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Content Provider | IEEE Xplore Digital Library |
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Author | Hamidi, Y.E. Javash, M.S. Ettefagh, M.M. Doust, F.A. |
Copyright Year | 2012 |
Description | Author affiliation: Department of Mechanical Engineering, Tabriz University, Tabriz, Iran (Hamidi, Y.E.; Javash, M.S.; Ettefagh, M.M.; Doust, F.A.) |
Abstract | In this paper, synthesis of the steering mechanism is optimized using Artificial Immune System (AIS) Algorithm for best function generation. A four-bar mechanism is employed as the Ackermann steering mechanism. For the first time the optimization in this problem is implemented with two methods. In the first method the length are selected as optimization parameter whereas in the second method precision points distribution is considered as optimization parameter. For the first method two of links have the same length in order to have a symmetric mechanism. For the precision point distribution method, five precision points are considered which one of them is in the straight line condition and the others are symmetric. Artificial Immune System (AIS) Algorithm has been used as an appropriate optimization strategy. The obtained result shows that in second method, precision points distribution as optimization parameter, the AIS algorithm can generate more accurate function. But first method, length as optimization parameter, is more practical because of its ability to satisfy all dimensional constraints. |
Starting Page | 913 |
Ending Page | 917 |
File Size | 1342282 |
Page Count | 5 |
File Format | |
ISBN | 9781467322478 |
e-ISBN | 9788993215045 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-10-17 |
Publisher Place | Korea (South) |
Access Restriction | Subscribed |
Rights Holder | ICROS |
Subject Keyword | Couplings Algorithm design and analysis mechanism synthesis Linear programming Signal generators Artificial Immune System optimization function generation Ackermann steering Optimization Equations Immune system Four-bar mechanism |
Content Type | Text |
Resource Type | Article |
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