Mohammad cheraghiyan - Department of Automation and Instrumentation, Ahwaz Faculty of Petroleum Engineering, Petroleum University of Technology, Ahvaz, Iran
Mohammad Mohseni Ahad - Department of Automation and Instrumentation, Ahwaz Faculty of Petroleum Engineering, Petroleum University of Technology, Ahvaz, Iran

Today, there are many systems in the industry which their performances can be detected by using input -output of systems. To do this, they use system identification algorithms. n this paper, the differential equation of input and output a plant is investigated. We used three methods to identify the target system; Levenberg Marquardt, Recursive Batch Back Propagation and Memory-saving implementation. Finally, it was observed that the Memory- saving implementation method has the lowest value of MSE and Final Prediction Error and Recursive Batch Back Propagation method has the lowest Error in last iteration.

System Identification, Plant, Neural Network