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- Process Systems Analysis Control
- Process System Analysis and Control – Donald R. Coughanowr – 2nd Edition
- Process systems analysis and control
- PROCESS SYSTEMS ANALYSIS AND CONTROL, 2nd edition by D. Coughanowr
Process Systems Analysis Control
Log In Sign Up. Download Free PDF. Mahmood Saeed. Download PDF. A short summary of this paper. It is intended to be not a comprehensive treatise on process control, but rather a textbook that provides students with the tools to learn the basic material and be in a position to continue their studies in the area if they so choose. Students are expected to have a background in mathematics through differential equations, material and energy balance concepts, and unit operations.
After the fi rst 13 chapters, the instructor may select from the remaining chapters to fi t a course of particular duration and scope. A typical one-semester week course, for example, may include Chapters 1 through 19 and As competition becomes stiffer in the chemical marketplace and processes become more complicated to operate, it is advantageous to make use of some form of automatic control. A common example of a control system from everyday life is the cruise control on an automobile.
The purpose of a cruise control is to maintain the speed of the vehicle the controlled variable at the desired value the set point despite variations in terrain, hills, etc. Another common example is the home hot water heater.
The control system on the hot water heater attempts to maintain the temperature in the tank at the desired value by manipulating the fuel flow to the burner for a gas heater or the electrical input to the heater in the face of disturbances such as the varying demand on the heater early in the morning, as it is called upon to provide water for the daily showers.
A third example is the home thermostat. This control system is designed to maintain the temperature in the home at a comfortable value by manipulating the fuel flow or electrical input to the furnace.
The furnace control system must deal with a variety of disturbances to maintain temperature in the house, such as heat losses, doors being opened and hopefully closed, and leaky inefficient windows. The furnace must also be able to respond to a request to raise the desired temperature if necessary. The controller compares the measurement signal of the controlled variable to the set point the desired value of the controlled variable.
The difference between the two values is called the error. The concept of using information about the deviation of the system from its desired state to control the system is called feedback control. Information about the state of the system is "fed back" to a controller, which utilizes this information to change the system in some way.
The type of control system shown in Fig. Closed-loop refers to the fact that the controller automatically acts to return the controlled variable to its desired value. In contrast, an open-loop system would have the measurement signal disconnected from the controller, and the controller output would have to be manually adjusted to change the value of the controlled variable. An open-loop system is sometimes said to be in manual mode as opposed to automatic mode closed-loop.
Negative feedback is the most common type of signal feedback. Negative refers to the fact that the error signal is computed from the difference between the set point and the measured signal. The negative value of the measured signal is "fed back" to the controller and added to the set point to compute the error. Example 1. Hot water tank control system. As a specific example, let us consider a hot water heater for a home and examine its control system, using the same type of diagram Fig.
The thermocouple measures the temperature of the water in the tank and sends a signal to the thermostat indicating the temperature. Disturbances to the system, which decrease the temperature of the water in the tank, include ambient heat losses and hot water demand by the household which is replaced with a cold water feed. Depending on the value of the error signal, the output from the controller is Many other types of controllers that we will study can modulate their output based on the magnitude of the error signal, how long the error signal has persisted, and even how rapidly the error appears to be changing.
Clearly, the larger the error, the less we are satisfied with the present state of affairs and vice versa. In fact, we are completely satisfied only when the error is exactly zero. Based on these considerations, it is natural to suggest that the controller should change the heat input by an amount proportional to the error. This is called proportional control. In effect, the controller is instructed to maintain the heat input at the steadystate design value as long as the error is zero.
If the tank temperature deviates from the set point, causing an error, the controller is to use the magnitude of the error to change the heat input proportionally. We shall reserve the right to vary the proportionality constant to suit our needs.
This degree of freedom forms a part of our instructions to the controller. As we will see shortly during the course of our studies, the larger we make the proportionality constant for the proportional controller called the controller gain , the smaller the steady-state error will become.
We will also see that it is impossible to completely eliminate the error through the use of a proportional controller. There will always be some residual steadystate error called offset. For a home water heater, this is probably good enough; the exact temperature is not that critical.
In an industrial process, this may not be adequate, and we have to resort to a bit more complicated controller to drive the error to zero. Considerable improvement may be obtained over proportional control by adding integral control. The controller is now instructed to change the heat input by an additional amount proportional to the time integral of the error.
This type of control system has two adjustable parameters: a multiplier for the error and a multiplier for the integral of the error.
