Recurrent neuro fuzzy control design for tracking of mobile robots via hybrid algorithm

Authors:
Ching-Hung Lee;Ming-Hui Chiu
Affiliations:
Department of Electrical Engineering, Yuan Ze University, No. 135, Yuan-tung Rd., Chungli, Taoyuan 320, Taiwan, ROC;Department of Electrical Engineering, Yuan Ze University, No. 135, Yuan-tung Rd., Chungli, Taoyuan 320, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

This paper proposes a TSK-type recurrent neuro fuzzy system (TRNFS) and hybrid algorithm- GA_BPPSO to develop a direct adaptive control scheme for stable path tracking of mobile robots. The TRNFS is a modified model of the recurrent fuzzy neural network (RFNN) to obtain generalization and fast convergence. The TRNFS is designed using hybridization of genetic algorithm (GA), back-propagation (BP), and particle swarm optimization (PSO), called GA_BPPSO. For the tracking control of mobile robot, two TRNFSs are designed to generate the control inputs by direct adaptive control scheme and hybrid algorithm GA_BPPSO. Through simulation results, we demonstrate the effectiveness of our proposed controller.