Inferential Control of Fuel Additive Purity via Reactive Distillation Process

2018 ◽  
Vol 37 ◽  
pp. 127-140 ◽  
Author(s):  
Abdulwahab Giwa ◽  
Edmund Iniyemi Yibo ◽  
Abel Adekanmi Adeyi
Keyword(s):  
Transfer Function ◽  
Mole Fraction ◽  
Pid Controller ◽  
Closed Loop ◽  
Reactive Distillation ◽  
Fuel Additive ◽  
Reflux Ratio ◽  
Transfer Function Model ◽  
Function Model ◽  
Product Temperature

In this work, the control of the mole fraction of a fuel additive being produced in a reactive distillation column has been carried out using proportional-integral-derivative (PID) control. The fuel additive considered in this case was isopropyl alcohol, which was produced from the reaction between propylene and water. To accomplish the work, a ChemCAD model of the process was first developed and simulated to convergence before it was converted to dynamic type from which the dynamic responses of the system were generated and used, with the aid of MATLAB, to develop a transfer function model having the reboiler duty, the reflux ratio and the temperature of the bottom product as the input, the disturbance and the output variables of the process, respectively. The obtained transfer function model was used to develop the open-loop and the closed-loop Simulink models of the process that were also simulated. The closed-loop simulation was carried out with the objective of achieving a fuel additive product with a mole fraction of 0.97, and this was done using a PID controller that was applied inferentially via the product temperature. The results obtained showed that the control of the fuel additive mole fraction could be achieved inferentially, with PID controller tuned with Cohen-Coon and Simulink approaches, using product temperature.

System Identification and IMC-Based PID Control of a Reactive Distillation Process: A Case Study of n-Butyl Acetate Production

2017 ◽  
Vol 31 ◽  
pp. 104-119 ◽  
Author(s):  
Abdulwahab Giwa ◽  
John Olusoji Owolabi ◽  
Saidat Olanipekun Giwa
Keyword(s):  
Transfer Function ◽  
Pid Control ◽  
Butyl Acetate ◽  
Closed Loop ◽  
Reactive Distillation ◽  
Research Work ◽  
Absolute Error ◽  
Distillation Process ◽  
Function Model ◽  
Input Variables

The identification of a reactive distillation system for the production of n-butyl acetate from the esterification reaction between acetic acid and n-butanol has been carried out in this research work. In order to achieve the aim of the research work, a prototype plant of the process was developed using ChemCAD from which dynamics data were generated upon applications of step changes to the reboiler duty and the reflux ratio, which were the input variables of the system. Thereafter, the transfer function of the process, later represented in Simulink environment, was formulated using the dynamics data and with the aid of MATLAB. The simulation of the transfer function model of the system was also carried out for open loop by applying step changes unto the input variables using the developed Simulink model of the system. Thereafter, the closed-loop control system developed also in Simulink environment was simulated by applying step changes to the set-point variable, which was the bottom mole fraction of n-butyl acetate. The results obtained from the simulation of the prototype plant of the reactive distillation process showed ChemCAD to be a powerful tool for steady state and dynamics prototype plant development. Furthermore, good representation and stability were also observed to exist in the system from the formulation and the simulation of the transfer function model of the process, which were carried out with the aid of MATLAB/Simulink. Moreover, the selection of appropriate closed-loop time constant contained in the tuning parameter formulas of IMC-based control system showed that the value suggested by Rivera et al. [1] was very good for this system, compared to those of Chien and Fruehauf [2] and Skogestad [3], because it could give closed-loop dynamic response with comparatively very low values of integral squared error (ISE), integral absolute error (IAE) and integral time absolute error (ITAE) for both proportional-integral (PI) and proportional-integral-derivative (PID) control systems. In addition, the comparison made between the IMC-based tuning approach and other ones (Cohen-Coon, Tyreus-Luyben and Ziegler-Nichols) considered in this work made it known that IMC-based tuning technique was the best among all those considered because its ISE, IAE and ITAE were found to be the lowest for both PI-and PID-controlled cases simulated.

Study on Pilot Transfer Function Model Gain of Closed-Loop Pilot-Vehicle System

2013 ◽  
Vol 706-708 ◽  
pp. 1038-1041
Author(s):  
Lin Li ◽  
Jun Xu ◽  
Fu Lei Zheng
Keyword(s):  
Steady State ◽  
Transfer Function ◽  
Calculation Method ◽  
Closed Loop ◽  
Reference Value ◽  
Transfer Function Model ◽  
Function Model ◽  
Specific Calculation ◽  
Pilot Model ◽  
Vehicle System

Based on the analysis of pilot handling behavior characteristics, this paper establishes the pilot transfer function model. According to the characteristics of closed-loop pilot-vehicle system and the relationship between pilot and flight quality, the specific calculation method of pilot model steady state gain was given. Take the aircraft roll angle manipulation for example, and simulate the pilot's manipulation of aircraft of dynamic process. The results show that: the pilot model steady state gain calculation method is simple and feasible, and have a certain reference value for the analysis of closed-loop pilot-vehicle system.

