Title :
A neuro-fuzzy multilayer weights approach for an on-line learning speed controller applied to a switched reluctance machine: why and how to use it
Author :
Rafael, Silviano ; Pires, A.J. ; Branco, P. J Costa
Author_Institution :
LabSEI, Instituto Politecnico de Setubal, Lisbon
Abstract :
The most used neuro-fuzzy motor speed control systems are time consuming and have an high computation effort when the speed reference changes suddenly and the system, most of the time, has to learn this new operating point. In this case a degradation of the system performance is evident, as is demonstrated by our experimental results in this paper. To surpass these effects, a new neuro-fuzzy multilayer control´s approach is proposed. The multilayer controller is tested and compared in the speed control system for an 8/6 switched reluctance motor by experimental tests. The proposed solution is explained, tested and the experimental results are presented and discussed
Keywords :
angular velocity control; control engineering computing; electric machine analysis computing; fuzzy neural nets; machine control; neurocontrollers; reluctance motors; multilayer controller; neurofuzzy motor speed control systems; neurofuzzy multilayer weights approach; online learning speed controller; switched reluctance machine; Control systems; Electric variables control; Input variables; Machine learning; Nonhomogeneous media; Reluctance machines; Reluctance motors; System testing; Variable speed drives; Velocity control; Adjustable speed drive; Control methods for electrical systems; Neural control; Switched reluctance drive; Variable speed drive;
Conference_Titel :
Power Electronics and Applications, 2005 European Conference on
Conference_Location :
Dresden
Print_ISBN :
90-75815-09-3
DOI :
10.1109/EPE.2005.219488
