A New MIMO ANFIS-PSO Based NARMA-L2 Controller for nonlinear dynamic systems

The corresponding author is grateful to the Iraqi Ministry of Higher Education and Scientific Research for supporting the current research

Inferential active disturbance rejection control of distillation columns

PhD ThesisThe distillation column is an important processing unit in the chemical and oil refining industry. Distillation is the most widely employed separation method in the world’s oil plants, chemical and petrochemical industrial facilities. The main drawback of the technique is high energy consumption, which leads to high production costs. Therefore, distillation columns are required to be controlled close to the desired steady state conditions because of economic incentives. Most industrial distillation columns are currently controlled by conventional multi-loop controllers such as proportional-integral-derivative (PID) controllers, which have several shortcomings such as difficulty coping with sudden set-point jumps, complications due to the integral term (I), and performance degradation due to the effect of noise on the derivative term (D). The control of ill-conditioned and strongly non-linear plants such as high purity distillation needs advanced control schemes for high control performance. This thesis investigates the use of active disturbance rejection control (ADRC) for product composition control in distillation columns. To the author’s knowledge, there are few reported applications of ADRC in the chemical industry. Most ADRC applications are in electrical, robotics and others. Therefore, this research will be the first to apply the ADRC scheme in a common chemical processing unit, and can be considered as a first contribution of this research. Initially, both PI and ADRC schemes are developed and implemented on the Wood–Berry distillation column transfer function model, on a simulated binary distillation column based on a detailed mechanistic model, and on a simulated heat integrated distillation column (HIDiC) based on a detailed mechanistic model. Process reaction curve method and system identification tools are used to obtain the 2×2 multi-input multi-output (MIMO) transfer function of both binary and HIDiC for the purpose of PI tuning where the biggest log-modulus tuning (BLT) method is used. Then, the control performance of ADRC is compared to that of the traditional PI control in terms of set-point tracking and disturbance rejection. The simulation result clearly indicates that the ADRC gives better control performance than PI control in all three case studies. The long time delay associated with product composition analysers in distillation columns such as gas chromatography deteriorates the overall control performance of the ADRC scheme. v To overcome this issue an inferential ADRC scheme is proposed and can be considered as a second contribution of this research. The tray temperatures of distillation columns are used to estimate both the top and bottom product compositions that are difficult to measure on-line without a time delay. Due to the strong correlation that exists in the tray temperature data, principal component regression (PCR) and partial least square (PLS) are used to build the soft sensors, which are then integrated into the ADRC. In order to overcome control offsets caused by the discrepancy between soft sensor estimation and actual compositions measurement, an intermittent mean updating technique is used to correct both the PCR and PLS model predictions. Furthermore, no significant differences were observed from the simulation results in the prediction errors reported by both PCR and PLS. The proposed inferential ADRC scheme shows effective and promising results in dealing with non-linear systems with a large measurement delay, where the ADRC has the ability to accommodate both internal uncertainties and external disturbances by treating the impact from both factors as total disturbances that will then be estimated using the extended state observer (ESO) and cancelled out by the control law. The inferential ADRC control scheme provides tighter product composition control that will lead to reduced energy consumption and hence increase the distillation profitability. A binary distillation column for separating a methanol–water mixture and an HIDiC for separating a benzene–toluene mixture are used to verify the developed inferential ADRC control scheme.Petroleum Development of Oman (PDO) for their generous support and scholarshi

Tuning of Distillation Column Control

Distillation column is one of the most important equipment in a chemical industry. It is quite a challenge to control both the composition of the bottom and top product without affecting the composition of one another. By designing a good controller and a good tuning for a controller, a distillation column can be controlled efficiently and a product with a high quality can be obtained. A few methods are applied in this project which is by first designing a controller which is a PID controller and a MPC controller. Once the designing of the controller is done, an algorithm is developed to make sure that the tuning of distillation column control can be done efficiently. Then, the controller tuning setting is tested using matlab and the result of each approach is compared and the best result is selected to control the distillation column. Lastly, a performance evaluation is done in order to make sure that the controller tuning does not damage the valve. Therefore, by studying on tuning of distillation column control the composition of the bottom and the top product can be control and the product of a distillation column can be obtain according to the desired valu

