Trajectory Control of Mobile Robots using Type-2 Fuzzy-Neural PID Controller

At the present time, various types of autonomous mobile robots have found their place in many applications related with surveillance, transportation, inspection, and other problems. The trajectory tracking problem stands along with this growth. In real world, uncertainty and fuzziness of information cause additional difficulties. Hence, deterministic models insufficient usually are, one possible way to overcome the problem is to resort to the use of type-2 fuzzy systems. In this paper an adaptive tuned interval type-2 Takagi-Sugeno fuzzy-neural PID controller for compensation of friction and disturbance effects during the trajectory tracking control of a non-holonomic mobile robot is proposed. The parameters of the adaptive controller are updated according the introduced on-line learning algorithm. Preformed simulation experiments demonstrate the effect of the developed control algorithm on the trajectory tracking performance of a mobile robot.