TY - GEN
T1 - The design of three-motor intelligent synchronous decoupling control system
AU - Xingqiao, Liu
AU - Jianqun, Hu
AU - Shaoqing, Teng
AU - Liang, Zhao
AU - Guohai, Liu
PY - 2009
Y1 - 2009
N2 - Aiming at the characteristics of multi-input and multi-output, nonlinearity, time-variation and strong coupling in the threemotor synchronous control system, and on the basis of mathematic model analysis of three-motor synchronous control system, the neural network control system is designed. It is composed of three intelligent PID controllers based on BP neural network arithmetic which adjusts the parameters of PID controllers on-line and neuron decoupling compensator. The control of speed and tension of system is realized by three intelligent PID controllers based on BP neural network, and the decoupling control of coupled variables is achieved by neuron decoupling compensator. Experiment is combined with PLC, and the results indicate that the control system can get some optimal parameters of the PID controllers according to different running state of system. The method is designed to realize better decoupling control between the speed and tension in the system, and it has better dynamic and static characteristics.
AB - Aiming at the characteristics of multi-input and multi-output, nonlinearity, time-variation and strong coupling in the threemotor synchronous control system, and on the basis of mathematic model analysis of three-motor synchronous control system, the neural network control system is designed. It is composed of three intelligent PID controllers based on BP neural network arithmetic which adjusts the parameters of PID controllers on-line and neuron decoupling compensator. The control of speed and tension of system is realized by three intelligent PID controllers based on BP neural network, and the decoupling control of coupled variables is achieved by neuron decoupling compensator. Experiment is combined with PLC, and the results indicate that the control system can get some optimal parameters of the PID controllers according to different running state of system. The method is designed to realize better decoupling control between the speed and tension in the system, and it has better dynamic and static characteristics.
KW - BP neural network
KW - Decoupling control
KW - Neuron decoupling
KW - Speed
KW - Synchronous control system
KW - Tension
UR - http://www.scopus.com/inward/record.url?scp=67650699802&partnerID=8YFLogxK
U2 - 10.1145/1543834.1543884
DO - 10.1145/1543834.1543884
M3 - Conference contribution
AN - SCOPUS:67650699802
SN - 9781605583266
T3 - 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - Proceedings of the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09
SP - 375
EP - 379
BT - 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - Proceedings of the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09
T2 - 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09
Y2 - 12 June 2009 through 14 June 2009
ER -