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.
