Implementación de un control predictivo para un proceso multivariable de nivel y caudal
The present technological proposal comprises a methodology for the implementation of a Model Based Predictive Control (MPC) that is established within modern control engineering and is used as a tool for the regulation of variables when classical control techniques have not been able to handle condi...
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| Formaat: | bachelorThesis |
| Taal: | spa |
| Gepubliceerd in: |
2022
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| Onderwerpen: | |
| Online toegang: | http://repositorio.utc.edu.ec/handle/27000/9483 |
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Voeg label toe | Samenvatting: | The present technological proposal comprises a methodology for the implementation of a Model Based Predictive Control (MPC) that is established within modern control engineering and is used as a tool for the regulation of variables when classical control techniques have not been able to handle conditions for planning, acting in advance or predicting the controller's actions in order to maintain the process variable(s) within acceptable ranges. The experimental result of this proposal has been applied to a didactic module for the control of flow and level variables that has involved the use of PLC S7-1200 control equipment mainly to receive voltage signals from the sensors and to send voltage to the frequency inverter iG5A, In the same way, the KEPServerEX communication server has been used to allow the interaction between the TIA Portal software and the MATLAB Simulink tool, these have been used mainly for signal scaling and to send data used in the design of the MPC controller model; which starts with the obtaining of equations in state space of each variable, which includes stages of: data acquisition, data processing, modeling and validation. Once this is done, we proceed to simulate the behavior of the controller in open loop, in order to obtain tuning adjustments such as: control horizon, prediction and sampling times. Finally, the controller is implemented to the real processes of the plant. This controller was compared with a proportional integral derivative control (PID) tuned aggressively to ratify its characteristics in equal conditions, in terms of: delay times, settling times, rise times, percentages of over impulse and stability. As a result, the most evident parameter when using the MPC control is the over impulse for both the flow and level processes, presenting a percentage of 1.57% and 1.20% respectively. However, the best stabilization is seen in the MPC; since the PID control presents more noticeable oscillations. |
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