An evolutionary approach to derive adaptive optimal control policy

In the case of chemical reaction process

Abstract

To obtain a near optimal control policy for real world chemical processes, in this paper, we focused our attention on a new meta-heuristic method termed differential evolution (DE). Compared with conventional approaches characterized by variational logic as well as by the inconveniences of simultaneous optimization methods for differential-algebraic equation, we have shown DE's ability to derive a near optimal solution adaptive to various requirements in practice. Since the algorithm is straightforward and flexible to manage various conditions, we can cope with high dimensionality and outstanding non-linearity peculiar to chemical process in real world applications. Taking reaction processes, we applied the proposed method under various meaningful conditions, and validated its adaptability in comparison with other methods.