The Control Algorithm Research of Yarn Tension for Winding Machine Based on Grey Prediction Model

2014 ◽  
Vol 519-520 ◽  
pp. 1305-1308
Author(s):  
Can Cai Wang ◽  
Hai Xia Zhao
Keyword(s):  
Control Algorithm ◽  
Magnetic Particle ◽  
Prediction Method ◽  
Control Model ◽  
The Self ◽  
Tension Control ◽  
Grey Prediction ◽  
Yarn Tension ◽  
Winding Machine ◽  
Prediction Control

For building high precision yarn tension control model, grey prediction method was first employed in this paper. The commonly used GM(1,1) model was modified by means of changing the coefficient a and b. Then the next tension value was forecasted from the previous test values by the modified GM(1,1) model. Then the forecasted values and the referred value were import into the self-adaption PID model. And the PID model output the control sign to magnetic particle clutch. The simulation of the control algorithm was completed in MATLAB 7.0. The simulation result showed that the proposed control algorithm had better precision than general PID and general grey prediction control algorithm.

Study on the Prediction Control Model Based on GM(1, 1)

2014 ◽  
Vol 631-632 ◽  
pp. 728-731
Author(s):  
Zhong Cheng Zhang
Keyword(s):  
House Price ◽  
Housing Price ◽  
Development Trend ◽  
Control Model ◽  
Grey Prediction ◽  
Grey System ◽  
Prediction Theory ◽  
Prediction Control ◽  
And Control ◽  
The Development Trend

With the development and application of prediction theory in the fields of engineering and control, the grey prediction model is introduced. Real estate can be regarded as a grey system in the engineering circle, and housing price is an uncertain indicator which is affected by multiple factors such as policy, market, and economy. In this paper, we study the prediction control problem of housing price, and present a prediction control model of housing price based on GM(1, 1). From the house price data of Huanggang city in recent five years, we use this prediction control model to predict the development trend of housing price in the next five years. We try to provide an effective reference for housing price control.

scholarly journals Yarn tension control technique for improving polyester soft winding process

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohamed Ali ◽  
Rana Ahmed ◽  
Motaz Amer
Keyword(s):  
Textile Industry ◽  
Tension Control ◽  
Control Technique ◽  
Conventional System ◽  
Polyester Yarn ◽  
Yarn Tension ◽  
Dyeing Process ◽  
Yarn Quality ◽  
Winding Machine ◽  
Machine Speed

AbstractThe textile industry has a great role in the improvement of any country’s economy. Moreover, the ready-made garments need different coloured high yarn quality, so yarn should be rewinded on plastic cones for dyeing. However, manufacturers are facing the problem of tension variation during soft winding process that mainly affects the yarn quality. Consequently, to overcome the tension variation drawbacks, the attainment of constant optimal tension values is required in order to: (1) Increase the winding speed while maintaining the yarn quality, (2) Improve the dyeing quality, and (3) Reduce the water consumption during the dyeing process. In this paper, a proposed yarn tension control technique is introduced to upgrade the soft winding machine, thus maintain the yarn quality and improve the manufacturing capacity. The proposed technique has been tested on Polyester yarn samples classified as; fine, medium and coarse yarn counts, to cover most yarn sizes used in the industry. Arduino Mega 2560 controller is utilized to implement the proposed tension control. The results are compared to the conventional system to advocate the effectiveness and capability of the proposed technique in overcoming the trade-off between tension control and machine speed that occurs in conventional system using variable tension levels.

Application of Fuzzy PID Control in Yarn Tension Control System

2013 ◽  
Vol 321-324 ◽  
pp. 1748-1752
Author(s):  
Hai Xia Zhao ◽  
De Gong Chang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Tension Control ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Yarn Tension ◽  
On Line ◽  
Winding Machine ◽  
Tension Control System

When winding yarn, the yarn tension control of a winding machine affects the quality of yarn subsequent processing. For randomicity and instability of the yarn tension in a winding machine, the paper designed a yarn tension control system based on analyzing conventional PID controller, using the fuzzy PID control algorithm to control the yarn tension system and realizing on-line self-adjustment of PID control parameters. The simulation experiment showed that system tension had better response using fuzzy PID control and eliminated nonlinearity and uncertainty of the system.

Size Prediction Control Modeling in Cylindrical Grinding

2010 ◽  
Vol 154-155 ◽  
pp. 977-980
Author(s):  
Ning Ding ◽  
Shi Qiang Ma ◽  
Yu Mei Song ◽  
Long Shan Wang
Keyword(s):  
Fuzzy Control ◽  
Model Simulation ◽  
Size Control ◽  
Control Model ◽  
Elman Neural Network ◽  
Cylindrical Grinding ◽  
Control Subsystem ◽  
Control Precision ◽  
Prediction And Control ◽  
Prediction Control

A dynamic size control model during cylindrical grinding is built. The model consists of Elman neural network, fuzzy control subsystem and deformation optimal adaptive control subsystem. To improve the size prediction accuracy, the first and the second derivative of the actual amount removed from the workpiece are added into the Elman network input; To self-adapt and adjust the quantification factor and scale factor in the fuzzy control, the flexible factor is introduced to the fuzzy control model. Simulation and experiment verify that the developed prediction control model is feasible and has high prediction and control precision.

Trigonometric Grey Prediction Method for Turkey's Electricity Consumption Prediction

2021 ◽  
pp. 136-154
Author(s):  
Adem Tuzemen
Keyword(s):  
Evaluation Criteria ◽  
Electricity Consumption ◽  
Prediction Method ◽  
Electricity Demand ◽  
Grey Prediction ◽  
Data Set ◽  
Determining Factors ◽  
The Future ◽  
Forecasting Analysis ◽  
Short Term Forecasting

Industry and technology continue to develop rapidly in today's world. The indisputable most important source of this development, energy is among the indispensables of daily life. Since it is one of the determining factors for the country's economy, the future forecast of electricity demand means calculating the future steps. Based on this, to forecast Turkey's electricity demand, it was benefited from grey model (GM) and trigonometric GM (TGM) techniques. The data set includes annual electricity consumption for the period 1970-2018. The performances of the methods determined were compared based on the forecast evaluation criteria (MSE, MAD, MAPE, and RMSE). Short-term forecasting analysis was carried out by determining the method that gives these values to a minimum. In the future forecast, it has been determined that electricity consumption will increase continuously.

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