A Self Balancing Personal Transporter (SBPT) is a robotic platform with two wheels that functions from the balance of the individual who uses it, resembling the operation of classic inverted pendulum. In this thesis, a SBPT is designed, built and controlled. Among the features from the developed SBPT, it can be mentioned: relatively high speeds, agility, compact aluminum structure, zero turn radius, and high load capacity, when compared to other SBPT in the market. Unlike traditional motor vehicles, the SBPT uses electric power, so there is no polluent emissions to the environment and no noise pollution. It is powered by two motors with output powers between 0.7HP and 1.6HP. To measure the tilt angle and its rate of change, a three-axis accelerometer and a gyroscope are used. The turning commands to the SBPT are sent through a potentiometer attached to the handle bars. The method of Kane is used to obtain the system dynamic equations, which are then used in Matlab simulations. The controller, programmed in eLua, reads the signals from the accelerometer, gyroscope and potentiometer slider, process them, and then sends PWM output signals to the speed controller of the drive motors. This thesis studies three control implementations: PID, Fuzzy and Robust Control. The control variables are the error and error variation of the tilt angle. It is found that the Fuzzy and Robust controls are more efficient than the PID to stabilize the system on inclined planes and on rough terrain.