Estudio comparativo de control PID, predictivo y difuso en un proceso de flujo.
A suitable scenario for the analysis of control systems is the comparison between PID, predictive and fuzzy control using a flow process that can be linear or non-linear. However, to carry out this comparison, it is necessary to establish the technical operating conditions for its implementation usi...
Gorde:
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| Formatua: | masterThesis |
| Hizkuntza: | spa |
| Argitaratua: |
2023
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| Gaiak: | |
| Sarrera elektronikoa: | http://repositorio.utc.edu.ec/handle/27000/11527 |
| Etiketak: |
Etiketa erantsi
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Etiketa erantsi | Gaia: | A suitable scenario for the analysis of control systems is the comparison between PID, predictive and fuzzy control using a flow process that can be linear or non-linear. However, to carry out this comparison, it is necessary to establish the technical operating conditions for its implementation using mathematical models that consider the control and process variables. The control systems used in this project have libraries that allow their implementation in physical memory, such as the S7-1200 PLC and the Arduino Uno microcontroller. As an interaction link, an OPC communication platform is used, which allows communication to be established. successful between the implemented plant and the KepServerEX software that supports both controllers in real time. Each controller is designed in the Matlab Simulink tool once the conditions for its implementation have been created. At this stage, the most arduous process is to find the right tuning point that provides stability and speed to the system. As a result, it is necessary to apply experimental techniques and observation of the behavior of each of the controllers to be able to implement them, carefully adjusting their tuning values. The result of the implementation when performing a PID flow control and also for a predictive control shows that it is stable, unlike a fuzzy control with the variation in transient response that is much faster; In PID control there is better management of the variable in steady state for predictive control. However, the performance of both controllers is very similar, even in the rejection of disturbances, taking into account that the steady state variable and the flow variable in the PID control are managed thanks to the mathematical model due to its ease of implementation. . |
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