Abstarct: This thesis presents the design and implementation of fuzzy sliding mode controller in order to keep balance and motion control of two wheeled balancing robot (TWBR). TWBR is configured with a chassis placed in two parallel coaxial wheels. The main target from control of RWBRs, is keep balance and avoid falling. Also, goals such as speed control and position control can be defined for TWBR. This robot has coupled nonlinear dynamics and is an inherent unstable system. This structure is not easily possible to model and control system. Dynamic equations of TWBR is derived by Lagrangian approach. Uncertainties and model mismatch between the nominal mathematical models and real system are inevitable. Therefore, we design a sliding mode controller for main loop control of this robot. And inner loop controller that its purpose is to track the desired path, is a backstepping method. Also, two sliding mode controller is designed for realize the backstepping control laws and balancing of robot. One conventional sliding mode controller for control the angle of the robot on the plane, and a novel sliding mode controller for control tilt angle and linear velocity of robot simultaneously. In order to speed up the sliding surface approaches zero, the fuzzy logic approach are used. Fuzzy system task in this study is determine appropriate parameters so that speeds up the convergence of the sliding surface. Simulation results show that the designed controllers are good performance in TWBRs. Finally, designed controllers are applied in real TWBR.