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A new proportional-integral-derivative (PID) controller is proposed based upon a simplified generalized predictive control (GPC) control law. The tuning parameters of the proposed predictive PID controller are obtained from the simplified GPC control law for the 1 st -order and 2 nd -order processes with time delays of integer and non-integer multiples of the sampling time. The internal model technique is employed to compensate the effect of time delay of the target process. The predictive PID controller is equivalent to the PI controller when the target process is 1 st -order and to the PID controller when the target process is an integrating process. The performance of the proposed predictive PID controller is almost the same as that of the simplified GPC. The main advantage of the proposed control scheme over other control methods is the ease of tuning and operation. INTRORUCTIONNumerous advanced control techniques are developed and utilized in various control areas. But proportional-integral-derivative (PID) controllers are still the choice of most industrial companies because of the many advantages such as simplicity of implementation, robustness, wide applicability and familiarity of plant engineers [1]. It is obvious that the parameters of PID controllers should be tuned according to the process dynamics in order to maintain acceptable control performance. But most PID controllers implemented in many industries are tuned by experienced engineers using the trial-and-error method. This tuning method requires considerable time and cost. In particular, for the control of a process with time delay or showing nonminimum phase behavior, the PID controller should be retuned adaptively to maintain the stability of the control system. Therefore a tuning method is required which determines on-line optimal PID parameters based on the input and output operation data. Clarke et al. [2,3] presented the generalized predictive control (GPC) scheme which predicts the process outputs over the time range greater than the maximum time delay of the process. The GPC method, also known as a self-tuning controller, has the capability of controlling nonminimum phase or unstable processes by employing analytical solution procedures. But the large amount of cost and time as well as the non-familiarity of the process engineers to the complicated control method limit the application of the GPC scheme.To overcome these difficulties and maintain typical advantageous characteristics of PID and GPC methods, many design methods for PID controllers by using the GPC strategy have been proposed so far. Miller et al. [4,5] presented a predictive PID controller based on the GPC with steady state weighting. Kwok et al. [6] suggested the use of the augmented PID control scheme with multiple PID blocks to apply the GPC method. Moradi et al.[7] defined a PIDtype control structure which predicts the process outputs and recalculates new future set points. This type of the predictive PID controller maintains the basic structure of the PID scheme famil...

We investigate the model for an industrial isothermal HDPE slurry reactor. The model, consisting of several nonlinear equations, can be linearized to give sets of linear time invariant state space model. The effectiveness of the linearized model is verified by the numerical simulations. A simple model predictive control scheme is constructed based on the linear state space model. The value of the melt index is obtained from the values of the manipulated and controlled variables generated from the control scheme. The control performance can be evaluated from the comparison between the computed melt index values and measured melt index values. The control scheme shows good tracking performance in the numerical simulations. We believe that the model developed in the present study can be effectively used to predict process variables as well as to control the melt index.