Research Of Intelligent Control Strategy On Warp Tension

The main content of the thesis is intelligent control strategy of warp tension. Warp tension control is one of the technology in top-grade loom control system, it is difficult for conventional PID control to fix loom control problem because of its nonlinear and uncertainty, which isn't difficult to intelligent control.The thesis does much analysis on control object, gets the character of warp tension which is the basis of the next research work. Firstly, digital process or warp tension signal was finished, which raised the accuracy of the warp tension data. Then the PID control based on target let-off value was proposed to improve the control effect of warp tension. After gaining PID control experience, the intelligent control was applied to warp tension control, and which appears to have good control effect.The PID control based on target let-off value method introduced the concept of target let-off value, which is used to assist warp tension control. The dynamic performance was greatly improved, and the static performance was also improved, but it wasn't perfect enough.Fuzzy control is able to settle the nonlinear and uncertainty of loom system, expert control and neural network has some advantage to fuzzy control, so the thesis designed fuzzy expert control and fuzzy neural network to solve the control problem of warp tension. They have some advantages, fuzzy expert control is easy to apply, fuzzy neural network control has strong learning ability, and fuzzy neural network control have good performance to fulfill the demands of top-grade loom after learning.The result of the thesis is able to raise the automation level of top-grade loom, which is important to the develop of textile industry of China.