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This work is based on the application of Cohen-Coon and Zeigler-Nichols tuning techniques using proportional (P), proportional-integral (PI) and proportional-integral-derivative (PID) controllers to the control of a reactive distillation process used for the production of methyl oleate, which is a fatty acid methyl ester, produced from the esterification reaction between oleic acid and methanol. The model used for the study was obtained from literature and formulated in Simulink environment of MATLAB. Before embarking on the control study, the open-loop dynamics of the system was first studied by applying a step to its input variable. Furthermore, the closed-loop dynamic simulation was accomplished by applying a step to the set-point of the controlled variable of the system. From the results obtained, it was discovered that the obtained model of the process was a stable one because it was able to get settled within the simulation time considered. Also, the closed-loop results obtained from the simulation revealed that the process was successfully controlled using PID controllers tuned with the techniques because they (the controllers) made the system to behave as it was desired, even though there was a normal offset in the case of P-only controller.
With the limited availability of conventional petroleum diesel and, also, as a result of environmental concerns, fatty acid methyl Ester, otherwise known as biodiesel, which is an alternative fuel, is currently receiving attention in both academic and industrial research. This material can be used to replace petroleum diesel without any modification because their properties are similar (Simasatitkul et al., 2011; Giwa et al., 2014; Giwa et al., 2015a; Giwa et al., 2015c). Biodiesel is defined as the mono-alkyl esters of long chain fatty acids derived from oils and fats by transesterification of vegetable oils using alcohol in presence of catalyst that conforms to ASTM D-6159 specifications (Cherng-Yuan and Jung-Chi, 2010; Kapilan et al., 2009).
Biodiesel has similar fuel properties to diesel and, therefore, it can be used as a substitute for diesel fuel, either in neat form or in blends with petroleum diesel (Pasias et al., 2006). The fuel has the following advantages over petroleum-based diesel: it is renewable, carbon neutral, more rapidly biodegradable, less toxic, has a higher flash point and low sulphur content. The use of straight vegetable oils (SVO) in energy production processes has been studied, but in the last three decades, renewed interest in biodiesel has re-instigated the research into vegetable oils science and engineering which established that biodiesel is a possible substitute or supplement to mineral diesel for engine and other applications.
There are different technologies available for the production of biodiesel and many more are expected to emerge in the near future. The most widely used method worldwide, however, remains transesterification process to form an alkyl-ester of the fatty acid along with glycerol as a by-product of the reaction. Various techniques of biodiesel production
are available today. These are catalytic (Lin et al., 2009; Hou et al., 2007), enzymatic (Hama et al., 2008), reactive distillation (Simasatitkul et al., 2011) and non-catalytic techniques (Diasakou et al., 1998; Kusdiana and Saka, 2001; He et al., 2007). Catalytic technique is commonly used in the industrial sectors.
The transesterification global reaction process is normally a sequence of three consecutive reversible reactions. The triglycerides are converted step by step in diglycerides, monoglycerides and finally in glycerol. One fatty acid ester molecule is produced at each step (Marchetti et al., 2007). The performance of the transesterification is affected by multiple parameters, such as molar ratio of alcohol:vegetable oil, type and quantity of catalyst, reaction time, reaction temperature, feedstock properties and mixer intensity. Usually, an alcohol in excess is used for driving the reaction equilibrium towards the product side. This alcohol excess must be recovered in order to reutilize it and, furthermore, purify the biodiesel. The alcohol recovery process is generally carried out by distillation process, thus, the energy consumption, operating costs, equipment number and the production time increase. This is the reason why it is better to employ a novel process known as reactive distillation in this production of biodiesel.
Reactive Distillation (RD) belongs to the so-called “process-intensification technologies” (Michael Sakuth et al. 2003). It may be advantageous for liquid-phase reaction systems when the reaction must be carried out with a large excess of one or more of the reactants, when a reaction can be driven to completion by removal of one or more of the products as they are formed, or when the product recovery or by-product recycle scheme is complicated or made infeasible by azeotrope formation (Perry et al., 1997).
