Khalil Muhammad Zuhaib

Dr. Khalil Muhammad Zuhaib

orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 February 2016 in International Journal of Control, Automation, and Systems
Verified
Journal Article
Closed access
PDF file
AKAbdul Manan Khan
Abdul Manan Khan
DYDeok-Won Yun
Deok-Won Yun
MAMian Ashfaq Ali
Mian Ashfaq Ali
KZKhalil Muhammad Zuhaib
Khalil Muhammad Zuhaib
CYChao Yuan
Chao Yuan
CHChang-soo Han
Chang-soo Han

8 March 2017 in International Journal of Control, Automation, and Systems
Verified
Journal Article
Closed access
PDF file
AKAbdul Manan Khan
Abdul Manan Khan
DYDeok-Won Yun
Deok-Won Yun
KZKhalil Muhammad Zuhaib
Khalil Muhammad Zuhaib
JIJunaid Iqbal
Junaid Iqbal
RYRui-Jun Yan
Rui-Jun Yan
CHChang-soo Han
Chang-soo Han

19 July 2017 in Applied Sciences
Verified
Journal Article
Open access
PDF file
JIJunaid Iqbal
Junaid Iqbal
KZKhalil Muhammad Zuhaib
Khalil Muhammad Zuhaib
CHChang-soo Han
Chang-soo Han
AKAbdul Manan Khan
Abdul Manan Khan
MAMian Ashfaq Ali
Mian Ashfaq Ali
A steer-by-wire (SbW) system, also known as a next-generation steering system, is one of the core elements of autonomous driving technology. Navigating a SbW system road vehicle in varying driving conditions requires an adaptive and robust control scheme to effectively compensate for the uncertain parameter variations and external disturbances. Therefore, this article proposed an adaptive global fast sliding mode control (AGFSMC) for SbW system vehicles with unknown steering parameters. First, the cooperative adaptive sliding mode observer (ASMO) and Kalman filter (KF) are established to simultaneously estimate the vehicle states and cornering stiffness coefficients. Second, based on the best set of estimated dynamics, the AGFSMC is designed to stabilize the impact of nonlinear tire-road disturbance forces and at the same time to estimate the uncertain SbW system parameters. Due to the robust nature of the proposed scheme, it can not only handle the tire–road variation, but also intelligently adapts to the different driving conditions and ensures that the tracking error and the sliding surface converge asymptotically to zero in a finite time. Finally, simulation results and comparative study with other control techniques validate the excellent performance of the proposed scheme.

5 March 2016 in International Journal of Precision Engineering and Manufacturing
Verified
Journal Article
Closed access
PDF file
DYDeokwon Yun
Deokwon Yun
AKAbdul Manan Khan
Abdul Manan Khan
RYRui-Jun Yan
Rui-Jun Yan
YJYounghoon Ji
Younghoon Ji
HJHyeyoun Jang
Hyeyoun Jang
CHChang-soo Han
Chang-soo Han

27 July 2019 in International Journal of Control, Automation, and Systems
Verified
Journal Article
Closed access
PDF file
SYSheraz Yaqub
Sheraz Yaqub
AAAhmad Ali
Ahmad Ali
MUMuhammad Usman
Muhammad Usman
KZKhalil Muhammad Zuhaib
Khalil Muhammad Zuhaib
AKAbdul Manan Khan
Abdul Manan Khan
CHChang-soo Han
Chang-soo Han

8 March 2017 in International Journal of Control, Automation, and Systems
Verified
Journal Article
Closed access
PDF file
MAMian Ashfaq Ali
Mian Ashfaq Ali
CKChangjun Kim
Changjun Kim
SKSangho Kim
Sangho Kim
AKAbdul Manan Khan
Abdul Manan Khan
JIJunaid Iqbal
Junaid Iqbal
CHChang-soo Han
Chang-soo Han