scholarly journals A Study of the Dynamics and Control of the Model IV Fluidized Catalytic Cracking Process

2014 ◽  
Vol 5 (1) ◽  
pp. 1-26
Author(s):  
Dhia Yasser Aqar
Keyword(s):  
Flow Rate ◽  
Catalytic Cracking ◽  
Closed Loop ◽  
Research Work ◽  
Economic Benefits ◽  
Open Loop ◽  
Internal Model Control ◽  
Oil Refineries ◽  
Bed Temperature ◽  
Model Control

Fluid catalytic cracking (FCC) is one of the most important chemical units in oil refineries due to its economic benefits. This research work concentrates on improving the control system of the Model IV FCC unit where dynamic modeling and the controllability based on the McFarlane et al. (1993) model. Different open-loop tests were carried out in the wash oil flow rate (F1) and the furnace fuel flow rate (F5) to find the FCC models using Sundaresan and Krishnaswamy (S&K) and fraction incomplete response (FIR) methods. The riser temperature (Tr) and the regenerator bed temperature (Tg) were chosen as the control variables while (F1 and F5) were selected as the corresponding manipulated variables based on the relative gain array (RGA).  PI controller tuning parameters were evaluated using the internal model control (IMC) method and different closed-loop control responses were examined for both set point tracking and disturbance rejection changes. Additional adjustments to the IMC filter constant were employed to further improve the closed loop responses for the system.

Tracking Trajectories in a Continuous Anaerobic Bioreactor Employing a Nonlinear Proportional Controller

2007 ◽  
Vol 5 (1) ◽  
Author(s):  
M. Isabel Neria-Gonzalez ◽  
Ricardo Aguilar-López
Keyword(s):  
Internal Model ◽  
Closed Loop ◽  
Open Loop ◽  
Internal Model Control ◽  
Control Law ◽  
Anaerobic Bioreactor ◽  
Model Control ◽  
Integral Controller ◽  
Proportional Integral Controller ◽  
Proportional Controller

This work is related to the tracking of sulfate concentration trajectories in a continuous anaerobic bioreactor, where Desulfovibrio alaskensis is considered for different operation purposes. A new design of a class of nonlinear proportional control law with an adaptive gain was proposed. The proposed controller was applied to the mathematical bioreactor's model with the kinetics experimentally corroborated; this describes the dynamics of biomass, sulfate and sulfide concentrations. The open-loop stability conditions of the optimum set points and the corresponding closed-loop performances were analyzed. The proposed control law is able to track trajectories, despite sustained disturbances. An Internal Model Control (IMC) Proportional-Integral Controller was implemented for comparison purposes and the corresponding performances were illustrated via numerical experiments.

Discrete-time internal model control with disturbance and vibration rejection

2016 ◽  
Vol 23 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Robin De Keyser ◽  
Cosmin Copot ◽  
Andres Hernandez ◽  
Clara Ionescu
Keyword(s):  
Discrete Time ◽  
Disturbance Rejection ◽  
Internal Model ◽  
Design Methodology ◽  
Closed Loop ◽  
Open Loop ◽  
Internal Model Control ◽  
Process Dynamics ◽  
Model Control ◽  
Novel Design

This paper presents a novel design methodology for discrete-time internal model control (IMC) used to compute a disturbance filter. The proposed method employs a generalized algorithm for disturbance rejection and for process dynamics compensation. In IMC, the controller is designed based on a model of the process, while ensuring a desired closed loop performance trajectory (for setpoint tracking). However, in some situations, for example poorly damped systems, the open loop poles of the process affect the closed loop disturbance rejection dynamics. The novel design methodology presented is able to compensate both process dynamics and input disturbances. The method is validated both in simulations and in experimental tests on a poorly damped mass–spring–damper testbench.