It is more advantageous than a conventional process with separate reaction and separation sections owing to the following advantages that include low reduced investment and operating costs as a result of increased yield of a reversible reaction that is due to the separation of the desired product from the reaction mixture (Pérez-Correa et al., 2008; Giwa and Giwa, 2015), high conversion, improved selectivity, low energy consumption, ability to carry out difficult separations and avoidance of azeotropes (Jana and Adari, 2009; Giwa, 2012; Giwa and Giwa, 2012; Giwa and Giwa, 2015).
The RD process has less separation steps, produces no waste salt streams as water is the only by-product, and could use a part of the produced biodiesel as source of energy. The low residence time of the liquid phase inside the RD column (20–60 min) requires a highly active catalyst. A RD column has some hydraulic constrains that limit the maximum residence time. In addition, the production rate is increased when the residence time is short (Anton et al., 2006). However, no mixing devices are used in distillation columns and typically any moving part is avoided in chemical industry due to the increased energy consumption and higher maintenance costs. (Anton et al., 2006).
Model can be defined scientifically as "A mathematical or physical system, obeying certain specified conditions, whose behaviour is used to understand a physical, biological, or social system to which it is analogous in some way." A working definition of process model is a set of equations (including the necessary input data to solve the equations) that allows us to predict the behaviour of a chemical process. Models play a very important role in control-system design. Models can be used to simulate expected process behaviour with a proposed control system. Also, models are often "embedded"
in the controller itself; in effect the controller can use a process model to anticipate the effect of a control action.
The term process dynamics refers to unsteady-state (or transient) process behaviour. By contrast, most of the chemical engineers’ curricula emphasize steady-state and equilibrium conditions such courses as material and energy balance, thermodynamics, and transport phenomena. But process dynamics are also very important. Transient operation occurs during important situations such as start-ups and shut-downs, un-usual process disturbances, planned transitions from one product grade to another.
The primary objective of process control is to maintain a process at the desire operation conditions safely and efficiently, while satisfying environmental and product quality requirements. The subject of process control is concerned on how to achieve these goals. In large-scale, integrated processing plants such as oil refineries or ethylene plants, thousands of process variables such as compositions, temperatures and pressures are measured and must be controlled.
In order to design a controller, then, we need to know whether an increase in the manipulated input increases or decreases the process output variable; that is, we need to know whether the process gain is positive or negative.
In recent years the performance requirements for process plants have become increasingly difficult to satisfy. Stronger competition, tougher environmental and safety regulations, and rapidly changing economic conditions have been key factors in tightening product quality specification. A further complication is that modern plants
have become more difficult to operate because of the trend towards complex and high integrated processes. For such plant, it is difficult to prevent disturbances from propagating from one unit to other interconnected units.
In view of the increased emphasis placed on safe, efficient plant operation, it is only natural that the subject process control has been increasingly important in recent years. Without computer-based process control systems it would be impossible to operate modern plants safely and profitably while satisfying products quality and environmental requirements. Thus, it is important chemical engineers to have an understanding of both the theory and practice of control.
This research project is aimed at applying proportional-integral-derivative control to the control of a process used for the production of a fatty acid methyl ester.
1.2 Problem Statement
One of the problems facing chemical process industries producing fatty acid methyl ester is low purity, in terms of mole fraction, of the desired product. There is the need to look for a way to tackle this problem so that the future of biodiesel can be guaranteed.
The successful completion of this project will provide a control algorithm that can be used to handle any fatty acid methyl ester reactive distillation process for the purpose of obtaining high mole fraction of the desired FAME.
1.4 Scope of study
This work is limited to using MATLAB/Simulink to develop a model, simulate the model and apply PID control algorithms tuned with Cohen-Coon and Ziegler-Nichols techniques to the model of the reactive distillation process used for the production of methyl oleate.
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