System identification and control of pressure process rig® system using backpropagation neural networks

A neural networks based direct inverse controller for Pressure Process Rig® system is presented, including with the performance analysis using an open-loop and a closed loop system. In order to enhance the performance characteristics of this direct inverse controller, a Fine-Tuning method is proposed. Experimental results show that the open-loop system shows lower MSE compare with that of the closed-loop system, and the Fine-Tuned NN-DIC method always performed better with lower MSE compare with that of the normal NN-DIC method.

[1]  Jan G. Pieters,et al.  Modelling greenhouse temperature using system identification by means of neural networks , 2004, Neurocomputing.

[2]  Brendan Peter McGrath,et al.  Current Regulation Strategies for Vector-Controlled Induction Motor Drives , 2012, IEEE Transactions on Industrial Electronics.

[3]  Hwi-Beom Shin,et al.  Anti-Windup PID Controller With Integral State Predictor for Variable-Speed Motor Drives , 2012, IEEE Transactions on Industrial Electronics.

[4]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[5]  Haitham Abu-Rub,et al.  Speed Sensorless Induction Motor Drive With Predictive Current Controller , 2013, IEEE Transactions on Industrial Electronics.

[6]  Feri Yusivar,et al.  Identification and Control Design of Fuzzy Takagi-Sugeno Model for Pressure Process Rig , 2012 .

[7]  K. Valarmathi,et al.  Intelligent techniques for system identification and controller tuning in pH process , 2009 .

[8]  Vesna Ranković,et al.  Identification of nonlinear models with feed forward neural network and digital recurrent network , 2008 .

[9]  Ralph Kennel,et al.  High-Performance Control Strategies for Electrical Drives: An Experimental Assessment , 2012, IEEE Transactions on Industrial Electronics.

[10]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[11]  Tien-Li Chang,et al.  Application of NARX neural networks in thermal dynamics identification of a pulsating heat pipe , 2009 .