If this type of controller is used, the steady-state error will be zero. From this standpoint, the response is clearly superior to that of the system with proportional control only. One price we pay for this improvement is the tendency for the system to be more oscillatory. The system will tend to overshoot its final steady-state value before slowly settling out at the desired set point. So what is the best control system to use for a particular application? This and related questions will be addressed in subsequent chapters.
Some Further ComplicationsAt this point, it would appear that the problem has been solved in some sense. A little further probing will shatter this illusion. It has been assumed that the controller receives instantaneous information about the tank temperature. From a physical standpoint, some measuring device such as a thermocouple will be required to measure this temperature. The temperature of a thermocouple inserted in the tank may or may not be the same as the temperature of the fluid in the tank.
This can be demonstrated by placing a mercury thermometer in a beaker of hot water. The thermometer does not instantaneously rise to the water temperature. Rather, it takes a bit of time to respond. Since the controller will receive measured values of the temperature, rather than the actual values, it will be acting upon the apparent error, rather than the actual error.
The effect of the thermocouple delay in transmission of the temperature to the controller is primarily to make the response of the system somewhat more oscillatory than if the response were instantaneous. If we increase the controller gain the proportionality constants , the tank temperature will eventually oscillate with increasing amplitude and will continue to do so until the physical limitations of the heating system are reached. In this case, the control system has actually caused a deterioration in performance, and this type of reponse is referred to as an unstable response.
This problem of stability of response will be a major concern for obvious reasons. At present, it is sufficient to note that extreme care must be exercised in specifying control systems. In the case considered, the proportional and integral controllers described above will perform satisfactorily if the gain is kept lower than some particular value. However, it is not difficult to construct examples of systems for which the addition of any amount of integral control will cause an unstable response.
Since integral control usually has the desirable feature of eliminating steady-state error, it is extremely important that we develop means for predicting the occurrence of unstable response in the design of any control system. Block DiagramA good overall picture of the relationships among variables in the heated-tank control system may be obtained by preparing a block diagram as shown in Fig. It indicates the flow of information around the control system and the function of each part of the system.
Much more will be said about block diagrams later, but the reader can undoubtedly form a good intuitive notion about them by comparing Fig.
Particularly significant is the fact that each component of the system is represented by a block, with little regard for the actual physical characteristics of the represented component e. The major interest is in 1 the relationship between the signals entering and leaving the block and 2 the manner in which information flows around the system.
Two process streams are mixed to produce one of the feeds for our chemical reactor. After mixing, the blended stream is fed to a heating vessel before being sent to the reactor. The process is running along at steady state. At P. The new operator on our unit misreads the flowmeters for the process and switches the flow rates of the two streams. Use your knowledge of chemical engineering to determine what has happened to the exit concentration from the heating vessel over the first half-hour of the shift.
We can model the mixing tee and the blending tank using an unsteady-state mass balance to predict the behavior of this part of the process since the shift change and the unfortunate error by the new operator. So, what we know of the situation is shown in Fig. To analyze how the exit from the heating vessel the feed to the reactor varies with time, we must perform an unsteady mass balance on component A around the heating vessel. Thus the volume of fluid in the tank V is constant.
Transient periodA plot of the exit concentration from the heating vessel is shown in Fig. Modeling the mixing process enables us to determine the concentration of component A in the stream being fed to the reactor. Being able to determine or predict the dynamic behavior of a process is crucial to being able to design a control system for it.
As another modeling example, consider the energy balance for the mixing process described above. Prior to 3 P. Before we look at the effect of the disturbance caused by the operator, it is necessary to determine the steady-state process conditions prior to the upset.
Process System Analysis and Control – Donald R. Coughanowr – 2nd Edition
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OBJECTIVES AND USES OF THE TEXTThis text is intended for use in an introductory one-semester-long undergraduate process dynamics and control course.
Process systems analysis and control
The new problems are a mixture of hand-solutions and computational-exercises. One-page capsule summaries have been added to the end of each chapter to help students review and study the most important concepts in each chapter. Read more
Process Systems Analysis and Control download for free Process Systems Analysis and Control, third edition retains the clarity of presentation for which this book is well known. It is an ideal teaching and learning tool for a semester-long undergraduate chemical engineering course in process dynamics and control. It avoids the encyclopedic approach of many other texts on this topic.
PROCESS SYSTEMS ANALYSIS AND CONTROL, 2nd edition by D. Coughanowr
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