Study on the Model Prediction Control and MRAS in Electrodeposited Process Control System for Vehicle Painting - Jo Hyok; Pak GumHyok; Ri CholMan; Han GuangJin; Kim Jong Chol; Ri Gi Song (Journal of Chemical Engineering Research Progress, 2026)
Electrodeposition is widely used in automotive painting due to its high adhesion and uniform coating. Temperature control is critical for coating quality, but stirred tanks exhibit nonlinear dynamics with large inertia and time-varying parameters. This study aims to develop an integrated control strategy combining model predictive control (MPC) with a model reference adaptive system (MRAS) to improve temperature control accuracy and robustness in a stirred electrodeposition tank. A robust MPC with N-step-free control action was designed based on an ARX-identified state-space model, and an MRAS estimator with PI adaptation was integrated to online-update the dominant time constant perturbed by stirring. Simulation and experimental results demonstrated that the proposed MPC-MRAS method achieved temperature control accuracy within ±0.2 °C, superior set-point tracking, and robust disturbance rejection compared to conventional MPC without parameter adaptation. The integrated strategy effectively compensates for model uncertainties caused by fluid agitation and operational variations, showing significant potential for industrial electrodeposition applications. Copyright © 2026 by Authors, Published by Universitas Diponegoro and BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).