Study of Intelligent Prediction and Control of Workpiece Size in Traverse Grinding

2006 ◽  
Vol 304-305 ◽  
pp. 191-195
Author(s):  
Ning Ding ◽  
Long Shan Wang ◽  
Guang Fu Li ◽  
J.Z. Wang ◽  
Xiao Wei Chen
Keyword(s):  
Fuzzy Control ◽  
Prediction Model ◽  
Control Model ◽  
Control Precision ◽  
The Neural Network ◽  
Neural Network Prediction ◽  
Prediction And Control ◽  
Prediction Control ◽  
And Control ◽  
Traverse Grinding

A size intelligent prediction control model during traverse grinding is constructed. The model is composed of the neural network prediction model, the deformation optimal adaptive control system and fuzzy control model. Dynamic Elman network is used in the prediction model. The first and the second derivative of the actual amount removed from the workpiece are added into the network input, which can greatly improve the prediction accuracy. The flexible factor is introduced to the fuzzy control model, which can self-adapt and adjust the quantification factor and scale factor in the fuzzy control. Simulation and experiment verify that the developed prediction control model is feasible and has high prediction and control precision.

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.

Dynamic Intelligent Prediction Control in Slender Cylindrical Grinding

2007 ◽  
Vol 359-360 ◽  
pp. 189-193
Author(s):  
Ning Ding ◽  
Xiao Mei Li ◽  
Yuan Ding ◽  
Guo Fa Li ◽  
Long Shan Wang
Keyword(s):  
Surface Roughness ◽  
Control System ◽  
Dynamic Prediction ◽  
Cylindrical Grinding ◽  
Vibration Data ◽  
Fuzzy Neural ◽  
Neural Network Prediction ◽  
Prediction And Control ◽  
Prediction Control ◽  
And Control

A dynamic intelligent prediction control system is built in slender cylindrical grinding. Elman network is used in the dynamic size prediction control model, and the first and the second derivative of the actual amount removed from the workpiece are added into the network input, which can greatly improve the size dynamic prediction accuracy. Moreover, a surface roughness equation with vibration data is proposed. Based the equation, the surface roughness dynamic fuzzy neural network prediction subsystem is built. Experiment verifies that the developed prediction control system is feasible and has high prediction and control accuracy.

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 Furnace heat prediction and control model and its application to large blast furnace

2019 ◽  
Vol 38 (2019) ◽  
pp. 884-891
Author(s):  
Zhuang-nian Li ◽  
Man-sheng Chu ◽  
Zheng-gen Liu ◽  
Gen-ji Ruan ◽  
Bao-feng Li
Keyword(s):  
Blast Furnace ◽  
Control Model ◽  
Heat Index ◽  
Model Parameters ◽  
Stable Operation ◽  
Oxygen Balance ◽  
Large Blast ◽  
Large Blast Furnace ◽  
Prediction And Control ◽  
And Control

AbstractBlast furnace heat is the key to the blast furnace’s high efficiency and stable operation, and it is difficult to maintain a suitable temperature for large blast furnace operations. When designing the furnace heat prediction and control model, parameters with good reliability and measurability should be chosen to avoid using less accurate parameters and to ensure the accuracy and practicability of the model. This paper presents an effective model for large blast furnace temperature prediction and control. Using thermal equilibrium and the carbon-oxygen balance of the blast furnace’s high-temperature zone, the slag-iron heat index was calculated. Using the relation between the molten iron temperature and slag-iron heat index, the furnace heat parameter can be calculated while production conditions are changed,which can guide furnace heat control.

Prediction and control model of shale induced fracture leakage pressure

2021 ◽  
Vol 198 ◽  
pp. 108186
Author(s):  
Xiaopeng Zhai ◽  
Hui Chen ◽  
Yishan Lou ◽  
Huimei Wu
Keyword(s):  
Control Model ◽  
Prediction And Control ◽  
And Control

Neural network prediction and control of three-dimensional unsteady separated flowfields

1995 ◽  
Vol 32 (6) ◽  
pp. 1213-1220 ◽  
Author(s):  
William E. Faller ◽  
Scott J. Schreck ◽  
Marvin W. Luttges
Keyword(s):  
Neural Network ◽  
Three Dimensional ◽  
Neural Network Prediction ◽  
Prediction And Control ◽  
Network Prediction ◽  
And Control
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