Automated Vehicle Path Planning and Trajectory Tracking Control Based on Unscented Kalman Filter Vehicle State Observer

2021 ◽  
Author(s):  
Zixuan Chen ◽  
Yupeng Duan ◽  
Yunqing Zhang
Keyword(s):  
Kalman Filter ◽  
Path Planning ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Unscented Kalman Filter ◽  
State Observer ◽  
Trajectory Tracking Control ◽  
Automated Vehicle ◽  
Vehicle Path

scholarly journals Adaptive Sliding Mode Trajectory Tracking Control for WMR Considering Skidding and Slipping via Extended State Observer

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3305 ◽  
Author(s):  
Gang Wang ◽  
Chenghui Zhou ◽  
Yu Yu ◽  
Xiaoping Liu
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
External Disturbance ◽  
State Observer ◽  
Extended State Observer ◽  
Extended State ◽  
Parameter Uncertainties ◽  
Trajectory Tracking Control ◽  
Adaptive Sliding Mode

When the wheeled mobile robot (WMR) is required to perform specific tasks in complex environment, i.e., on the forestry, wet, icy ground or on the sharp corner, wheel skidding and slipping inevitably occur during trajectory tracking. To improve the trajectory tracking performance of WMR under unknown skidding and slipping condition, an adaptive sliding mode controller (ASMC) design approach based on the extended state observer (ESO) is presented. The skidding and slipping is regarded as external disturbance. In this paper, the ESO is introduced to estimate the lumped disturbance containing the unknown skidding and slipping, parameter variation, parameter uncertainties, etc. By designing a sliding surface based on the disturbance estimation, an adaptive sliding mode tracking control strategy is developed to attenuate the lumped disturbance. Simulation results show that higher precision tracking and better disturbance rejection of ESO-ASMC is realized for linear and circular trajectory than the ASMC scheme. Besides, experimental results indicate the ESO-ASMC scheme is feasible and effective. Therefore, ESO-ASMC scheme can enhance the energy efficiency for the differentially driven WMR under unknown skidding and slipping condition.

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