DocumentCode
2277313
Title
A new two-degree-of-freedom internal model decoupling control of three-motor drive system
Author
Liu, Guohai ; Yu, Kun ; Zhang, Yi ; Zhang, Jin ; Zhao, Wenxiang
Author_Institution
Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang, China
fYear
2011
fDate
20-23 Aug. 2011
Firstpage
1
Lastpage
4
Abstract
Multi-motor drive is a multi-input multi-output (MIMO), nonlinear and strong-coupling system. Its high precision coordinated control performance can meet the requirements of many drive applications, such as urban rail transit, paper making, electric vehicle drive, and steel rolling. To decouple the velocity and the tension of the three-motor drive system, a new control strategy is proposed by incorporating two-degree-of-freedom internal model control (IMC) with back-propagation (BP) neural network generalized inverse (NNGI). Firstly, the composite pseudo-linear system is formed by making NNGI connect in series with the original system. Secondly, a two-degree-of-freedom IMC method is introduced to this pseudo-linear system. Finally, the simulation results are given, verifying that the proposed strategy can not only effectively attain decoupling towards velocity and tension, but also transform this MIMO nonlinear system into a number of SISO linear subsystems with open-loop stability, so as to improve the dynamic characteristic of the system.
Keywords
MIMO systems; backpropagation; linear systems; machine control; motor drives; neural nets; neurocontrollers; nonlinear control systems; open loop systems; stability; MIMO nonlinear system; NNGI; SISO linear subsystem; backpropagation neural network; coordinated control performance; degree-of-freedom IMC method; electric vehicle drive; multiinput multioutput system; multimotor drive; nonlinear system; open loop stability; paper making; pseudolinear system; steel rolling; strong-coupling system; three motor drive system; two degree-of-freedom internal model control; two degree-of-freedom internal model decoupling control strategy; urban rail transit; Artificial neural networks; Control systems; DC motors; Induction motors; Mathematical model; Rotors; Synchronous motors;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical Machines and Systems (ICEMS), 2011 International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4577-1044-5
Type
conf
DOI
10.1109/ICEMS.2011.6073639
Filename
6073639
Link To Document