A Comparative study between MPC and PI controller to control vacuum distillation unit for producing LVGO, MVGO, and HVGO

Wahid, Abdul; Prasetyo, A. P.

doi:10.1088/1757-899x/334/1/012020

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…[9] have developed the tuning method for MPC. However, if the controller performance that resulted is poor, the fine tuning is the best alternative method [10][11][12][13]. Three parameters of MPC have to tune are (sampling time), P (prediction horizon) and using identical model to compute M (control horizon).…”

Section: Figure 1 the Control Structure Of Depropanzer With Turbo Expmentioning

confidence: 99%

Optimation of Depropanizer Unit using Turbo Expander and Its Controller using Model Predictive Control

Wahid

Maulana

2018

E3S Web Conf.

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In this study, Turbo expander (TE) and Model Predictive Control (MPC) is suggested for depropanizer unit to increase propane recovery and improve control performance of the unit. The model that used in the MPC is a first order plus dead time (FOPDT), which tested the control performance using set point (SP) and disturbance change test. The measurement of the performance is the integral of the absolute error (IAE). As a result, use of TE in the depropanizer able to increase the recovery of propane of 8.44% (from 82.11% to 90.55%). The control structure of the depropanizer unit using turbo expander are pressure control for the TE (using proportional-integral control), composition control in the distillate flow (using MPC), and pressure control in depropanizer column (using MPC). The control performance after carrying out the tests show that at the SP change, the composition control and the pressure control in depropanizer unit has lower IAE values for MPC than PI contoller. Similarly when tested using disturbance rejection, the IAE of MPC is lower than PI controller. It means that MPC is better than PI controller for composition control and pressure control in depropanizer unit.

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Section: Figure 1 the Control Structure Of Depropanzer With Turbo Expmentioning

confidence: 99%

Optimation of Depropanizer Unit using Turbo Expander and Its Controller using Model Predictive Control

Wahid

Maulana

2018

E3S Web Conf.

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“…Wahid and Prasetio [13] has been researching singleinput single-output (SISO) MPC or single MPC applications on VDU. However, a SISO MPC has a weakness because it works like a PI controller that does not consider the inter-variable interactions that generally occur in a process.…”

Section: Introductionmentioning

confidence: 99%

Multi Input Multi Output (MIMO) Control 2x2 at Vacuum Distillation Unit for LVGO, MVGO, and HVGO Production

Wahid

Maro

2018

E3S Web Conf.

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Currently, Indonesia is still experiencing a fuel deficit, so it is necessary to build a new oil refinery and a process optimization at an existing refinery. A vacuum distillation unit (VDU) is used to process the atmospheric residue products from crude distillation unit (CDU). A multivariable model predictive control (MMPC) is proposed to improve a control performance in VDU because of the interaction between variables in the unit. Therefore, it is necessary to find the variables that interact with each other. In this study only two variables are discussed. Set point (SP) and disturbance changes are used to test the control performance with integral of square error (ISE) as the indicator. The results are compared with the control performance of the PI controller and a single MPC. As a result, the feed flow rate and bottom-stage temperature are strongest interactions so that both are determined as controlled variables in MMPC. The control performance of MMPC is better than the PI controller and the single MPC with control performance improvement of 48% to the PI controller and 21% to MPC on for Feed Flow Rates, and 98% to the PI controller and 27% to MPC on Bottom Stage Temperature. While on disturbance changes the enhancement is 35% for the Bottom Stage Temperature.

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“…[20][21][22]. e figure shows the circuit diagram of the PI controller with the following components, sensed voltage, V sensed , DC referenced voltage, V ref1 , error voltage (input voltage to the PI controller), V e , resistances, R 1 , R 2 , R 3 , R 4 , R 5 and feedback capacitance, C.…”

mentioning

confidence: 99%

Nonzero Staircase Modulation Scheme for Switching DC-DC Boost Converter

Salau

Eya

Onyebuchi

2020

Journal of Control Science and Engineering

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This paper presents a novel modulation scheme known as the nonzero staircase modulation scheme for switching DC-DC boost converters. This modulation scheme generates two distinct pulse trains/firing signals when a 50 Hz nonzero staircase modulating signal is compared with a 1.5 kHz triangular wave signal. Unlike the conventional modulation schemes, the proposed novel modulation scheme provides two distinctive trains of pulse-width modulated signals for mitigating low and high harmonics. It also possesses 0.56% total harmonic distortions (THD) of the output voltage waveform system, a power output of 4591 W, and THD of 1.12% in the DC-DC boost converter system. It has a simple design and low power loss of 209 W. The proposed scheme enables the single switch boost DC-DC converter used to have an efficiency of 96%. The proposed scheme can be applied in single switch or double switch boost DC-DC converter based-hospital equipment.

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A Comparative study between MPC and PI controller to control vacuum distillation unit for producing LVGO, MVGO, and HVGO

Cited by 5 publications

References 3 publications

Optimation of Depropanizer Unit using Turbo Expander and Its Controller using Model Predictive Control

Optimation of Depropanizer Unit using Turbo Expander and Its Controller using Model Predictive Control

Multi Input Multi Output (MIMO) Control 2x2 at Vacuum Distillation Unit for LVGO, MVGO, and HVGO Production

Nonzero Staircase Modulation Scheme for Switching DC-DC Boost Converter

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