Guiding mechanism design and precision pressure control in composites filament winding system

Author(s):  
Pengbing Zhao ◽  
Jinzhu Zhou ◽  
Jin Huang

During the composite winding process, pressure fluctuation will affect the density and homogeneity of the products and will make the interfacial strength disaccord with the fiber volume fraction. In order to improve the guiding precision and stability of the winding pressure, the bearing guide is replaced by the rolling guide in designing the pressure guiding mechanism, and parametric model of the guiding mechanism is established based on dynamics experiment of the joint surfaces. By analyzing the modal and harmonic response, the corresponding measures for improvement are proposed. Experimental results show that the designed guiding mechanism based on the rolling guide has high precision and perfect stability. Additionally, roundness error and installation error of the mandrel can cause the winding pressure to fluctuate and the gas compressibility, nonlinear flow, dead zone, cylinder friction, measurement noise and other nonlinear disturbances have significant impact on the pneumatic pressure control system. Considering the above circumstance, an adaptive fuzzy proportional–integral–derivative (PID) controller based on the grey prediction is proposed. By predicting the output pressure, trend of the pressure signal can be reflected accurately, which provides a reliable basis for the decision-making of the fuzzy PID controller. Simultaneously, two separate fuzzy inference systems are employed to adjust the step length of the predictive control and the scale factor of the step self-tuning algorithm. Simulation and experimental results show that the fuzzy PID controller based on grey prediction has shorter settling time, smaller overshoot and error, stronger robustness and interference immunity. The designed guiding mechanism and control algorithm have effectively improved the precision and stability of the pressure control system for the composite materials winding formation.

2014 ◽  
Vol 945-949 ◽  
pp. 2568-2572
Author(s):  
Si Yuan Wang ◽  
Guang Sheng Ren ◽  
Pan Nie

The test rig for hydro-pneumatic converter used in straddle type monorail vehicles was researched, and its electro-pneumatic proportional control system was set up and simulated based on AMESim/Simulink. Compared fuzzy-PID (Proportion Integral Derivative) controller with PID controller through fuzzy logic tool box in Simulink, the results indicate that, this electro-pneumatic proportional control system can meet design requirements better, and fuzzy-PID controller has higher accuracy and stability than PID controller.


2013 ◽  
Vol 706-708 ◽  
pp. 1063-1067
Author(s):  
Hai Feng Lin ◽  
Liu Qing Du ◽  
Li Ping Xiong

The Liquid Surface Pressure Control is the key factor for the guarantee of Low Pressure Die Casting Quality. Regarding to the disadvantages of conventional PID Control such as pressure fluctuation, poor repeatability of the pressure curve, and so on, we propose Liquid Surface Pressure Control System (LSPCS) based on Fuzzy Adaptive PID. Design method of Fuzzy PID Controller has been discussed, and the realization methods of the hardware and software in this system are developed. This proposed system has a good performance in practice.


2013 ◽  
Vol 631-632 ◽  
pp. 1106-1110
Author(s):  
Wei Zhao ◽  
Qiang Wang ◽  
Sheng Li Song

In the tyred machinery chassis dynamometer control system, a fuzzy PID controller was used to adjust the exciting current of a DC dynamometer in order to change the resistance load torque, so the requirement of roller load for simulating the run resistance from the road surface was satisfied. A fuzzy PID arithmetic was designed to control the resistance loads, the system performance was improved by simulation. The software of the detection line measure-control system was designed in VB, the technical parameters of the machinery chassis could the automatically detected.


2013 ◽  
Vol 432 ◽  
pp. 472-477
Author(s):  
Wei Fan ◽  
Tao Chen

This paper presents a robust fuzzy proportional-integral-derivative (PID) controller for brushless DC motor (BLDCM) control system. The hardware circuit of the BLDCM control system is designed and implemented using a digital signal processor (DSP) TMS320LF2407A and a monolithic BLDCM controller MC33035 as the core. Furthermore, a fuzzy PID controller, which combines the advantages of good robustness of fuzzy controller and high precision of conventional PID controller, is employed in the hardware system, thereby yielding a digital, intelligent BLDCM control system. Experimental results have shown that the control system can run steadily and control accurately, and have convincingly demonstrated the usefulness of the proposed fuzzy PID controller in BLDCM control system.


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