| This thesis evaluates the performance of three multirate inferential estimation schemes which infer intersample values of the controlled output from a more rapidly sampled secondary plant output. Three estimator equations based on using first and second order plant models are employed. Each of these estimators is combined with a fixed parameter PI controller to form an adaptive inferential control (AIC) scheme. The control performance of each AIC scheme was compared with the control behavior of a conventional PI feedback control strategy.; The AIC schemes have been evaluated, by simulation, for bottoms composition control of a binary distillation column and of a five component depropanizer. Use of a dead-band on AIC strategies was found to stablize the control behavior during the initial adaptation period so its use is strongly recommended for practical applications.; The performance of the AIC algorithms were also examined experimentally for control of the bottoms composition of a pilot scale binary distillation column.; In general, the simulation and experimental results show the potential for successful application of the SM-1 control algorithm to industrial processes. (Abstract shortened by UMI.)... |
