Multistage dynamic optimization of a copolymerization reactor using differential evolution

Targeting on Different Characteristic Continuous Variables in Process Transition for Ethylene Column with Wide-Range Feed Fluctuation

For the study of the transition strategies of continuous chemical processes, both continuity and dynamic characteristics in the physical sense are critical. The continuous transition strategy has a higher information density and can describe the real situation as closely as possible. In addition, the accuracy of the dynamic characteristics is necessary because the process transition is the study of the dynamic system processes. However, existing transition strategies have certain shortcomings. Dynamic optimization can obtain transition strategies with different characteristics but no physical meaning and a frequency domain-based analytical approach can acquire a continuous transition strategy with physical meaning, but its dynamic characteristics are the same. Therefore, by integrating the advantages of the existing strategies, a new transition strategy has been presented, which possesses different dynamic characteristics and continuity synchronous with physical significance. When process transition occurs, the proposed strategy results in less fluctuation and can quickly reach and maintain a steady state. Furthermore, the strategy is also suitable for the rapid application of different transition processes in the same plant. The performance of the transition strategies is evaluated through research on a continuous feed ethylene column.

Dynamic optimization of a copolymerization reactor using tabu search

A novel multistage dynamic optimization strategy based on meta-heuristic tabu search (TS) is proposed and evaluated through sequential and simultaneous implementation procedures by applying it to a semi-batch styrene-acrylonitrile (SAN) copolymerization reactor. The adaptive memory and responsive exploration features of TS are exploited to design the dynamic optimization strategy and compute the optimal control policies for temperature and monomer addition rate so as to achieve the desired product quality parameters expressed in terms of single and multiple objectives. The dynamic optimization results of TS sequential and TS simultaneous implementation strategies are analyzed and compared with those of a conventional optimization technique based on iterative dynamic programming (IDP). The simulation results demonstrate the usefulness of TS for optimal control of transient dynamic systems.