Trajectory Tracking for Mobile Robots Based on Fractional-Order Sliding Mode and Dynamic Modeling

Nan Ning^1,2*

• ¹Zibo Polytechnic University, Zibo, China
• ²Hunan Communication Polytechnic, Changsha, China

With the development of science, technology, and economy, robots are now applied in many industries. To address the problem that robot trajectory tracking is easily affected by environmental disturbances, this paper raises a trajectory tracking control model based on Fractional-Order Sliding Mode Control and dynamic modeling to improve robot control performance. The model uses a Fractional-Order Sliding Mode Control to design a trajectory tracking controller, and then applies Particle Swarm Optimization algorithm and Radial Basis Function Neural Network to optimize the controller. After that, it analyzes the main operating components and coupling relationships of the robot based on kinematic modeling and dynamic modeling to improve the accuracy of trajectory tracking control. In simulation experiments, the improved controller keeps the position error within the range of [-1×10-5, 1×10-5], which is smaller than that of the compared algorithms and shows higher accuracy. The proposed trajectory tracking control model has a rise time of 0.06 s, which is shorter than that of the compared models and shows faster convergence speed. These results show that the proposed model performs well in accuracy, stability, and rise speed.