Stability improvement of induction motor based on stator parameter identification scheme

2008 ◽  
Author(s):  
Shanlin Kang ◽  
Yuzhe Kang ◽  
Jingwei Chen
Keyword(s):  
Parameter Identification ◽  
Induction Motor ◽  
Identification Scheme

Parameter identification of induction motor drives

Automatica ◽  
1995 ◽  
Vol 31 (8) ◽  
pp. 1137-1147 ◽  
Author(s):  
Christiaan Moons ◽  
Bart De Moor
Keyword(s):  
Parameter Identification ◽  
Induction Motor ◽  
Motor Drives ◽  
Induction Motor Drives

VSS theory-based parameter identification scheme for MIMO systems

Automatica ◽  
1996 ◽  
Vol 32 (2) ◽  
pp. 279-284 ◽  
Author(s):  
Jian-Xin Xu ◽  
Hideki Hashimoto
Keyword(s):  
Parameter Identification ◽  
Mimo Systems ◽  
Identification Scheme

Detection of Stator and Rotor Faults in Asynchronous Motor Using Artificial Intelligence Method

2018 ◽  
pp. 278-285
Author(s):  
K. Vinoth Kumar ◽  
Prawin Angel Michael
Keyword(s):  
Induction Motor ◽  
Asynchronous Motor ◽  
Feed Forward Neural Network ◽  
Identification Scheme ◽  
Hardware System ◽  
Rotor Faults ◽  
Squirrel Cage ◽  
Three Phase ◽  
Neural Network Structure ◽  
Trained Network

This chapter deals with the implementation of a PC-based monitoring and fault identification scheme for a three-phase induction motor using artificial neural networks (ANNs). To accomplish the task, a hardware system is designed and built to acquire three phase voltages and currents from a 3.3KW squirrel-cage, three-phase induction motor. A software program is written to read the voltages and currents, which are first used to train a feed-forward neural network structure. The trained network is placed in a Lab VIEW-based program formula node that monitors the voltages and currents online and displays the fault conditions and turns the motor. The complete system is successfully tested in real time by creating different faults on the motor.

scholarly journals Inertia Parameter Identification for an Unknown Satellite in Precapture Scenario

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Xiao-Feng Liu ◽  
Xiao-Yu Zhang ◽  
Pei-Ran Chen ◽  
Guo-Ping Cai
Keyword(s):  
Parameter Identification ◽  
Momentum Conservation ◽  
Space Robot ◽  
Control Force ◽  
Soft Contact ◽  
Identification Scheme ◽  
Inertia Parameter ◽  
Inertia Parameters ◽  
Dynamics And Control ◽  
And Control

The problem of dynamics and control using a space robot to capture a noncooperative satellite is an important issue for on-orbit services. Inertia parameters of the satellite should be identified before capturing such that the robot can design an active controller to finish the capturing task. In this paper, a new identification scheme is proposed for parameter identification of a noncooperative satellite. In this scheme, the space robot is controlled to contact softly and then maintain contact with the noncooperative target firstly, then the variation of momentum of the target during the contact-maintaining phase is calculated using the control force and torque acting on the base of the space robot and the kinematic information of the space robot, and finally, the momentum-conservation-based identification method is used to estimate inertia parameters of the target. To realize soft contact and then maintain contact, a damping contact controller is designed in this paper, in which a mass-damping system is designed to control the contact between the robot and the target. Soft contact and then contact maintenance can be realized by utilizing the buffering characteristics of the mass-damping system. The effectiveness of the proposed identification scheme is verified through numerical simulations at the end of this paper. Simulation results indicate that the proposed scheme can achieve high-precision identification results.

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