Abstract
This paper develops a multivariable self-tuning predictive control for improving set-point tracking performance, disturbance rejection, and robustness of a temperature control system for an extruder barrel in a plastic injection molding process. The stochastic discrete-time multivariable mathematical model is built and its unknown system parameters are identified by using the recursive least-squares estimation method. The multivariable predictive control is derived based on the minimization of a generalized predictive performance criterion. A real-time self-tuning control algorithm is proposed and then implemented by using a digital signal processor (DSP) TMS320C31 from Texas Instruments. Experimental results are used to show the feasibility and effectiveness of the proposed method.
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