Title :
The Control Algorithm Research of the Warp Tension Based on Neural Network
Author :
Li, Lei ; Yang, Jiancheng ; Zhao, Yongli ; Liu, Yan ; Cong, Liangchao
Author_Institution :
Sch. of Mech. & Electron. Eng., Tianjin Polytech. Univ., Tianjin, China
Abstract :
This paper put forward to use neural network control algorithm to control warp tension, and introduced the single neuron control method and multi-neuron control method respectively. And first proposes a modeling method that fits non-linear system with multiple single neuron models, introduction of multi-model reference trajectory to acquire a new multi-model prediction control. Then use the SIMULINK of MATLAB to simulate. The transition time of system which based on multi-neuron PID control is about 0.5s, and there is no overshoot exists, system stability, and multi-neuron PID controller has a better control effect.
Keywords :
neurocontrollers; nonlinear systems; position control; three-term control; MATLAB simulation; PID control; SIMULINK simulation; control algorithm research; multimodel prediction control; multineuron control method; neural network control algorithm; neuron control; nonlinear system method; single neuron models; warp tension; Control systems; MATLAB; Mathematical model; Neural networks; Neurons; Nonlinear control systems; Predictive models; Stability; Three-term control; Trajectory; algorithm; multi-neuron; neural network; single neuron; warp tension;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.364