Dynamic Control of Biologically Inspired Pulsatile Jet Propulsion Thrusters

2009 ◽  
Author(s):  
Michael Krieg ◽  
Kamran Mohseni
Keyword(s):  
Transfer Function ◽  
Frequency Response ◽  
Closed Loop ◽  
Dynamic Control ◽  
Transfer Function Model ◽  
Function Model ◽  
Jet Propulsion ◽  
Vehicle Simulation ◽  
Virtual Vehicle ◽  
Slug Model

Inspired by the propulsion techniques employed by squid and other cephalopod, a new type of thruster was designed which utilized pulsatile jet propulsion to generate controlling forces. The thrust production from this jet actuator was characterized in a static environment and seen to be well approximated by a simple fluid slug model. A linear transfer function model was derived to describe the transient dynamics of this thruster being employed in a virtual vehicle simulation; which was developed to test the thruster with unsteady driving signals. It was predicted that an impulsive type of thrust (as is found in our jet actuator) is ideal in a non-linear damping environment, since all of the acceleration is being added to the system while its at its lowest velocity and therefore lowest drag. Due to the extremely nonlinear nature of underwater vehicle environments we developed a scaling system to classify regimes of maneuvers and characterize their dynamics independently. Assuming a simple proportional derivative control algorithm, the vehicle closed loop frequency response was predicted using the transfer function model; which was linearized according to the maneuvering regime. Within the hybrid simulation environment, the closed loop frequency response was tested empirically and seen to be well approximated by the model.

Model Fungsi Transfer Input Ganda untuk Pemodelan Jakarta Islamic Index

2019 ◽  
Vol 7 (3) ◽  
Author(s):  
Nur Laela Fitriani ◽  
Pika Silvianti ◽  
Rahma Anisa
Keyword(s):  
Exchange Rate ◽  
Transfer Function ◽  
Multivariate Time Series ◽  
Model Identification ◽  
Transfer Function Model ◽  
Function Model ◽  
Jones Index ◽  
Multiple Input ◽  
Identification Stage ◽  
Stage Estimation

Transfer function model with multiple input is a multivariate time series forecasting model that combines several characteristics of ARIMA models by utilizing some regression analysis properties. This model is used to determine the effect of output series towards input series so that the model can be used to analyze the factors that affect the Jakarta Islamic Index (JII). The USD exchange rate against rupiah and Dow Jones Index (DJI) were used as input series. The transfer function model was constructed through several stages: model identification stage, estimation of transfer function model, and model diagnostic test. Based on the transfer function model, the JII was influenced by JII at the period of one and two days before. JII was also affected by the USD exchange rate against rupiah at the same period and at one and two days before. In addition, the JII was influenced by DJI at the same period and also at period of one until five days ago. The Mean Absolute Prencentage Error (MAPE) value of forecasting result was 0.70% and the correlation between actual and forecast data was 0.77. This shows that the model was well performed for forecasting JII.

scholarly journals Administrative Costs and Tariff Rates in the Presence of Customs Evasion: Evidence from Ecuador

Economies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 21
Author(s):  
Jazmín González Aguirre ◽  
Alberto Del Villar
Keyword(s):  
International Trade ◽  
Transfer Function ◽  
Gross Domestic Product ◽  
Foreign Trade ◽  
Transfer Function Model ◽  
Administrative Cost ◽  
Function Model ◽  
Administrative Costs ◽  
Tariff Rates ◽  
Budgetary Expenditure

This paper seeks to assess the effectiveness of customs policies in increasing the resources devoted to controlling and inspection. Specifically, it seeks to analyze whether an increase in the administrative cost of collecting taxes on foreign trade in Ecuador contributes to reducing customs fraud. To this end, we identify and estimate a transfer function model (ARIMAX), considering information on foreign trade such as official international trade statistics report and tariff rates, as well as the execution of budgetary expenditure and Ecuador’s gross domestic product (GDP). The period under study includes quarterly series from 2006 to 2018. The results obtained by the model indicate that allocating greater material and budgetary resources to combat customs fraud does not always achieve the objective of reducing customs evasion.

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