Title :
Sensorless and Fuzzy Neuro-Network Control of IPMSM Drives for Ship Electric Propulsion
Author :
Guo, Yi ; Zheng, Hua-yao ; Tan, Xin-yuan
Author_Institution :
Shanghai Maritime Univ., Shanghai
Abstract :
For the control of ship electric propulsion interior permanent-magnet synchronous motor (IPMSM), the position-sensorless observer and based neuro-fuzzy PI controller had been designed, the position sensorless of the flux-observer-based control scheme can obtain an accurate knowledge of the motor magnetic behavior, and lead to good robustness against load variations. A fuzzy basis neuro-network is utilized for online tuning of the PI controller to ensure optimum drive performance. The DC generator simulates the propeller characteristic as the load of the propulsion motor, the proposed observer and controller had been investigated, and they have been carried out in the digital signal process (DSP).
Keywords :
DC motor drives; PI control; electric propulsion; electric vehicles; fuzzy control; machine control; neurocontrollers; permanent magnet motors; position control; ships; synchronous motor drives; DC generator; PI controller; digital signal processing; fuzzy neuro-network control; interior permanent-magnet synchronous motor drive; load variation; motor magnetic behavior; position-sensorless observer; ship electric propulsion; DC generators; Fuzzy control; Load management; Marine vehicles; Permanent magnet motors; Propellers; Propulsion; Robust control; Sensorless control; Synchronous motors; DSP; Fuzzy neuro-network; IPMSM; Position-sensorless; Vessel-propeller model;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370233