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 have an effect on the output controlled variable before compensating action can become effective, the feedforward action must be predictive in nature. Statistical time series models are used to model both the measured disturbance and the unobserved 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 the control scheme is compared with that of a pure feedback control scheme and the actual performances are shown to conform well to the theory. / Thesis / Master of Engineering (ME)