Adaptive Trajectory Control of Autonomous Robots using Decoupled Fuzzy-Neural PID Controllers

Konferenz: ANNA '18 - Advances in Neural Networks and Applications 2018
15.09.2018 - 17.09.2018 in St. St. Konstantin and Elena Resort, Bulgaria

Tagungsband: ANNA '18

Seiten: 6Sprache: EnglischTyp: PDF

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Ahmed, Sevil; Petrov, Michail (Control Systems Department, Technical University of Sofia, Plovdiv, Bulgaria)

Various types of autonomous mobile robots have found their place in many applications related with surveillance, transportation, inspection, and other problems. This paper is focused on the design of an algorithm for decoupling multivariable systems based on adaptive fuzzy-neural control and its application to control of autonomous mobile robots. Adaptive tuned 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. Performed simulation experiments demonstrate the effect of the developed control algorithm on the trajectory tracking performance of a mobile robot.