A Modular Real-time Tidal Prediction Model based on Grey-GMDH Neural Network

2018 ◽  
Vol 32 (2) ◽  
pp. 165-185 ◽  
Author(s):  
Ze-Guo Zhang ◽  
Jian-Chuan Yin ◽  
Cheng Liu
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Real Time ◽  
Model Based

Neural Network Based Control of Preform Permeation in Resin Transfer Molding Processes With Real-Time Permeability Estimation

2000 ◽  
Author(s):  
David Nielsen ◽  
Ranga Pitchumani
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Resin Transfer Molding ◽  
Local Pressure ◽  
Transfer Molding ◽  
Model Based ◽  
Rtm Process ◽  
Virtual Sensing ◽  
Intelligent Model ◽  
Injection Pressures

Abstract Variabilities in the preform structure in situ in the mold are an acknowledged challenge to effective permeation control in the Resin Transfer Molding (RTM) process. An intelligent model-based controller is developed which utilizes real-time virtual sensing of the permeability to derive optimal decisions on controlling the injection pressures at the mold inlet ports so as to track a desired flowfront progression during resin permeation. This model-based optimal controller employs a neural network-based predictor that models the flowfront progression, and a simulated annealing-based optimizer that optimizes the injection pressures used during actual control. Preform permeability is virtually sensed in real-time, based on the flowfront velocities and local pressure gradient estimations along the flowfront. Results are presented which illustrate the ability of the controller in accurately steering the flowfront for various fill scenarios and preform geometries.

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