Title :
A novel grammatical inference learning algorithm for automatic modelling of drive systems
Author :
Martins, F. ; Pires, A.J. ; Mendes, R. Vilela ; Dente, J.A.
Author_Institution :
Inst. Politecnico de Setubal, Escola Superior de Tecnologia de Setubal, Portugal
Abstract :
A new formal language concept for the automatic modelling of drive systems is presented. The proliferation of electrical drives promises improved efficiency and reliability, reduced maintenance and operative costs, and environment friendly operation. However, they considerable complexities related with their behaviour such as large uncertainties at the structural and parameter levels, multidimensionality and strong mutual interactions. The integration of these systems with information processing techniques allows for a better modelling of their behaviour. The drive system is assumed as a linguistic source producing a certain language. A grammatical inference algorithm is developed to extract the productions of the language grammar. The formalism of the developed formal language-based modelling algorithm is presented and experimental results are discussed
Keywords :
DC-AC power convertors; PWM invertors; electric machine analysis computing; formal languages; induction motor drives; machine theory; squirrel cage motors; PWM inverters; automatic modelling; efficiency; electric drive modelling; environment friendly operation; formal language concept; formalism; grammatical inference learning algorithm; maintenance; multidimensionality; mutual interactions; reliability; squirrel cage motor drives; uncertainties; Costs; Data mining; Formal languages; Inference algorithms; Information processing; Multidimensional systems; Production; Pulse width modulation inverters; Stators; Uncertainty;
Conference_Titel :
Industry Applications Conference, 2000. Conference Record of the 2000 IEEE
Conference_Location :
Rome
Print_ISBN :
0-7803-6401-5
DOI :
10.1109/IAS.2000.882091
