Recursive Least Squares–Based Adaptive Temp...

Recursive Least Squares–Based Adaptive Temperature Control of a Batch Mma Polymerization Reactor

Author Name : Sangeeta Metkar, Dr. Raju Mankar, Dr. Imran Rahman

DOI: https://doi.org/10.56025/IJARESM.2026.0502170073

ABSTRACT Precise temperature regulation in batch polymerization reactors is critical for ensuring product quality, operational safety, and batch-to-batch consistency. This paper presents an adaptive temperature control strategy based on the Recursive Least Squares (RLS) algorithm for a batch suspension polymerization reactor producing methyl methacrylate (MMA). While RLS is traditionally employed within Model Predictive Control (MPC) frameworks for online model identification, this work exploits RLS directly as an adaptive control mechanism to cope with nonlinear, time-varying reactor dynamics. Reactor temperature is regulated by manipulating electrical heater power in the presence of strong nonlinearities, gel and glass effects, and varying heat transfer characteristics. Closed-loop simulation studies demonstrate that the proposed RLS-based controller achieves improved tracking performance, reduced overshoot, and enhanced robustness compared with fixed PI, adaptive PID, and globally linearizing control strategies. Owing to its simplicity, fast convergence, and low computational demand, the proposed approach represents a practical alternative to nonlinear MPC for industrial batch polymerization processes.