Related Experiment Video
Updated: Oct 20, 2025

Operation of the Collaborative Composite Manufacturing CCM System
Published on: October 1, 2019
Development and Validation of Advanced Nonlinear Predictive Control Algorithms for Trajectory Tracking in Batch
Prajwal Shettigar J1, Kshetrimayum Lochan1, Gautham Jeppu1
1Department of Mechatronics Engineering, Department of Chemical Engineering, Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India.
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.
Related Concept Videos
Step-Growth Polymerization: Overview
Many natural and synthetic polymers are produced by...
Ziegler–Natta Chain-Growth Polymerization: Overview
Linear Approximation in Time Domain
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
Radical Chain-Growth Polymerization: Overview
Anionic Chain-Growth Polymerization: Overview
PD Controller: Design
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...

