Title :
Improved vector control of induction motor drives using genetic algorithms-based machine and control parameters estimation
Author :
Trentin, A. ; Zanchetta, P. ; Wheeler, P. ; Clare, J.
Author_Institution :
Univ. of Nottingham, Nottingham
Abstract :
This paper presents an improved rotor flux-based vector control for a high power induction machine. An off-line Genetic Algorithms routine is used to estimate the electrical and mechanical parameters of the machine using only speed transient measurements. This routine is used for a range of operating conditions for the control algorithm and design optimisation. The effectiveness of this design method is demonstrated with a wide range of simulations and experimental results at power levels up to 200 kW.
Keywords :
genetic algorithms; induction motor drives; machine vector control; parameter estimation; rotors; genetic algorithms; induction motor drives; machine vector control; parameters estimation; rotor flux; speed transient measurements; Algorithm design and analysis; Electric variables measurement; Genetic algorithms; Induction machines; Induction motor drives; Machine vector control; Mechanical variables measurement; Parameter estimation; Rotors; Velocity measurement; Genetic Algorithms; Induction Motors; Parameters Estimation; Rotor Flux Control;
Conference_Titel :
Power Electronics and Applications, 2007 European Conference on
Conference_Location :
Aalborg
Print_ISBN :
978-92-75815-10-8
Electronic_ISBN :
978-92-75815-10-8
DOI :
10.1109/EPE.2007.4417732
