CHAOS OPTIMIZATION IN FORMALDEHYDE PRODUCTION PROCESS

Chaos optimization method is proposed for solving nonlinear constraint optimization problems, and linear search is applied to speed the rate of convergence and improve the accuracy of solution. To solve the problem of estiblishing process static-state model, soft sensing based on artificial neural network is proposed. This method is applied to formaldehyde production process online optimization. The results show that the method is simple and easy to implement, robust in versatility, and it has high accuracy and reliability, so it is effective for chemical process optimization.