Accurate semi-empirical predictive modeling of an underdamped process

Rollins et al. (D.K. Rollins, J.M. Liang, P. Smith. Accurate simplistic pre dictive modeling of nonlinear dynamic processes, ISA Transactions 4 (1998) 293-303.) introduced a predictive modeling approach that uses a semi-empiri cal model in an algorithm that changes the model form when input changes oc cur. This approach was found to be very accurate under a variety of samplin g conditions when processes follow first order dynamics. The purpose of thi s article is to demonstrate the ability of this approach to accurately pred ict output response for systems with complex dynamics. More specifically, t his approach is evaluated on a mathematically simulated CSTR that approxima tely follows underdamped second order behavior for changes in coolant flow rate and inverse second order behavior for changes in feed rate. This work demonstrates creativity in obtaining accurate fitted models with coefficien ts that vary widely over the input space using a few number of experimental runs to obtain the model coefficients. The proposed method is evaluated un der conditions of high input (coolant flow rate) change frequency, variable change rate of the input, and no sampling of the output. (C) 1999 Elsevier Science Ltd. All rights reserved.