This chapter is from the book
This chapter is from the book
This chapter is from the book
1.2 Instrumentation
The level-control problem detailed in Example 1.1 had three critical pieces of instrumentation: a sensor (measurement device), actuator (manipulated input device), and controller. The sensor measured the tank level, the actuator changed the flow rate, and the controller determined, on the basis of the sensor signal, how much to vary the actuator.
There are many common sensors used for chemical processes. These include temperature, level, pressure, flow, composition, and pH. The most common manipulated input is the valve actuator signal (usually pneumatic).
Each device in a control loop must supply or receive a signal from another device. When these signals are continuous, such as electrical current or voltage, we use the term analog. If the signals are communicated at discrete intervals of time, we use the term digital.
Analog
Analog or continuous signals provide the foundation for control theory and design and analysis. A common measurement device might supply either a 4- to 20-mA or 0- to 5-V signal as a function of time. Pneumatic analog controllers (developed primarily in the 1930s, but used in some plants today) use instrument air, as well as a bellows-and-springs arrangement, to “calculate” a controller output based on an input from a measurement device (typically supplied as a 3- to 15-psig pneumatic signal). The controller output of 3 to 15 psig is sent to an actuator, typically a control valve where the pneumatic signal moves the valve stem. For large valves, the 3- to 15-psig signal might be amplified to supply enough pressure to move the valve stem.
Electronic analog controllers typically receive a 4- to 20-mA or 0- to 5-V signal from a measurement device and use an electronic circuit to determine the controller output, which is usually a 4- to 20-mA or 0- to 5-V signal. Again, the controller output is often sent to a control valve that may require a 3- to 15-psig signal for valve stem actuation. In this case, the 4- to 20-mA current signal is converted to the 3- to 15-psig signal using an I/P (current-to-pneumatic) converter.
Digital
Most devices and controllers are now based on digital communication technology. A sensor may send a digital signal to a controller, which then does a discrete computation and sends a digital output to the actuator. Very often, the actuator is a valve, so there is usually a D/I (digital-to-electronic analog) converter involved. If the valve stem is moved by a pneumatic rather than electronic actuator, then an I/P converter may also be used.
Digital control-system design techniques explicitly account for the discrete (rather than continuous) nature of the control computations. If small sample times are used, the tuning and performance of the digital controllers is nearly equal to that of analog controllers, as shown in Chapter 8, “PID Controller Tuning.”
Wireless
The cost to run wiring between sensors, controllers, and actuators can be substantial. For noncritical applications, particularly for monitoring and infrequent actions, it can be desirable to use wireless systems. This has been done in household systems for years, with remote operation of garage doors and, more recently, lighting systems. A biomedical application that is studied several times in this text is automated insulin delivery for people with type 1 diabetes. Bluetooth is used to send signals from a glucose sensor to a smartphone or other control device and to an insulin pump. Similar methods are likely to be used on select chemical processes in the future.
Techniques Used in This Textbook
Most of the techniques used in this book are based on analog (continuous) control. Although many of the control computations performed on industrial processes are digital, the discrete sample time is usually small enough that virtually identical performance to analog control is obtained. Our understanding of chemical processes is based on ordinary differential equations, so it makes sense to continue to think of control in a continuous fashion. We find that controller tuning is much more intuitive in a continuous, rather than discrete, framework. In Chapter 17, “Summary,” we spend some time discussing techniques that are specific to digital control systems, namely model predictive control (MPC).