Model Predictive Control for Bread Oven Temperature Regulation: Thermal Modeling, Constraint Handling and Performance Evaluation Against PID Control

Abstract

Precise temperature regulation is essential in industrial bread baking to ensure product quality, energy efficiency, and process reliability. Conventional Proportional–Integral–Derivative (PID) controllers are widely used but often exhibit overshoot, oscillation, and poor disturbance rejection under varying operating conditions. This study develops a Model Predictive Control (MPC)-based temperature regulation system for a bread oven using a physics-based thermal model derived from conduction, convection, and radiation heat transfer mechanisms. The thermal model was formulated in state-space form, and the MPC controller was implemented and simulated in MATLAB R2023a. The controller was evaluated under reference temperature changes, thermal load disturbance due to dough insertion, ambient temperature variation, and actuator constraint stress test, and its performance was compared with that of a conventional PID controller using rise time, settling time, and percentage overshoot. Simulation results showed that the MPC controller achieved smooth temperature tracking with zero overshoot, superior disturbance rejection, effective handling of actuator constraints, and highly consistent convergence characteristics. Although the PID controller exhibited a faster initial response, it produced overshoot, oscillatory behavior, and larger control input fluctuations. The results demonstrate that the proposed MPC strategy provides a robust, accurate, and energy-efficient solution for bread oven temperature regulation and is suitable for industrial baking systems and other temperature-sensitive thermal processing applications.