scholarly journals Stabilization of the Magnetic Levitation System

2021 ◽  
Vol 11 (21) ◽  
pp. 10369
Author(s):  
Štefan Chamraz ◽  
Mikuláš Huba ◽  
Katarína Žáková
Keyword(s):  
Closed Loop ◽  
Magnetic Levitation ◽  
Internal Model Control ◽  
Pass Filter ◽  
Low Pass Filter ◽  
First Order ◽  
Model Based ◽  
Model Control ◽  
Levitation System ◽  
Magnetic Levitation System

This paper contributes toward research on the control of the magnetic levitation plant, representing a typical nonlinear unstable system that can be controlled by various methods. This paper shows two various approaches to the solution of the controller design based on different closed loop requirements. Starting from a known unstable linear plant model—the first method is based on the two-step procedure. In the first step, the transfer function of the controlled system is modified to get a stable non-oscillatory system. In the next step, the required first-order dynamic is defined and a model-based PI controller is proposed. The closed loop time constant of this first-order model-based approach can then be used as a tuning parameter. The second set of methods is based on a simplified ultra-local linear approximation of the plant dynamics by the double-integrator plus dead-time (DIPDT) model. Similar to the first method, one possible solution is to stabilize the system by a PD controller combined with a low-pass filter. To eliminate the offset, the stabilized system is supplemented by a simple static feedforward, or by a controller proposed by means of an internal model control (IMC). Another possible approach is to apply for the DIPDT model directly a stabilizing PID controller. The considered solutions are compared to the magnetic levitation system, controlled via the MATLAB/Simulink environment. It is shown that, all three controllers, with integral action, yield much slower dynamics than the stabilizing PD control, which gives one motivation to look for alternative ways of steady-state error compensation, guaranteeing faster setpoint step responses.

scholarly journals Anisochronic Internal Model Control Design

10.14311/482 ◽  
2003 ◽  
Vol 43 (5) ◽  
Author(s):  
T. Vyhlídal ◽  
P. Zítek
Keyword(s):  
System Dynamics ◽  
Internal Model ◽  
Closed Loop ◽  
Control Design ◽  
Internal Model Control ◽  
Loop System ◽  
Closed Loop System ◽  
First Order ◽  
Dominant Pole ◽  
Model Control

The features of internal model control (IMC) design based on the first order anisochronic model are investigated in this paper. The structure of the anisochronic model is chosen in order to fit both the dominant pole and the dominant zero of the system dynamics being approximated. Thanks to its fairly plain structure, the model is suitable for use in IMC design. However, use of the anisochronic model in IMC design may result in so-called neutral dynamics of the closed loop. This phenomenon is studied in this paper via analysing the spectra of the closed loop system.

A closed-loop analysis of the tubuloglomerular feedback mechanism

1991 ◽  
Vol 261 (5) ◽  
pp. F880-F889 ◽  
Author(s):  
N. H. Holstein-Rathlou
Keyword(s):  
Flow Rate ◽  
Closed Loop ◽  
Feedback Mechanism ◽  
Open Loop ◽  
Tubuloglomerular Feedback ◽  
Operating Point ◽  
Sprague Dawley ◽  
Loop Analysis ◽  
Experimental Conditions ◽  
Tubular Flow

The tubuloglomerular feedback (TGF) mechanism is of importance in the regulation of glomerular filtration rate (GFR). A second mechanism of potential importance is the change in proximal pressure caused by a change, for example, in the rate of proximal fluid reabsorption. The quantitative contributions of these two mechanisms to the regulation of GFR and the late proximal flow rate are not known. To determine the regulatory efficiency of these two mechanisms, the late proximal flow rate was perturbed by microperfusion with artificial tubular fluid in halothane-anesthetized Sprague-Dawley rats. The resulting changes in late proximal flow rate were measured by pulse injection of rhodamine dextran. Fluorescence was excited by means of a He-Ne laser. Bolus velocity was measured by videomicroscopy. Tubular pressure was measured by the servonulling method. The microperfusion rate was varied from -15 to 20 nl/min in steps of 5 nl/min. The open-loop gain (OLG) was 3.1 (range 1.5-9.9, n = 13) at the unperturbed tubular flow rate, and decreased as the tubular flow rate was either increased or decreased. The proximal pressure increased by 0.21 +/- 0.03 mmHg per unit increase in late proximal flow rate (nl/min). By use of a mathematical model of the glomerulus, it is estimated that under the present experimental conditions the pressure increase contributes 8% (range 3-15%) of the OLG. It is concluded that, for small perturbations around the operating point, TGF accounts for most of the regulation of GFR and the late proximal flow rate, with changes in the proximal pressure of lesser importance. Furthermore, under closed-loop conditions the operating point for the TGF mechanism is at or close to the point of maximal sensitivity.

