DunAn Microstaq, Inc. (DMQ) released a highly anticipated journal article for optimal superheat response within an air-conditioning or refrigeration (HVAC/R) system that in turn results in improved efficiency performance.
The article examines the utilization of expansion valves with Adaptive-Model Predictive Control (AMPC) as opposed to traditional Model Predictive Control (MPC) to achieve optimal superheat response. Some current controllers of electronic expansion valves use a MPC algorithm that requires manual tuning that comes with degradation in desired parameter set up over time. For a strongly nonlinear plant with dramatically time varying characteristics, linear time invariant (LTI) prediction accuracy might degrade significantly to where the performance of traditional Model Predictive Controller (MPC) becomes unacceptable and AMPC is necessary within a controller algorithm for better superheat performance.
In this report, an AMPC mechanism is used to address the degradation where parameters are tuned continuously through recursive estimation and updated approaches, making the MPC insensitive to prediction errors and to achieve the optimal superheat response. The report also includes implementation of an adaptive set point hunting algorithm so that the system achieves stability and improves energy efficiency simultaneously.
Report Highlights:
o An adaptive-model predictive mechanism is demonstrated
o An MPC controller utilizes the adaptive model for controlling EEV valve
o A hunting algorithm for optimal superheat set point select is designed
o High controller stability and fast response time were experimentally demonstrated.
To download, visit the ScienceDirect website.
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