Transfer function models to control a chemical process
Transfer function models are used to express the relationship between the input and the output variables of a continuous chemical process. A time series method is used to derive the control equation. Experiments were conducted at a chemical plant to estimate the time delay and the impulse response function between the input and the output variables. The input variable that perturbs the chemical process is called the disturbance variable and the associated transfer function is called the perturbation equation. Similarly, the input variable that neutralizes the disturbance effect is called the compensation variable and its transfer function is called the compensation equation. Correlation analysis was used to identify the mathematical structure of the disturbance and compensation equations. Monte Carlo simulation technique and the Hook and Jeeves search were used to determine the initial parameter set for a nonlinear optimization routine. The Levenberg-Marquardt algorithm was used to obtain the final estimates of the transfer function. The control equation determines the values of the compensation variable that should be input into the system to neutralize the disturbance effects and maintain the output variable as close as possible to the target value. (C) 1997 Published by Elsevier Science Ltd.
transfer function chemical processes time series models process control