Automation of search for optimal values of the ethylene oligomerization process parameters - Antipina, E.V.; Mustafina, S.A.; Antipin, A.F. (Nauchno-tekhnicheskiĭ vestnik informat͡s︡ionnykh tekhnologiĭ, mekhaniki i optiki, 2024)
A mathematical description of the process of ethylene oligomerization on a NiO/B2O3-Al2O3 catalyst in a liquid heptane solvent is given. Problems of optimal process control are formulated. The temperature and time of the process are taken as control parameters. An algorithm is proposed for solving the problem of optimal control of the industrially significant catalytic process of ethylene oligomerization. The search for solutions to the formulated problems is carried out using a genetic algorithm with real coding. For each of the problems under consideration, a method is proposed for representing a mathematical analogue of a population on the basis of which a solution is searched. A step-by-step algorithm for determining the optimal parameters for the ethylene oligomerization process is presented. A special feature of the algorithm is the simultaneous search for the values of a continuous control parameter (temperature) and a discrete control parameter (process time). A program (application) has been developed to determine the optimal values of process parameters. The application allows the user to select an optimal control problem, set the values of the genetic algorithm parameters to find a solution, and visualize the results obtained. A computational experiment was carried out for the process of ethylene oligomerization. The optimal duration of the process under isothermal conditions was calculated, at which the highest concentration of C4 hydrocarbons is achieved. The optimal temperature conditions and duration of the ethylene oligomerization process were determined to ensure the maximum concentration of C6 hydrocarbons. The conducted numerical experiments demonstrated lower resource consumption compared to the methods of uniform search and variations in the control space. The proposed algorithm can be used to study the patterns of catalytic processes without resorting to laboratory experiments associated with additional material and time costs.