Biomass Boiler Drum Water Level Control System Using Neural Networks

. Biomass energy transforms solar energy into chemical energy and the energy is stored in the organisms internally with the help of the photosynthesis. In the biomass boiler combustion system, the boiler drum water level is an important parameter and it is a sign to measure regardless of whether boiler steaming water system is in balance. For a nonlinear process as water level control in boilers, conventional control theory is not an appropriate choice. In this study, a neural network based predictive controller is designed and implemented through simulation in MATLAB software for biomass boilers drum water level control. Performance of neural network controller is compared with conventional PID (Proportional + Integral + Derivative) controller for boiler drum water level control system and it is observed that the neural network based approach is more efficient than conventional PID controller.

[1]  T.,et al.  Training Feedforward Networks with the Marquardt Algorithm , 2004 .

[2]  George Stephanopoulos,et al.  Chemical Process Control: An Introduction to Theory and Practice , 1983 .

[3]  Mohd Fadzli,et al.  Comparison between ziegler-nichols and cohen-coon method for controller tunings , 2006 .

[4]  Thomas J. Mc Avoy,et al.  Use of Neural Nets For Dynamic Modeling and Control of Chemical Process Systems , 1989, 1989 American Control Conference.

[5]  N. V. Bhat,et al.  Use of neural nets for dynamic modeling and control of chemical process systems , 1990 .

[6]  Bohumil Sulc,et al.  Achieving optimal operating conditions in PI controlled biomass-fired boilers: Undemanding way for improvement of small-scale boiler effectiveness , 2011, 2011 12th International Carpathian Control Conference (ICCC).

[7]  Stephen A. Billings,et al.  Non-linear system identification using neural networks , 1990 .

[8]  Mohammad Bagher Menhaj,et al.  Training feedforward networks with the Marquardt algorithm , 1994, IEEE Trans. Neural Networks.

[9]  Michael Mulholland Applied process control , 2016 .

[10]  Yongchao Pang,et al.  Study on Fuzzy Self-Adaptive PID Control System of Biomass Boiler Drum Water , 2013 .

[11]  K. Ghousiya Begum,et al.  An Intelligent Model Based Level Control of Boiler Drum , 2013 .

[12]  Ka-Yiu San,et al.  Process identification using neural networks , 1992 .

[13]  R. Hedjar ADAPTIVE NEURAL NETWORK MODEL PREDICTIVE CONTROL , 2012 .

[14]  Stanislav Vrana,et al.  Investigation in control of small-scale biomass boilers , 2011, 2011 12th International Carpathian Control Conference (ICCC).

[15]  Teuku Meurah Indra Mahlia,et al.  Dynamic modeling and simulation of a palm wastes boiler , 2003 .