Design of Decoupler and Performance Analysis of A Distillation Column

The main aim of this thesis is to control the basic parameters of distillation column .The distillation column is basically a MIMO process that means all the inputs and outputs are coupled to each other. It is very difficult to control such type of process so, we have to reduce or eliminate the interaction between the inputs and outputs. Therefore the process can be converted to a single input and single output system (SISO).In order to convert the MIMO system to SISO system it is necessary to design a decoupler which will eliminate the interaction among all the inputs and outputs.My focus is here to design that decoupler, which is very difficult to design when the process variables are more. It is easy when we consider TITO system. When we consider a ‘three input and three input’ and ‘four input and four output’ system it is necessary to follow some methods like RGA and RNGA methods. After getting those parameters we have to follow the ETF method so that the decoupler will be designed. After designing the decoupler, our aim to be controlled the distillation process. Here I am using PID controller to control the process. In order to design the PID controller we basically emphasized on the tuning parameters of the PID. To get the tuning parameters we must follow certain methods such as Ziegler Nichols, Cohen coon and decentralized relay feedback methods, BLT methods etc. Here we are using decentralized relay feedback method in to do the tuning of the controller. After tuned the PID .We will get the desired output what we actually want to get.The result was obtained and shown that implemented work is successfully done. Finally the interactions are rejected and the process was controlled.Here all the simulations are done by the MATLAB tool and Microsoft window 7operating syste

Energy efficient control and optimisation techniques for distillation processes

PhD ThesisDistillation unit is one of the most energy intensive processes and is among the major CO2 emitter in the chemical and petrochemical industries. In the quest to reduce the energy consumption and hence the environmental implications of unutilised energy, there is a strong motivation for energy saving procedures for conventional columns. Several attempts have been made to redesign and heat integrate distillation column with the aim of reducing the energy consumption of the column. Most of these attempts often involve additional capital costs in implementing. Also a number of works on applying the second law of thermodynamics to distillation column are focused on quantifying the efficiency of the column. This research aims at developing techniques of increasing the energy efficiency of the distillation column with the application of second law using the tools of advanced control and optimisation. Rigorous model from the fundamental equations and data driven models using Artificial neural network (ANN) and numerical methods (PLS, PCR, MLR) of a number of distillation columns are developed. The data for the data driven models are generated from HYSYS simulation. This research presents techniques for selecting energy efficient control structure for distillation processes. Relative gain array (RGA) and relative exergy array (REA ) were used in the selection of appropriate distillation control structures. The viability of the selected control scheme in the steady state is further validated by the dynamic simulation in responses to various process disturbances and operating condition changes. The technique is demonstrated on two binary distillation systems. In addition, presented in this thesis is optimisation procedures based on second law analysis aimed at minimising the inefficiencies of the columns without compromising the qualities of the products. ANN and Bootstrap aggregated neural network (BANN) models of exergy efficiency were developed. BANN enhances model prediction accuracy and also provides model prediction confidence bounds. The objective of the optimisation is to maximise the exergy efficiency of the column. To improve the reliability of the optimisation strategy, a modified objective function incorporating model prediction confidence bounds was presented. Multiobjective optimisation was also explored. Product quality constraints introduce a measure of penalization on the optimisation result to give as close as possible to what obtains in reality. The optimisation strategies developed were applied to binary systems, multicomponents system, and crude distillation system. The crude distillation system was fully explored with emphasis on the preflash unit, atmospheric distillation system (ADU) and vacuum distillation system (VDU). This study shows that BANN models result in greater model accuracy and more robust models. The proposed ii techniques also significantly improve the second law efficiency of the system with an additional economic advantage. The method can aid in the operation and design of energy efficient column.Commonwealth scholarship commissio

Simulation Study on Operations Aspects of a Reactive Distillation Column for Production ofEthyl Acetate Using ASPEN PLUS™ and ASPEN DYNAMIC™

Ethyl acetate is a widely used organic compound in manufacturing of printing inks, paints, coatings, perfume, film, food additives, pharmaceutical and others due to its low boiling point. There were numerous research carried out in different areas related with ethyl acetate production. In recent years, due to the increasing trend in ethyl acetate demand, reactive distillation that combined reaction process and distillation process technique has been used for ethyl acetate production studies. However, most of the researchers focus on column configuration and control of the column. There are limited studies being carried out on starting up a reactive distillation column in dynamic simulation

