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This paper investigates the tracking control of an electrically driven nonholonomic mobile robot with model uncertainties in the robot kinematics, the robot dynamics, and the wheel actuator dynamics. A robust adaptive controller is proposed with the utilization of adaptive control, backstepping and fuzzy logic techniques. The proposed control scheme employs the adaptive control approach to design an auxiliary wheel velocity controller to make the tracking error as small as possible in consideration of uncertainties in the kinematics of the robot, and makes use of the fuzzy logic systems to learn the behaviors of the unknown dynamics of the robot and the wheel actuators. The approximation errors and external disturbances can be efficiently counteracted by employing smooth robust compensators. A major advantage of the proposed method is that previous knowledge of the robot kinematics and the dynamics of the robot and wheel actuators is no longer necessary. This is because the controller learns both the robot kinematics and the robot and wheel actuator dynamics online. Most importantly, all signals in the closed-loop system can be guaranteed to be uniformly ultimately bounded. For the dynamic uncertainties of robot and actuator, the assumption of ldquolinearity in the unknown parametersrdquo and tedious analysis of determining the ldquoregression matricesrdquo in the standard adaptive robust controllers are no longer necessary. The performance of the proposed approach is demonstrated through a simulation example.