Design and Simulation of IMC based PI Controller for a MIMO Process

2018 ◽  
pp. 57-63
Author(s):  
Ravikumar C ◽  
Sivakumar D
Keyword(s):  
Mathematical Models ◽  
Detailed Analysis ◽  
Flow Rate ◽  
Internal Model ◽  
Pi Controller ◽  
Internal Model Control ◽  
Nonlinear Behaviour ◽  
Simulation Studies ◽  
Input Output ◽  
Model Control

The objective of this paper is to develop the Internal Model Control (IMC) based PI Controller for a MIMO (SISO) Process. The controller thus developed is implemented on Laboratory interacting coupled tank process through simulation. This can be regarded as the relevant process control in petrol and chemical industries. These industries involve controlling the liquid level and the flow rate in the presence of nonlinearity and disturbance which justifies the use of IMC based PI Controller scheme. For this purpose, mathematical models are obtained for each of the input-output combinations using white box approach and the respective controllers are developed. A detailed analysis on the performance of the chosen process with these controllers is carried out. Simulation studies reveal the effectiveness of proposed controller for MIMO process that exhibits nonlinear behaviour.

scholarly journals Permeate Flux Control in SMBR System by Using Neural Network Internal Model Control

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1672
Author(s):  
Norhaliza Abdul Wahab ◽  
Nurazizah Mahmod ◽  
Ramon Vilanova
Keyword(s):  
Neural Network ◽  
Control System ◽  
Radial Basis Function ◽  
Basis Function ◽  
Membrane Fouling ◽  
Internal Model ◽  
Closed Loop ◽  
Internal Model Control ◽  
Permeate Flux ◽  
Model Control

This paper presents a design of a data-driven-based neural network internal model control for a submerged membrane bioreactor (SMBR) with hollow fiber for microfiltration. The experiment design is performed for measurement of physical parameters from an actuator input (permeate pump voltage), which gives the information (outputs) of permeate flux and trans-membrane pressure (TMP). The palm oil mill effluent is used as an influent preparation to depict fouling phenomenon in the membrane filtration process. From the experiment, membrane fouling potential is observed from flux decline pattern, with a rapid increment of TMP (above 200 mbar). Membrane fouling is a complex process and the available models in literature are not designed for control system (filtration performance). Therefore, this work proposes an aeration fouling control strategy to measure the filtration performance. The artificial neural networks (Feed-Forward Neural Network—FFNN, Radial Basis Function Neural Network—RBFNN and Nonlinear Autoregressive Exogenous Neural Network—NARXNN) are used to model dynamic behaviour of flux and TMP. In this case, only flux is used in closed loop control application, whereby the TMP effect is used for monitoring. The simulation results show that reliable prediction of membrane fouling potential is obtained. It can be observed that almost all the artificial neural network (ANN) models have similar shape with the actual data set, with the highest accuracy of more than 90% for both RBFNN and NARXN. The RBFNN is preferable due to simple structure of the network. In the control system, the RBFNN IMC depicts the highest closed loop performance with only 3.75 s (settling time) for setpoint changes when compared with other controllers. In addition, it showed fast performance in disturbance rejection with less overshoot. In conclusion, among the different neural network tested configurations the one based on radial basis function provides the best performance with respect to prediction as well as control performance.

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