Evidence map›Paper›PMID 36790937›Full record

ArticleInternational symposium on process systems engineering2022

Application of MHE-based NMPC on a Rotary Tablet Press under Plant-Model Mismatch.

Yan-Shu Huang, M Ziyan Sheriff, Sunidhi Bachawala, Marcial Gonzalez, Zoltan K Nagy, Gintaras V Reklaitis

Abstract read
In one paragraph

Article in International symposium on process systems engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Yan-Shu HuangDavidson School of Chemial Engineering, Purdue University, West Lafayette, IN 47907, USA.
M Ziyan SheriffDavidson School of Chemial Engineering, Purdue University, West Lafayette, IN 47907, USA.
Sunidhi BachawalaSchool of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.
Marcial GonzalezSchool of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.
Zoltan K NagyDavidson School of Chemial Engineering, Purdue University, West Lafayette, IN 47907, USA.
Gintaras V ReklaitisDavidson School of Chemial Engineering, Purdue University, West Lafayette, IN 47907, USA.

Funding

Industry 4.0 Implementation in Continuous Pharmaceutical ManufacturingU01FD006487 · FDA · UNIVERSITY OF DELAWARE · PI IERAPETRITOU, MARIANTHI · 2018 to 2020
$4.0M
FDA HHS U01 FD006487
6 · The paper itself

Abstract

Active control strategies play a vital role in modern pharmaceutical manufacturing. Automation and digitalization are revolutionizing the pharmaceutical industry and are particularly important in the shift from batch operations to continuous operation. Active control strategies provide real-time corrective actions when departures from quality targets are detected or even predicted. Under the concept of Quality-by-Control (QbC), a three-level hierarchical control structure can be applied to achieve effective setpoint tracking and disturbance rejection in the tablet manufacturing process through the development and implementation of a moving horizon estimation-based nonlinear model predictive control (MHE-NMPC) framework. When MHE is coupled with NMPC, historical data in the past time window together with real-time data from the sensor network enable model parameter updating and control. The adaptive model in the NMPC strategy compensates for process uncertainties, further reducing plant-model mismatch effects. The frequency and constraints of parameter updating in the MHE window should be determined cautiously to maintain control robustness when sensor measurements are degraded or unavailable. The practical applicability of the proposed MHE-NMPC framework is demonstrated via using a commercial scale tablet press, Natoli NP-400, to control tablet properties, where the nonlinear mechanistic models used in the framework can predict the essential powder properties and provide physical interpretations.

Indexed as

continuous manufacturingmoving horizon estimationnonlinear model predictive controlpharmaceutical manufacturingprocess control

Identifiers

PMID36790937
PMCPMC9923513

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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.