CONTROL AND OBSERVER SIMULATION ON THE COMPLEXITY MODELING OF DRY TANK DEMO SET SYSTEM
The previous demo set is a simulator level control parameter in filling tank interaction process. As a learning medium, the demo set requires system modeling in accordance with the actual conditions in the industrial process. In this final project, the complexity of modeling the demo set system i...
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Main Author: | |
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/49975 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | The previous demo set is a simulator level control parameter in filling tank
interaction process. As a learning medium, the demo set requires system modeling
in accordance with the actual conditions in the industrial process.
In this final project, the complexity of modeling the demo set system is carried out
by changing the location of the control action which was initially carried out at the
input to the output for the interaction tank system. Complexity is done so that the
system is more in accordance with the actual situation. The control is done by
placing polishes and adding integral conditions. In this final project, an observer
is also designed to observe state variables in system modeling using the full state
order observer method.
Controlling with the pole placement and the addition of integral conditions is
carried out on each tank for the interaction tank system without additional
disturbances. The output response shows that the control system with the pole
placement method and the addition of the integral conditions produces a faster
output response than the open loop system response. Meanwhile, the system output
response using a controller and the addition of an integral condition results in a
greater and slower overshoot (OS) value than when controlling using the pole
placement alone. Addition of disturbance to the interaction tank system results in
smaller offsets when using controllers with the addition of integral conditions
rather than the pole placement method.
The simulation results of the control system with the observer show that the addition
of the observer gain to the control system will reduce the eror value in the difference
between the system observer state variable and the system state variable. Adding
noise to the control system still results in an offset in the output response. Therefore,
the control system was redesigned to find a relationship between the minimum pole
dominant placement and the disturbance variance value so that the resulting offset
is 5% and 10%.
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