Operation Condition Optimization of p-Xylene Oxidation Reaction Process Based on a Fuzzy Adaptive Immune Algorithm

Abstract

The oxidation of p-xylene to terephthalic acid (TA) is a significant chemical process of purified TA production. Variation of operation conditions of the reaction directly affects the quality of TA. In this paper a fuzzy adaptive immune algorithm (FAIA) was proposed to realize the operation condition optimization of the p-xylene oxidation reaction. In FAIA, a chaotic hypermutation was developed to strengthen the searching ability of the algorithm, and a new immune network regulatory strategy was devised to maintain population adversity. Furthermore, two fuzzy logic modules were constructed to adjust parameters, further increasing the adaptability of the algorithm. The data of function optimization show that FAIA can quickly converge to the global optimum and overcome premature problems. Optimization results of process variable values of the p-xylene oxidation reaction indicate that the application of FAIA in an oxidation reaction process can greatly save the time of operation condition selection and reduce production cost.

p-Xylene Oxidation to Terephthalic Acid: A Literature Review Oriented toward Process Optimization and Development

“…Mu et al , using a set of 10 process variables developed a genetic algorithm which optimizes operation profit either by manipulating product quality, i.e., 4-CBA and process throughput, or by operating the process variables sequence in the proper operating order. Hong et al present a Fuzzy Adaptive Immune Algorithm. Gujarathi and Babu present a multiobjective optimization algorithm based on effect of six decision variables identified, namely, catalyst concentration, vent oxygen content, % water in solvent, feed xylene rate, temperature of reactor, and total feed rate, also to achieve the same effect of allowing the industrial operator to make the desirable improvement in the process design decisions.…”