“Model Predictive Control of Low-Speed Partial Stroke Operated Digital Displacement Pump Unit”
Authors: Niels Henrik Pedersen, Per Johansen, Anders Hedegaard Hansen and Torben Ole Andersen,Affiliation: Aalborg University
Reference: 2018, Vol 39, No 3, pp. 167-177.
Keywords: Digital Displacement Units, Fluid Power, Control, Non-smooth System, Hybrid Systems
Abstract: To enhance the use of the Digital Displacement Machine (DDM) technology as the future solution for low speed fluid power pump and motor units, a Model Predictive Control (MPC) strategy is presented. For a low speed DDM, the conventional full stroke operation strategy is unsuitable, since the control update rate is proportional to the machine speed. This creates an incentive to utilize sequential partial stroke operation where a fraction of the full stroke is used, which thereby increases the control update rate and control signal resolution. By doing this, the energy loss is increased and may become undesirable large if the control objective is purely set-point tracking, why a trade-off is considered advantageous. Discretizing the full stroke based on a chosen update rate results in a Discrete Linear Time Invariant (DLTI) model of the system with discrete input levels. In this paper, the Differential Evolution Algorithm (DEA) is used to determine the optimal control input based on the trade-off between set-point tracking and energy cost in the prediction horizon. The paper presents a flow and a pressure control strategy for a fixed speed digital displacement pump unit and shows the trade-off influence on the optimal solution through simulation. Results show the applicability of the control strategy and indicate that a much higher energy efficiency may be obtained with only a minor decrease in tracking performance for pressure control.
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DOI: 10.4173/mic.2018.3.3DOI forward links to this article:
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BibTeX:
@article{MIC-2018-3-3,
title={{Model Predictive Control of Low-Speed Partial Stroke Operated Digital Displacement Pump Unit}},
author={Pedersen, Niels Henrik and Johansen, Per and Hansen, Anders Hedegaard and Andersen, Torben Ole},
journal={Modeling, Identification and Control},
volume={39},
number={3},
pages={167--177},
year={2018},
doi={10.4173/mic.2018.3.3},
publisher={Norwegian Society of Automatic Control}
};