Adaptive Model Predictive Control of a Batch Solution Polymerization Process using Trajectory Linearization

TL;DR

This paper presents an adaptive model predictive control method for a batch MMA polymerization process, using trajectory linearization and multiple transfer functions to accurately track temperature trajectories.

Contribution

It introduces a novel sequential trajectory linearized adaptive MPC approach based on mechanistic modeling and transfer function linearization for batch polymerization control.

Findings

Controller effectively tracks desired temperature trajectories.

Model validation confirms accuracy of the linearized transfer functions.

Experimental results demonstrate improved temperature regulation.

Abstract

A sequential trajectory linearized adaptive model based predictive controller is designed using the DMC algorithm to control the temperature of a batch MMA polymerization process. Using the mechanistic model of the polymerization, a parametric transfer function is derived to relate the reactor temperature to the power of the heaters. Then, a multiple model predictive control approach is taken in to track a desired temperature trajectory.The coefficients of the multiple transfer functions are calculated along the selected temperature trajectory by sequential linearization and the model is validated experimentally. The controller performance is studied on a small scale batch reactor.