Control loops process variables

Instrument Loop-A combination of one or more interconnected instruments arranged to measure or control a process variable. 

On some control loops, a variable-speed drive on a pump, fan, or blower may be used as the final element connecting the controller output to the process. Variable-speed drives provide fast and linear response with little or no hysteresis and are therefore an excellent choice with respect to control performance. As the initial cost of variable-speed drives continues to decrease, their use should become a more widespread practice. 

Corripio reviewed the two-point Smith method for characterizing the open-loop process variable response to a step change in controller output by an apparent dead time, ADT, and an apparent first-order time constant, TFO. The two data points on the process variable response curve are taken at... 

The decision to include a process control computer must be made when the project scope is defined. Measurements are required for production loop, operator guidance, material balances, energy balances, and closed loop control of process variables. These measurements must be completely defined and specified. 

A loop is a combination of a number of items of equipment interconnected to measure and/or control a process variable. A list of loops, with the definition of their contents, interfaces and limits is prepared as part of the engineering design process. A prerequisite to functional testing of the loop is that ... 

Many misconceptions exist about cascade control loops and their purpose. For example, many engineers specify a level-flow cascade for every level control situation. However, if the level controller is tightly tuned, the out-flow bounces around as does the level, regardless of whether the level controller output goes direcdy to a valve or to the setpoint of a flow controller. The secondary controller does not, in itself, smooth the outflow. In fact, the flow controller may actually cause control difficulties because it adds another time constant to the primary control loop, makes the proper functioning of the primary control loop dependent on two process variables rather than one, and requites two properly tuned controllers rather than one to function properly. However, as pointed out previously, the flow controller compensates for the effect of the upstream and downstream pressure variations and, in that respect, improves the performance of the primary control loop. Therefore, such a level-flow cascade may often be justified, but not for the smoothing of out-flow. 

A closed-loop system uses the measurement of one or more process variables to move the manipulated variable to achieve control. Closed-loop systems may include reedfoi ward, feedback, or both. 

Feedback Control In a feedback control loop, the controlled variable is compared to the set point R, with the difference, deviation, or error e acted upon by the controller to move m in such a way as to minimize the error. This ac tion is specifically negative feedback, in that an increase in deviation moves m so as to decrease the deviation. (Positive feedback would cause the deviation to expand rather than diminish and therefore does not regulate.) The action of the controller is selectable to allow use on process gains of both signs. 

Strong process interacHons can cause serious problems if a conventional multiloop feedback control scheme (e g., PI or PID controllers) is employed. The process interacHons canproduce undesirable control loop interac tions where the controllers fight each other. Also, it may be difficult to determine the best pairing of controlled and manipulated variables. For example, in the in-hne blending process in Fig. 8-40(<7), should w be controlled with and x with tt>g, or vice versa ... 

The selection of controlled and manipulated variables is of crucial importance in designing a control system. In particular, a judicious choice may significantly reduce control loop interactions. For the blending process in Fig. 8-40(d ), a straightforward control strategy would be to control x by adjusting w, and w by adjusting Wg. But... 

In principle, ideal decouphng eliminates control loop interactions and allows the closed-loop system to behave as a set of independent control loops. But in practice, this ideal behavior is not attained for a variety of reasons, including imperfect process models and the presence of saturation constraints on controller outputs and manipulated variables. Furthermore, the ideal decoupler design equations in (8-52) and (8-53) may not be physically realizable andthus would have to be approximated. 

Basic process control system (BPCS) loops are needed to control operating parameters like reactor temperature and pressure. This involves monitoring and manipulation of process variables. The batch process, however, is discontinuous. This adds a new dimension to batch control because of frequent start-ups and shutdowns. During these transient states, control-tuning parameters such as controller gain may have to be adjusted for optimum dynamic response. 

New research advances in control theory that are bringing it closer to practical problems are promising dramatic new developments and attracting widespread industrial interest. One of these advances is the development of "robust" systems. A robust control system is a stable, closed-loop system that can operate successfully even if the model on which it is based does not adequately describe the plant. A second advance is the use of powerful semiempirical formalisms in control problems, particularly where the range of possible process variables is constrained. 

The components of the basic feedback control loop, combining the process and the controller can be best understood using a generalised block diagram (Fig. 2.29). The information on the measured variable, temperature, taken from the system is used to manipulate the flow rate of the cooling water in order to keep the temperature at the desired constant value, or setpoint. This is illustrated by the simulation example TEMPCONT, Sec. 5.7.1. 

Instruments are provided to monitor the key process variables during plant operation. They may be incorporated in automatic control loops, or used for the manual monitoring of the process operation. They may also be part of an automatic computer data logging system. Instruments monitoring critical process variables will be fitted with automatic alarms to alert the operators to critical and hazardous situations. 

