Adaptive model predictive control using neural networks

摘要

The authors work in controlling chemical processes included the following: (1) to develop neural networks and training procedures that are well suited to: small amounts of off-line training data for on-line control of systems with substantial time lags; (2) to develop generic Model Predictive Control (MPC) software; and (3) to control the following simulated systems using MPC: continuously stirred tank reactor with jacket dynamics; plasma etching model for semiconductor manufacture; and distillation columns. Details descriptions are given of the three points.