In this paper, trajectory tracking of a differential drive nonholonomic mobile robot is presented. In addition to the complex relations of the control system, the nonholonomic system adds complexity to the system which has been solved using the feed-forward and feedback fuzzy logic controllers. | Journal of Automation and Control Engineering Vol. 3, No. 3, June 2015 Feedforward and Feedback Kinematics Controller for Wheeled Mobile Robot Trajectory Tracking Muhammad Asif and Muhammad Junaid Khan National University of Sciences and Technology, Islamabad, Pakistan Email: {, juniad}@ Muhammad Safwan and Muhammad Rehan Sir Syed University of Engineering and Technology, Karachi, Pakistan Email: , murehan@ Abstract—In this paper, trajectory tracking of a differential drive nonholonomic mobile robot is presented. In addition to the complex relations of the control system, the nonholonomic system adds complexity to the system which has been solved using the feed-forward and feedback fuzzy logic controllers. An innovative scheme has been developed to track the reference trajectory in the presence of model uncertainties and disturbances. The performance comparison of the proposed controller is done with the standard backstepping controller and the simulation results show that the developed controller is best suited for the tracking trajectory problems. input-output feedback linearization [7], [8] and backstepping [1], and so on. However, the presented works have poor transient and steady state characteristics in the presence of disturbance and model uncertainties. In addition, most of the works use simple trajectories with constant linear and angular velocities. In this research work, an innovative kinematic controller is proposed for trajectory following to generate the kinematic velocities. The controller structure uses feed-forward and feedback controllers. The feed-forward controller is designed based on reference positions and velocities along with error propagation model, whereas the feedback controller is designed using fuzzy logic. The effectiveness of the deigned controller is validated by computer simulations. In addition, the performance and effectiveness of the proposed scheme is compared with .
