Predictive stochastic feedforward-feedback control of a heat exchanger-stirred tank system

An optimal stochastic feedforward-feedback control scheme is implemented on a heat exchanger-stirred tank system using an on-line minicomputer. Because variations in the measured disturbance variable affect the process output (controlled variable) before the compensating action can become effective, the feedforward action must be predictive in nature. Statistical time series models are used to model both the measured and unmeasured disturbances in the system. These stochastic disturbance models and the transfer-function models for the process are identified, fitted and checked using statistical model-building procedures on a set of data collected on-line using the minicomputer. The predictive feedforward-feedback controller is derived from these models. The performance of this control scheme is compared with that of an optimal feedback scheme and the actual on-line performance is shown to conform well to the theoretical predictions