ABSTRACT

The complexity of establishing intelligent telecommunication networks equipped with artificial intelligence technologies is an aspect to be considered when implementing automated control systems. Providing a quality signal and keeping strength levels for the transmission of commands to mobile robots is crucial for preventing malfunction during the operation of the mobile robot, especially when sending command signals over lengthy distances and in environments that create a lot of radio frequency noise. An ITN provides stability on output signal control tasks and compensates for any strength loses due to noise. Therefore, using fuzzy logic to measure signal loss and distortion, an adaptive neuro-fuzzy inference system (ANFIS) is implemented to compensate the incoming signal strength to minimize data or information loss. The proposed inference system can be used to control the telecommunication system. It can, for example, be used to adjust the signal gain level to improve signal quality while transmitting commands to mobile robots.