This paper presents a design for a control system that will ensure the stability and proper operation of a mobile four-wheeled robot. As a result of the nonlinear dynamics, structural and parametric uncertainty of this robot, various control approaches are used in order to achieve stability, proper performance, and minimize modeling errors and uncertainties. There are two types of control approaches applied to ensure this robot is stable, that its performance is appropriate, and that modeling errors and uncertainties are minimized. In the presence of external disturbances and parametric uncertainty, this algorithm uses the signals provided by the sensor from the trajectory to follow the predetermined trajectory. It was assumed in previous articles that the upper bound of uncertainty was known. In this paper, we assume the upper bound of uncertainty and disturbance in robotic system is unknown, since, in many cases, we cannot know the extent of these uncertainties. In this paper, we generalized the sliding mode control law and proved its effectiveness, so that by including an adaptive part to the control law, we make it into a robust-adaptive sliding mode control, and we could estimate the upper bound uncertainties online based on these adaptive laws. This typology can be expressed as a distinct theorem with stable results. Simulations with MATLAB software demonstrate that the controller ensures optimal performance under external disturbances and parametric uncertainty with fewer fluctuations.