Title :
Research of Speed Observer Based on Neural Network Optimized by Fast Modified ACO in DTCs
Author :
Cao, Chengzhi ; Jia, Lichao ; San, Hongli ; You, Ying
Author_Institution :
Sch. of Inf. Sci. & Eng., Shenyang Univ. of Technol., Shenyang
Abstract :
To enhance its global optimization speed, the basic ant colony optimization (ACO) is modified, then it is used to optimize the neural networks (NN), and the optimized NN is applied to the direct torque control (DTC) system, so that the rotate speed can be observed. The DTC with speed sensorless is implemented at last. The research of simulation shows that, the modified ACO has eminent global optimization performance and fast convergence rate, the rotate speed of the system is able to be observed by the DTC system with the NN optimized by this method exactly, thereby, the DTC with speed sensorless can be implement.
Keywords :
neurocontrollers; observers; optimisation; torque control; ant colony optimization; direct torque control; fast modified ACO; global optimization; neural network; speed observer; Ant colony optimization; Control theory; Convergence; Information science; Information technology; Intelligent networks; Neural networks; Optimization methods; Robustness; Torque control; DTC; Neural Network; ant colony optimization; speed observer;
Conference_Titel :
Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3497-8
DOI :
10.1109/IITA.2008.33
