Unbiased GM(1,1) model for grey prediction control

2007 ◽  
Author(s):  
Ji Peirong ◽  
Zheng Wencheng ◽  
Luo Xianju
Keyword(s):  
Grey Prediction ◽  
Prediction Control

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 Development and Experimental Analysis of a Fuzzy Grey Control System on Rapeseed Cleaning Loss

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1764
Author(s):  
Xiaoyu Chai ◽  
Lizhang Xu ◽  
Yang Li ◽  
Jie Qiu ◽  
Yaoming Li ◽  
...  
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Field Tests ◽  
Grey Prediction ◽  
Control Scheme ◽  
Cleaning Device ◽  
Important Means ◽  
Prediction Control ◽  
Microcontroller Unit ◽  
Control Principle

One of the most important means of improving the mechanization of rapeseed harvests and increasing farmers’ income is to reduce the cleaning loss of rapeseed. In this study, a fuzzy grey control system was developed using an assembled cleaning loss sensor. Based on experimental data, the relationship between the cleaning loss and the opening of the louver sieve in the cleaning device was obtained. The fuzzy control scheme was established by combining grey prediction and the fuzzy control principle. Secondly, a microcontroller unit (MCU) was used as the controller, and the opening of the louver sieve was automatically regulated by detecting the signal of the cleaning loss. Finally, the performance and robustness of the control system was evaluated in field tests. Different experiments were conducted under different speed conditions to reflect the variable throughput. Results showed that using the grey prediction control system can realize the adjustment of the louver sieve opening in real time. The cleaning loss could be maintained within the ideal setpoint interval, compared with the operation with the control system switched off. These findings indicate that the application of the grey fuzzy control system reduces cleaning loss, and the nonlinear, time-variable and time delay problems in cleaning devices can be solved effectively.

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