Abstract:
An improved version of the immune inspired optimizer
SILO is presented in this paper. The new model identification method
allows for utilization of model gains constraints. Moreover the
operation of a new Transition State algorithm is analyzed based on a
real-life example. The improved version of SILO was implemented
in a real power boiler. Results from a real combustion process
optimization are presented in this paper.
