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A Validated Model for Design and Evaluation of Control Architectures for a Continuous Tablet Compaction Process

By Nunes de Barros, Fernando; Bhaskar, Aparajith; Singh, Ravendra

Published on CMKC

Abstract

The systematic design of an advanced and efficient control strategy for controlling critical quality attributes of the tablet compaction operation is necessary to increase the robustness of a continuous pharmaceutical manufacturing process and for real time release. A process model plays a very important role to design, evaluate and tune the control system. However, much less attention has been made to develop a validated control relevant model for tablet compaction process that can be systematically applied for design, evaluation, tuning and thereby implementation of the control system. In this work, a dynamic tablet compaction model capable of predicting linear and nonlinear process responses has been successfully developed and validated. The nonlinear model is based on a series of transfer functions and static polynomial models. The model has been applied for control system design, tuning and evaluation and thereby facilitate the control system implementation into the pilot-plant with less time and resources. The best performing control algorithm was used in the implementation and evaluation of different strategies for control of tablet weight and breaking force. A characterization of the evaluated control strategies has been presented and can serve as a guideline for the selection of the adequate control strategy for a given tablet compaction setup. A strategy based on a multiple input multiple output (MIMO) model predictive controller (MPC), developed using the simulation environment, has been implemented in a tablet press unit, verifying the relevance of the simulation tool.

Journal

Processes. Volume 5, 2017, 76

DOI

10.3390/pr5040076

Type of publication

Peer-reviewed journal

Affiliations

  • Rutgers, The State University of New Jersey

Article Classification

Research Article

Classification Areas

  • Oral doses
  • Modeling

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