Transition States Handling in Self-Adaptive Steady State Optimizer of Industrial Processes

K. Wojdan, K. Swirski, and M. Warchol (Poland)


Steady State Control, Adaptive Control, Industrial Process Optimization, Combustion Process Optimization


The SILO (Stochastic Immune Layer Optimizer) system performs an on-line optimization of a large scale industrial processes. This immune inspired, steady state optimizer modifies a current process operating point. Previous optimization algorithm was made of three sub-algorithms called the layers. This paper describes a new Transition State layer. Enhanced optimizer, made of four subalgorithms, is capable of handling significant disturbance transitions. Simulations carried out and described within this paper confirm higher efficiency of the new optimization algorithm during essential transition of a process operating point.

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