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Control of plastic melt temperature: A multiple input multiple output model predictive approach
Author(s) -
Dubay Rickey,
Bell Adam C.,
Gupta Yash P.
Publication year - 1997
Publication title -
polymer engineering and science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.503
H-Index - 111
eISSN - 1548-2634
pISSN - 0032-3888
DOI - 10.1002/pen.11803
Subject(s) - materials science , model predictive control , temperature control , controllability , control theory (sociology) , thermal , injection molding machine , overshoot (microwave communication) , mimo , molding (decorative) , computer science , composite material , mechanical engineering , control (management) , mold , engineering , mathematics , thermodynamics , artificial intelligence , telecommunications , channel (broadcasting) , computer network , physics
Good control of plastic melt temperature for injection molding is very important in reducing operator setup time, ensuring product quality, and preventing thermal degradation of the melt. The controllability and setpoints of other process parameters also depend on the precise monitoring and control of plastic melt temperatures. We experimentally investigated the thermal interactions between the barrel zones of an instrumented plastic injection molding machine (IMM). These interactions result from the zone temperature differences that are used in normal machine operations. From these experimental interactions, multiple‐input‐multiple‐output (MIMO) and single‐input‐single‐output (SISO) models were derived for controlling these zone temperatures using a Model Predictive Control (MPC) strategy. An experimental comparison was made between MIMO MPC and SISO MPC of plastic melt temperature, which showed that the MIMO MPC scheme is more energy efficient, having zero overshoot.