Abstract
The proposed real-time multimodel for the injection molding process mainly contributes to the barrel temperature control. Good control of the plastic melt temperature is very important for injection molding in reducing the operator setup time, ensuring product quality, and preventing thermal degradation of the melt. The controllability and set points of the barrel temperature also depend on the precise monitoring and control of the plastic melt temperature. Motivated by the practical temperature control of injection molding, this article proposes a multimodel-based proportional integral derivative (PID) control scheme in real-time and the simulation studies of the PID, fuzzy, and adaptive neuro fuzzy inference system (ANFIS) control schemes. The injection molding process consists of three zones, and the mathematical model for each zone is different. The control output for each zone controller is assigned a weight, based on the computed probability of each model, and the resulting action is the weighted average of the control moves of the individual zone controller.
Published Version
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