Vehicle Speed Fuzzy Logic Controller System Using Surface EMG Signal

The interaction between the human body motion and the robotic motion has gained much interest nowadays. Enhancing the accuracy of such a system requires the use of more complex systems in order to maintain the safety of the user, especially in critical systems such as disabled assistant systems. In this work, an investigation of motion control using Surface electromyography (sEMG) signals, which are obtained from the user’s arm, is studied. This system can help disabled drivers who can use their arms and cannot use their feet for speed or braking pedals. The sEMG signal can be obtained by fixing a gesture with multi sEMG sensors on the user’s arm between the elbow and the wrist. The controller receives the sEMG signal and the proper signal is sent to the motors responsible for accelerating or decelerating the vehicle through speed or braking pedal, respectively. The sEMG signal is usually time-varying noisy signal; hence, a proper filter is needed to attenuate the unwanted noisy signal. In addition, an intelligent controller is developed to control vehicles speeding and braking safely. In this paper a Fuzzy logic controller is chosen due to the high nonlinearity of such a system. The system can be improved to cover different activities and actions based on the user’s needs.