In this paper, we propose an adaptive sliding mode-based fault tolerant control for mobile robots. While a mobile robot is tracking a given trajectory, several fault cases may occur, such as sensor model and controller faults, changes in the dynamic equation due to robot body shape or weight changes, and loss of actuator effectiveness. Disturbance signals are caused by the actuator faults and, for various reasons, can be considered the primary issue for the robots. In real-time applications, the Sliding Mode Controller (SMC) is insufficient if the robot parameters are unknown, the robot model is non-linear, and the overall system is subject to disturbances. An adaptive law is used to support the SMC to maintain the sliding surface and solve the problems of unknown system parameters, actuator faults, and disturbances. Besides SMC, the kinematic controller is also used, and its gain values are optimized using a neural network and a kinematic controller. The stability of the overall system is proven by using the Lyapunov theory. Besides actuator faults, the system is disturbed by defining a disturbance signal, which is added to the control signals. To show the effectiveness of the proposed controller, it is compared with traditional SMC and PID.