Predictive temperature control design for reaction calorimeter based on mechanism parameter model

Isothermal control is the most basic and crucial function in the principle of a reaction calorimeter system and affects the speed and validity of the calorimetric experiment. However, the complex and uncertain working conditions in different reaction processes pose a challenge to the adaptability of temperature control algorithms. Aiming at the problem, a heat transfer model of the system is first established for temperature control design. From the simulation results, a prediction model based on equivalent mechanism parameters is determined for the control. Then, an integrated model predictive control (MPC) strategy is presented. To reduce the influence on the temperature control caused by the mismatch of the prediction model, a set of online parameter identification and adjustment methods is proposed. Simulations of the MPC control were implemented to analyze the control's performance. Experiments were also carried out to verify the advantages of the proposed strategy over the proportional-integral-derivative algorithm and demonstrate the role and efficiency of online identification. This control strategy can be applied to other laboratory-scale instruments with tank reactors.