期刊
APPLIED SCIENCES-BASEL
卷 9, 期 7, 页码 -出版社
MDPI
DOI: 10.3390/app9071372
关键词
mining vehicle; articulated vehicle; path tracking; nonlinear model predictive control; nonlinear control systems
类别
资金
- National Key Research and Development Program of China [2018YFC0604403, 2016YFC0802905]
- National High Technology Research and Development Program of China (863 program) [2011AA060408]
- Fundamental Research Funds for the Central Universities [FRF-TP-17-010A2]
Featured Application This work is used for unmanned mining vehicles or articulated mobile robots. Abstract Path tracking of mining vehicles plays a significant role in reducing the working time of operators in the underground environment. Because the existing path tracking control of mining vehicles, based on model predictive control, is not very effective when the longitudinal velocity of the vehicle is above 2 m/s, we have devised a new controller based on nonlinear model predictive control. Then, we compare this new controller with the existing model predictive controller. In the results of our simulation, the tracking accuracy of our controller at the longitudinal velocity of 4 m/s is close to that of the existing model predictive controller, at the longitudinal velocity of 2 m/s. When longitudinal velocity is 4 m/s, the existing model predictive controller cannot drive the mining vehicle to track the given path, but our nonlinear model predictive controller can, and the maximum displacement error and heading error are 0.1382 m and 0.0589 rad, respectively. According to these results, we believe that this nonlinear model predictive controller can be used to improve the performance of the path tracking of mining vehicles.
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