ALSTOM has thrown a challenge problem related to the control of MIMO gasifier which is a nonlinear system. Quite a few researchers have tried different methods for control tuning and found that critical process transients such as pressure and temperature of syngas during specified load changes are not within the desired limits. This is mainly attributed to a very high order of the gasifier system. Due to this, efforts have been made to represent gasifier higher order models as a simplified lower order models. This paper focuses on identifying a reduced order transfer function models for gasifier with minimum IAE and ISE error criterion using Genetic Algorithm. The lower order transfer functions obtained using Genetic Algorithm is found to be superior to those obtained using RGA loop pairing and Algebraic method proposed respectively by Haryanto and Sivakumar et.al.
[1]
J. A. Rossiter,et al.
An advanced predictive control approach to the ALSTOM gasifier problem
,
2000
.
[2]
Roger Dixon,et al.
Dynamic modelling and simulation of the air blown gasification cycle prototype integrated plant
,
1998
.
[3]
X. Anitha Mary,et al.
A Low Order Transfer Function Model for MIMO ALSTOM Gasifier
,
2011,
2011 International Conference on Process Automation, Control and Computing.
[4]
S. N. Sivanandam,et al.
A Comparative Study Using Genetic Algorithm and Particle Swarm Optimization for Lower Order System Modelling
,
2009
.