A fuzzy logic based approach to real time optimization of dynamic processes

Most chemical processes are operated under continuously changing conditions and thus the optimal operating conditions change with time. On-line optimization techniques of various types which are used to track these kinds of moving optimum, have sparked significant interest in recent years. A multi-variable, adaptive, fuzzy logic based approach is presented here for real-time optimization of nonlinear dynamic chemical processes. The approach is model-free and utilizes only the online plant measurements and a set of properly formulated fuzzy rules to keep the process always at optimum conditions despite changes in environmental conditions. Both simulation and experimental studies point to the efficiency of the approach. The algorithm yields reasonably fast convergence and a robust performance against noisy and inaccurate signals.