Research Article
Trajectory Tracking of a Two-Wheeled Mobile Robot Using Backstepping and Nonlinear PID Controller
@INPROCEEDINGS{10.1007/978-3-031-28725-1_18, author={Lencho Duguma Fufa and Endalew Ayenew}, title={Trajectory Tracking of a Two-Wheeled Mobile Robot Using Backstepping and Nonlinear PID Controller}, proceedings={Artificial Intelligence and Digitalization for Sustainable Development. 10th EAI International Conference, ICAST 2022, Bahir Dar, Ethiopia, November 4-6, 2022, Proceedings}, proceedings_a={ICAST}, year={2023}, month={3}, keywords={Backstepping and NPID Controller Trajectory Tracking Two-Wheeled Mobile Robot Genetic Algorithm Lyapunov Stability Analysis}, doi={10.1007/978-3-031-28725-1_18} }- Lencho Duguma Fufa
Endalew Ayenew
Year: 2023
Trajectory Tracking of a Two-Wheeled Mobile Robot Using Backstepping and Nonlinear PID Controller
ICAST
Springer
DOI: 10.1007/978-3-031-28725-1_18
Abstract
Many researchers have become interested in wheeled mobile robot (WMR) trajectory tracking control in recent years. This is due to the increased application of mobile robots in the industry, the military, the home, and public service. Classically, the movement of WMR is controlled depending on its kinematic model. However, in real-time applications, both the dynamic and kinematic models of robots and external disturbance and uncertainty affect system performance. This paper proposes backstepping combined with a Nonlinear Proportional-Integral-Derivative (NPID) controller to control a two-wheeled mobile robot (TWMR). The kinematic and dynamic models of the WMR are derived. The dynamic modeling is derived using a Lagrangian approach, and stability of the system is achieved using the Lyapunov method. The controller gains are optimized using the Genetic Algorithm optimization technique. The proposed algorithms’ performance is tested using Matlab software. The simulation result shows that the proposed method achieved preferable reference trajectory tracking with a minimum tracking error. The proposed controller outperforms the GA-based backstepping plus PID controller in terms of root-mean-square (RMS) of trajectory tracking error (47.36% in a linear and 60.32% in a nonlinear case). In addition, it shows good unknown disturbance rejection and initial point change in all scenarios.
