This article propounds addressing the design of a sliding mode controller with adaptive gains for trajectory tracking of unicycle mobile robots. The dynamics of this class of robots are strong, nonlinear, and subject to external disturbance. To compensate the effect of the unknown upper bounded external disturbances, a robust sliding mode controller based on an integral adaptive law is proposed. The salient feature of the developed controller resides in taking into account that the system is MIMO and the upper bound of disturbances is not priori known. Therefore, we relied on an estimation of each perturbation separately for each subsystem. Hence, the proposed controller provides a minimum acceptable errors and bounded adaptive laws with minimum of chattering problem. To complete the goal of the trajectory tracking, we apply a kinematic controller that takes into account the nonholonomic constraint of the robot. The stability and convergence properties of the proposed tracking dynamic and kinematic controllers are analytically proved using Lyapunov stability theory. Simulation results based on a comparative study show that the proposed controllers ensure better performances in terms of good robustness against disturbances, accuracy, minimum tracking errors, boundness of the adaptive gains, and minimum chattering effects.

本文提出了一种具有自适应增益的滑模控制器的设计，该控制器可用于单轮移动机器人的轨迹跟踪。此类机器人的动力学很强，非线性且容易受到外部干扰。为了补偿未知上限外部干扰的影响，提出了一种基于积分自适应律的鲁棒滑模控制器。所开发的控制器的显着特征在于考虑到系统是MIMO且干扰的上限未知。因此，我们依赖于每个子系统的每个扰动的估计。因此，所提出的控制器提供了最小的可接受误差和具有最小颤动问题的有界自适应律。为了完成轨迹跟踪的目标，我们应用了一种运动学控制器，该控制器考虑了机器人的非完整约束。利用李雅普诺夫稳定性理论分析证明了所提出的跟踪动态和运动学控制器的稳定性和收敛性。基于一项比较研究的仿真结果表明，所提出的控制器在抗干扰，鲁棒性，精度，最小跟踪误差，自适应增益的界限和最小颤动效果方面具有良好的性能。