Development and Validation of Advanced Nonlinear Predictive Control Algorithms for Trajectory Tracking in Batch Polymerization

Prajwal Shettigar J, Kshetrimayum Lochan, Gautham Jeppu, Srinivas Palanki, Thirunavukkarasu Indiran

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In this work, a computationally efficient nonlinear model-based control (NMBC) strategy is developed for a trajectory-tracking problem in an acrylamide polymerization batch reactor. The performance of NMBC is compared with that of nonlinear model predictive control (NMPC). To estimate the reaction states, a nonlinear state estimator, an unscented Kalman filter (UKF), is employed. Both algorithms are implemented experimentally to track a time-varying temperature profile for an acrylamide polymerization reaction in a lab-scale polymerization reactor. It is shown that in the presence of state estimators the NMBC performs significantly better than the NMPC algorithm in real time for the batch reactor control problem.

Original languageEnglish
JournalACS Omega
DOIs
Publication statusAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)

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