Title :
Real-time neuro-fuzzy inverse control applied to a DC motor
Author :
Gonzalez-Gomez, J.C. ; Ruz-Hernandez, J.A. ; Garcia-Hernandez, R. ; Sanchez, E.N.
Author_Institution :
Univ. Autonoma del Carmen, Ciudad del Carmen, Mexico
Abstract :
This paper describes the development of an inverse model for a direct current (DC) motor. The model consist of an Adaptive Network Fuzzy Inference System (ANFIS). The identification procedure includes: the experiment to collect data, ANFIS training and model validation in real-time. The obtained model is used to design a neuro-fuzzy inverse control strategy for trajectory tracking. The obtained real-time results are compared when an inverse ARX model is used for inverse control and to demonstrate that neuro-fuzzy strategy has a successful performance.
Keywords :
DC motors; fuzzy control; machine control; neurocontrollers; real-time systems; ANFIS training; DC motor; adaptive network fuzzy inference system; direct current motor; inverse ARX model; inverse model; real-time neuro-fuzzy inverse control; trajectory tracking; Adaptation models; Angular velocity; DC motors; Data models; Mathematical model; Real time systems; Training; ANFIS; DC Motor; Inverse Model; Real-Time Control;
Conference_Titel :
Electrical Engineering Computing Science and Automatic Control (CCE), 2011 8th International Conference on
Conference_Location :
Merida City
Print_ISBN :
978-1-4577-1011-7
DOI :
10.1109/ICEEE.2011.6106631
