Control Principles Based on a Model-Predictive Controller
DOI:
https://doi.org/10.52171/herald.369Keywords:
optimal control, oil refining, optimal filter, optimization problem, catalytic cracking, control algorithmAbstract
Design of automated process control systems plays an important role in modern industry. Adaptation of such control systems to various processes is one of the pressing issues, and the presented article examines the design principles of a new type of controller based on a predictive model as part of a combined industrial facility control system. A simulation is performed using MATLAB/Simulink to study the application of conventional and combined process control systems. The development and adaptation of a model predictive cascade PID controller to modern systems is compared with traditional control systems. The principal control variable was precisely and accurately controlled using this strong control method, and it was maintained at the required setpoints. The PID controller quickly responded when disturbances were introduced into the system, thereby lessening their influence. The simulation results suggest that integrating a PLC with a cascade Model Predictive Control and PID controller is a practical and desirable strategy. These results show that this integrated regulatory system can greatly enhance control performance, attain reference targets.
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