It is desirable that the process variable to be monitored be measured directly often, however, this is impractical and some dependent variable, that is easier to measure, is monitored in its place. For example, in the control of distillation columns the continuous, on-line, analysis of the overhead product is desirable but difficult and expensive to achieve reliably, so temperature is often monitored as an indication of composition. The temperature instrument may form part of a control loop controlling, say, reflux flow with the composition of the overheads checked frequently by sampling and laboratory analysis. 

Identify the key process variables that need to be controlled to achieve the specified product quality. Include control loops using direct measurement of the controlled variable, where possible if not practicable, select a suitable dependent variable. 

Feedback is information in a closed-loop control system about the condition of a process variable. This variable is compared with a desired condition to produce the proper control action on the process. Information is continually "fed back" to the control circuit in response to control action. In the previous example, the actual storage tank water level, sensed by the level transmitter, is feedback to the level controller. This feedback is compared with a desired level to produce the required control action that will position the level control as needed to maintain the desired level. Figure 3 shows this relationship. 

An automatic control system is a preset closed-loop control system that requires no operator action. This assumes the process remains in the normal range for the control system. An automatic control system has two process variables associated with it a controlled variable and a manipulated variable. 

Feedback is information in a closed-loop control system about the condition of a process variable. 

Control loops can be either stable or unstable. Instability is caused by a combination of process time lags discussed earlier (i.e., capacitance, resistance, and transport time) and inherent time lags within a control system. This results in slow response to changes in the controlled variable. Consequently, the controlled variable will continuously cycle around the setpoint value. 

Controllers are the controlling element of a control loop. Their function is to maintain a process variable (pressure, temperature, level, etc.) at some desired value. This value may or may not be constant. 

We will consider all the components of this temperature control loop in more detail later in this book. For now we need only appreciate the fact that the automatic control of some variable in a process requires the installation of a sensor, a transmitter, a controller, and a final control element (usually a control valve). Most of this book is aimed at learning how to decide what type of controller should be used and how it should be tuned, i.e., how should the adjustable tuning parameters in the controller be set so that we do a good job of controlling temperature. 

The interface with the process at the other end of the control loop is made by the final control element. In a vast majority of chemical engineering processes the final control element is an automatic control valve which throttles the flow of a manipulated variable. Most control valves consist of a plug on the end of a stem that opens or closes an orifice opening as the stem is raised or lowered. As sketched in Fig. 7.5, the stem is attached to a diaphragm that is driven by changing air pressure above the diaphragm. The force of the air pressure is opposed by a spring. 

The basic reason for using different control-valve trims is to keep the stability of the control loop fairly constant over a wide range of flows. Linear-trim valves are used, for example, when the pressure drop over the control valve is fairly constant and a linear relationship exists between the controlled variable and the flow rate of the manipulated variable. Consider the flow of steam from a constant-pressure supply header. The steam flows into the shell side of a heat exchanger. A process liquid stream flows through the tube side and is heated by the steam. There is a linear relationship between the process outlet temperature and steam flow (with constant process flow rate and inlet temperature) since every pound of steam provides a certain amount of heat. 

The job of most control loops in a chemical process is one of regulation or load rejection, i.e., holding the controlled variable at its setpoint in the face of load... 

There are situations where the control loop should be aware of more than just one controlled variable. This is particularly true in highly automated plants where the operator cannot be expected to make all the decisions that must be made under abnormal conditions. This includes the startup and shutdown of the process. 

Of). The initial response of tiw output variable is in the opposite direction to where it eventually ends up. Thus the process starts out in the wrong direction. You can imagine what this sort of behavior would do to a poor feedback controller in such a loop. We will show quantitatively how inverse response degrades control-loop performance. 

Model predictive control is concerned with continuous feedback of information with the objective of reducing the variability of product quality by changing the set points (narrowing the range) in a plant control loop." By nsing model predictive control, projections on batch quality can be made and midstream corrections made to keep a batch within the target limits of the process. 

A closed-loop system with feedback, which is illustrated in Figure 13.2, is the central feature of a control system in bioprocess control, as well as in other processing industries. First, a set-point is established for a process variable. Then, the process variable measured in a bioreactor is compared with the set-point value to determine a deviation e. Based on the deviation, a controller uses an algorithm to calculate an output signal O that determines a control action to manipulate a control variable. By repeating this cycle during operation, successful process control is performed. The controller can be the operator when manual control is being employed. 

The original GC control system took the form of a central room which monitors the flowllne6, oil, water, and utility sections, plus a smaller satellite control room monitoring the gas compression and gas conditioning section of the plant. Closed loop process control, such as separator liquid level, pressure, flow and temperature control were handled by local pneumatic analog controllers. The key process variables are displayed in the control room via electronic instrumentation. All the key process and equipment trouble alarms are annunciated m the control rooms, plus the on/off status of key machinery and open/close status of key valves are displayed. 

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