Fault tolerant control system design for distillation processes

PhD ThesisThe complexity and sophistication of modern control systems deployed in the re nery operation, particularly the crude distillation unit as a result of increasing demand for higher performance and improved safety, are on the increase. This growing complexity comes with some level of vulnerabilities, part of which is the potential failure in some of the components that make up the control system, such as actuators and sensors. The interplay between these components and the control system needs to have some built-in robustness in the face of actuator and sensor faults, to guarantee higher reliability and improved safety of the control system and the plant respectively, which is fundamental to the economy and operation of the system. This thesis focuses on the application of frugally designed fault tolerant control systems (FTCS) with automatic actuator and sensor faults containment capabilities on distillation processes, particularly atmospheric crude distillation unit. A simple active actuator FTCS that used backup feedback signal, switchable references and restructurable PID controllers was designed and implemented on three distillation processes with varying complexities { methanol-water separation column, the benchmark Shell heavy oil fractionator, and an interactive dynamic crude distillation unit (CDU) to accommodate actuator faults. The fault detection and diagnosis (FDD) component of the actuator FTCS used dynamic principal component analysis (DPCA), a data-based fault diagnostic technique, because of its simplicity and ability to handle large amount of correlated process measurements. The recon gurable structure of the PID controllers was achieved using relative gain array (RGA) and dynamic RGA system interaction analysis tools for possible inputs { outputs pairing with and without the occurrence of actuator faults. The interactive dynamic simulation of CDU was developed in HYSYS and integrated with MATLAB application through which the FDD and the actuator FTCS were implemented. The proposed actuator FTCS is proved being very e ective in accommodating actuator faults in cases where there are suitable inputs { outputs pairing after occurrence of an actuator fault. Fault tolerant inferential controller (FTIC) was also designed and implemented on a binary distillation column and an interactive atmospheric CDU to accommodate sensor faults related to the controlled variables. The FTIC used dynamic partial least squared (DPLS) and dynamic principal component regression (DPCR) based soft sensor techniques to provide redundant controlled variable estimates, which are then used in place of faulty sensor outputs in the feedback loops to accommodate sensor faults and maintain the integrity of the entire control system. Implementation issues arising from the e ects of a sensor fault on the secondary variables used for soft sensor estimation were addressed and the approach was shown to be very e ective in accommodating all the sensor faults investigated in the distillation units. The actuator FTCS and the FTIC were then integrated with the DPCA FDD scheme to form a complete FTCS capable of accommodating successive actuator and sensor faults in the distillation processes investigated. The simulation results demonstrated the e ectiveness of the proposed approach. Lastly, fault tolerant model predictive control (FTMPC) with restructurable inputs { outputs pairing in the presence of actuator faults based on preassessed recon gurable control structures was proposed, and implemented on an interactive dynamic CDU. The FTMPC system used a rst order plus dead time (FOPDT) model of the plant for output prediction and RGA and DRGA tools to analyse possible control structure recon guration. The strategy helped improve the availability and performance of control systems in the presence of actuator faults, and can ultimately help prevent avoidable potential disasters in the re nery operation with improved bottom line { Pro t. Overall, the proposed approaches are shown to be e ective in handling actuator and sensor faults, when there are suitable manipulated variables and redundant analytical signals that could be used to contain the e ects of the faults on the system.University of Lagos, Nigeria & Petroleum Technology Development Fund (PTDF) for the Scholarship award at the later stage of my research programme

Tuning of Distillation Column Control

Distillation column is one of the most important equipment in a chemical industry. It is quite a challenge to control both the composition of the bottom and top product without affecting the composition of one another. By designing a good controller and a good tuning for a controller, a distillation column can be controlled efficiently and a product with a high quality can be obtained. A few methods are applied in this project which is by first designing a controller which is a PID controller and a MPC controller. Once the designing of the controller is done, an algorithm is developed to make sure that the tuning of distillation column control can be done efficiently. Then, the controller tuning setting is tested using matlab and the result of each approach is compared and the best result is selected to control the distillation column. Lastly, a performance evaluation is done in order to make sure that the controller tuning does not damage the valve. Therefore, by studying on tuning of distillation column control the composition of the bottom and the top product can be control and the product of a distillation column can be obtain according to the desired valu