Low Relaxation Prestressed Steel Wire Stabilization Of The Production Line System Control

Low-relaxation prestressed steel wire is one kind of high degree of strength steels, and it is well used in construction industry. This paper based on the product technics, analysis the electric control system in detail. This thesis focuses on the control of the temper temperature, which is the core technics parameter. This paper contains following parts:The first section: Based on the product technics ,designed the hardware structure and the software. The anti-jamming technique also be discussed.The second section: The process of induce heating is a complex process. After analysis the heating mechanism, this thesis build up an approximate model for the system.The third section: Used the feedforward--cascade control strategy to control the temper temperature, and acquires a good result.The fourth section: Introduced design of the normal fuzzy controller, and produced some improved schemes. After this, this thesis proposed a fuzzy-Pi controller what uses a self-regulating scaling method. The simulation result illustrates that the fuzzy-Pi control is better than the normal PI controller.The five section: The CMAC neural network will approach any complicated nonlinear relationship sufficiently. The network could study some unknown systems. The inverse model learning control strategy of CMAC neural network owned good quality in robustness, adaptability and short rights training time. It is adapt to the industry process which parameter is uncertain or unknown.