Investigation of the Process Parameters Influence on the Energy Efficiency of an Induction Motor under Model Predictive Control GRAMPC
Date Issued
2017
Author(s)
Diachenko, G. G.
Aziukovskyi, O. O.
Abstract
This paper presents the implementation of the nonlinear gradient based model predictive control (MPC)
software GRAMPC (GRAdient based MPC) for the energy efficient control of three-phase induction motor drives. GRAMPC is appropriate for controlling nonlinear systems with input constraints in the (sub)millisecond range and is based on real-time solution strategy. The effect of the model algorithmic parameters: prediction horizon, the maximum number of iterations and number of data points is considered and default values in terms of real-time demands are determined. Additionally, some comparison results with conventional methods are provided, which demonstrate the advantages and performance of GRAMPC. The analysis for appropriate choice of the algorithmic parameters is based on
simulation results for three different induction motors with different rated powers.
software GRAMPC (GRAdient based MPC) for the energy efficient control of three-phase induction motor drives. GRAMPC is appropriate for controlling nonlinear systems with input constraints in the (sub)millisecond range and is based on real-time solution strategy. The effect of the model algorithmic parameters: prediction horizon, the maximum number of iterations and number of data points is considered and default values in terms of real-time demands are determined. Additionally, some comparison results with conventional methods are provided, which demonstrate the advantages and performance of GRAMPC. The analysis for appropriate choice of the algorithmic parameters is based on
simulation results for three different induction motors with different rated powers.
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