Iterative Learning Control for Gear Shifting Process in Electrical Mechanical Transmission

被引：0
|
作者：
He K. [1 ]
Lin C. [1 ]
Li L. [1 ,2 ]
Wang X. [1 ]
机构：
[1] State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing
[2] Collaborative Innovation Center of Electric Vehicles, Beijing
来源：
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | 2019年 / 55卷 / 04期
关键词：
Electrical mechanical transmission(EMT); Gear shifting process; Iterative learning control(ILC); Unknown input observer;
D O I：
10.3901/JME.2019.04.084
中图分类号：
学科分类号：
摘要：
Gear shifting process in electrical mechanical transmission(EMT) is a complicated nonlinear multi-body dynamic process. Because of the difficulty in system modeling and huge uncertainty of this process, it is difficult to obtain favorable control performance by using traditional control methods. Hence, these problems largely hinder the development of corresponding control methods for this process. In face of these problems, the paper analyzes the characteristics of the entire process and consider that the process is a repetitive execution, then presents an approach of adopting iterative learning control(ILC) method to optimize gear shifting process. To realize this purpose, unknown input observer is used to estimate the gear shifting load force, then design a linear state feedback controller to generate initial control inputs. After that, ILC is adopted to compensate the control error and considering the construction of the desired trajectory. Finally, experimental results have shown that the proposed scheme is feasible and efficient. © 2019 Journal of Mechanical Engineering.
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页码：84 / 90
页数：6
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