An inexpensive embedded electronic Continuous Stirred Tank Reactor (CSTR) based on neural networks
- Resource Type
- Conference
- Authors
- Saad Saoud, Lyes; Rahmoune, Faycal; Tourtchine, Victor; Baddari, Kamel
- Source
- 2011 International Conference on Multimedia Technology Multimedia Technology (ICMT), 2011 International Conference on. :6233-6237 Jul, 2011
- Subject
- Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Microcontrollers
Chemical reactors
Pulse width modulation
Mathematical model
Inductors
Neural networks
Computers
CSTR
Nonlinear identification
Neural Networks
Embedded Systems
Microcontroller
- Language
The high nonlinearity and the high cost of the Continuous Stirred Tank Reactor (CSTR) system need to realize a low cost embedded system based on an inexpensive microcontroller using the full neural networks. The two parts, training and validation are used to adapt the network parameters in real time as proposed in this paper. The realized card simulates the CSTR model. The well-known backpropagation algorithm is implemented to train a neural network model. Both the training and the validation parts are shown through an alphanumeric liquid crystal display. A comparison was made between the realized embedded system and the computer results.