Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
386948 | Expert Systems with Applications | 2009 | 7 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Ching-Hung Lee, Ming-Hui Chiu,