Evidence map›Paper›PMID 41976740›Full record

ArticleMaterials (Basel, Switzerland)2026

Precise Pressure Control for Screw Extrusion 3D Printing of PP-GF Composites Based on Inverse Model Feedforward and Variable Structure Feedback.

Yunlong Ma, Xiping Li, Nan Ma, Youqiang Yao, Sisi Wang, Zhonglue Hu

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yunlong MaCollege of Engineering, Zhejiang Normal University, Jinhua 321004, China.
Xiping LiCollege of Engineering, Zhejiang Normal University, Jinhua 321004, China.
Nan MaTianjin Institute of Aerospace Mechanical and Electrical Equipment, Tianjin 300456, China.
Youqiang YaoCollege of Engineering, Zhejiang Normal University, Jinhua 321004, China.
Sisi WangCollege of Engineering, Zhejiang Normal University, Jinhua 321004, China.
Zhonglue HuCollege of Engineering, Zhejiang Normal University, Jinhua 321004, China.

Funding

Major and Key Science and Technology Plan Project of Jinhua City 2024-1-055
6 · The paper itself

Abstract

Addressing challenges such as the non-Newtonian fluid characteristics of melt, significant system hysteresis, and rheological thermal drift in large-scale glass fiber-reinforced polypropylene (PP-GF) screw-extrusion additive manufacturing (SEAM), this paper proposes a composite pressure control strategy based on inverse model feedforward and variable-structure feedback (VSFC-Smith). This strategy establishes a dynamic pressure benchmark through an inverse rheological model, utilizes a Smith predictor to compensate for time delay, and introduces dead-zone variable-structure feedback to smoothly suppress thermal drift. Experimental results demonstrate that, compared to traditional PID (Proportional-Integral-Derivative) controller, the VSFC-Smith strategy reduces the step pressure overshoot from 23.37% to 17.37%, decreases steady-state screw speed fluctuation by approximately 50%, and limits the error within ±0.04 MPa during complex trajectory tracking. In practical molding validation, this strategy effectively suppressed surface ripples, reducing the surface roughness (Sa) by 14.5% to 124.41 μm; simultaneously, the Z-directional interlayer tensile strength reached 12.63 MPa (a 22.5% improvement compared to open-loop control). This study successfully overcomes the limitations of traditional high-gain feedback, achieving synergistic optimization of the macroscopic morphology and microscopic mechanical properties of composite parts.

Indexed as

interlayer bonding strengthprecise pressure controlscrew extrusion additive manufacturingsmith predictorvariable structure feedback

Identifiers

PMID41976740
PMCPMC13074240

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.