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Neuro-Fuzzy DC Motor Speed Control Using Particle Swarm Optimization

Author(s): Boumediene ALLAOUA | Abdellah LAOUFI | Brahim GASBAOUI | Abdessalam ABDERRAHMANI

Journal: Leonardo Electronic Journal of Practices and Technologies
ISSN 1583-1078

Volume: 8;
Issue: 15;
Start page: 1;
Date: 2009;
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Keywords: DC Motor speed control | Neuro-Fuzzy controller | Swarm collective intelligence | ANFIS controller using PSO

This paper presents an application of Adaptive Neuro-Fuzzy Inference System (ANFIS) control for DC motor speed optimized with swarm collective intelligence. First, the controller is designed according to Fuzzy rules such that the systems are fundamentally robust. Secondly, an adaptive Neuro-Fuzzy controller of the DC motor speed is then designed and simulated; the ANFIS has the advantage of expert knowledge of the Fuzzy inference system and the learning capability of neural networks. Finally, the ANFIS is optimized by Swarm Intelligence. Digital simulation results demonstrate that the deigned ANFIS-Swarm speed controller realize a good dynamic behavior of the DC motor, a perfect speed tracking with no overshoot, give better performance and high robustness than those obtained by the ANFIS alone.