Adaptive Backstepping Control with Extended State Observer for Wheeled Mobile Robot

In this paper, the adaptive backstepping controller is designed based on kinematics and dynamics model of the wheeled mobile robot (WMR). Based on backstepping control theory, an adaptive law is designed to reduce the influence of the control system because of the internal disturbance caused by uncertain or unknown parameters of system and the external disturbance caused by environmental factors. Lyapunov stability theory is applied to prove the stability of the adaptive controller. In order to further reduce the influence of disturbance on the control performance, the extended state observer (ESO) is introduced to observe the disturbances of linear speed and angular speed which compensate the control output value of adaptive controller. Simulation results show that the proposed control method can adapt disturbance of the system and has a good performance on trajectory tracking.

[1]  Jing Zhang,et al.  Nonlinear Adaptive Backstepping with ESO for the Quadrotor Trajectory Tracking Control in the Multiple Disturbances , 2019, International Journal of Control, Automation and Systems.

[2]  S. S. Vishnu Prasad,et al.  Development of backstepping sliding mode tracking control for Wheeled Mobile Robot , 2014, 2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies.

[3]  Xiao SHEN,et al.  Adaptive Trajectory Tracking Control of Wheeled Mobile Robot , 2019, 2019 Chinese Control And Decision Conference (CCDC).

[4]  C.J. Tomlin,et al.  Autonomous Automobile Trajectory Tracking for Off-Road Driving: Controller Design, Experimental Validation and Racing , 2007, 2007 American Control Conference.

[5]  Zhang Jian,et al.  The sliding mode control based on extended state observer for skid steering of 4-wheel-drive electric vehicle , 2012, 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet).

[6]  Guohai Liu,et al.  Adaptive Sliding Mode Fault-Tolerant Coordination Control for Four-Wheel Independently Driven Electric Vehicles , 2018, IEEE Transactions on Industrial Electronics.

[7]  Oscar Barrero,et al.  Outdoors Trajectory Tracking Control for a Four Wheel Skid-Steering Vehicle* , 2018, 2018 IEEE 2nd Colombian Conference on Robotics and Automation (CCRA).

[8]  Ying Wang,et al.  Learning from adaptive neural network output feedback control of a unicycle-type mobile robot. , 2016, ISA transactions.

[9]  Tae Kyeong Yeu,et al.  Adaptive Backstepping Control Design for Trajectory Tracking of Automatic Guided Vehicles , 2016 .

[10]  Shirong Liu,et al.  Backstepping based trajectory tracking control for a four-wheel mobile robot with differential-drive steering , 2017, 2017 36th Chinese Control Conference (CCC).

[11]  Oishee Mazumder,et al.  Close loop control of non-holonomic WMR with augmented reality and potential field , 2014, 2014 Recent Advances in Engineering and Computational Sciences (RAECS).

[12]  Mohamed Boukattaya,et al.  Adaptive control of nonholonomic wheeled mobile robot with unknown parameters , 2015, 2015 7th International Conference on Modelling, Identification and Control (ICMIC).