کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10326406 | 678070 | 2016 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Robust Hâ output-feedback yaw control for in-wheel motor driven electric vehicles with differential steering
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Robust Hâ output-feedback yaw control for in-wheel motor driven electric vehicles with differential steering Robust Hâ output-feedback yaw control for in-wheel motor driven electric vehicles with differential steering](/preview/png/10326406.png)
چکیده انگلیسی
This paper investigates the yaw control issue for in-wheel-motor (IWM) electric ground vehicles (EGVs) based on the differential steering in the presence of the complete failure of the active front-wheel steering. Differential steering is an emerging steering mechanism, generated from the differential torque between the left and right wheels in IWM EGVs. In case that the regular steering system is defective, differential steering can be utilized to act as the sole steering power, and thus avoid dangerous consequences for vehicles. For this purpose, a robust Hâ output-feedback controller based on differential steering is designed to achieve yaw stabilization, considering that the desired steering angle is uncertain and hard to obtain. Parameter uncertainties for the cornering stiffnesses and the external disturbances are considered to make vehicle robust to different driving conditions. CarSim-Simulink joint simulation results based on a high-fidelity and full-car model verify the effectiveness of the proposed controller to guarantee the equal vehicle handling and stability.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 173, Part 3, 15 January 2016, Pages 676-684
Journal: Neurocomputing - Volume 173, Part 3, 15 January 2016, Pages 676-684
نویسندگان
Rongrong Wang, Hui Jing, Chuan Hu, Mohammed Chadli, Fengjun Yan,