Unmanned Hybrid Electric Vehicles FNN Control based on Self-organized Learning Algorithm and Supervised Learning Algorithm

摘要：

To resolve unmanned hybrid electric vehicles control problems, the fuzzy neural network control method based on self-organized learning algorithm and supervised learning algorithm is proposed in this paper. This algorithm can learn proper fuzzy logic rules and optimal memberships functions from training examples. Using this control method,,we can control an unmanned hybrid electric vehicle by learning the driving technique of a skilled drive. By combining both unsu per vised self-organized and supervised learning algorithm,the learning speed converges much faster than the original backpropagation learning algorithm. Simulation results are presented to illustrate the performance and applicability of the proposed learning algorithm.

关键词： unmanned hybrid electric vehicle fuzzy neural network(FNN) self-organized learning algorithm supervised learning algorithm

作者: Yun Zhang Xiumin Yu Xuemei Chen Mingshuang Bi

作者单位: College of Automobile Engineering Jilin University Changchun,China Water Resources Department of the JiLin Province Changchun,China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

会议地点: 长春

会议语种:英文

页码: 555-558

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）