllers FLCs are also designed to accomplish this aim. To optimize the FLCs, the controllers' parameters needed to be tuned. Tuning based on trial-and-error turned to be a tedious and time-consuming task and therefore a methodology to simplify the automatic tuning process of self organized FLCs is introduced. Due to the prohibitive cost of crash testing our system was designed and tested first with a lumped parameter model, second with a multi-body model and finally by using a complete crash simulation environment that link Madymo and Matlab.
590 $a School code: 0446.
650 4 $a Engineering, Automotive. $3 1018477
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, System Science. $3 1018128
690 $a 0540
690 $a 0544
690 $a 0790
710 2 $a Oakland University. $3 1019306
773 0 $t Dissertation Abstracts International $g 70-10B.
790 1 0 $a Das, Manohar, $e advisor
790 1 0 $a Cheok, Ka D., $e advisor
790 $a 0446
791 $a Ph.D.
792 $a 2009
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3381688