What is Automatic Control?
The American Automatic Control Council (AACC) promotes cooperation among the various segments of the automatic control community in the United States and represents the community to the world organization, the International Federation of Automatic Control (IFAC). But, what is automatic control?
A familiar example is the cruise controller on your car. You press the button and a computer program watches the speedometer and it automatically adjusts the accelerator pedal position to keep the car speed at the desired value. Another example is the automatic adjustment of the heating element power as wet clothes dry in the clothes dryer. The machine senses the dryness of the clothes, and reduces the heater power as the drying is completing. This saves energy, and prevents overheating, which extends the clothes life.
Control is the adjustment of some “knob” in response to some measure of desirability. Humans do it all the time. If the shower water too cold, we open the hot water valve to heat it up. If the chips are not salty enough, we shake some salt on them. If it is raining, we open the umbrella. If there is background noise we converse in a louder voice.
A common theme in all of this is that action is taken in response to something that is sensed. It is termed feedback, as it is in interactions between people. Automatic control is not a one-time adjustment, but a continual adjustment to keep something at a desired state.
Control is taking action to fix something, to regulate something, to make something come out in a desirable way. Biological beings do it, but when the control is done by a device built by humans, when it is performed autonomously by machine or computer, it is called automatic control. Simple feedback mechanisms have been built by humans for thousands of years, based on an intuitive understanding of how these devices behaved. It has been only in the past 125 years that some sort of shared understanding within a wide variety of devices and behaviors has fused into what is now called control theory. The theory is an abstraction that allows us to draw common themes out of myriad examples in both natural and man-made mechanisms.
Most automatic control is performed by computers, but there are four essential physical elements, which are parallel to those in the human way of taking action. One element in automatic control is the algorithm, usually implemented as a software program on a computer. Like our brain, the algorithm decides action. It dictates the calculations that are performed to decide how much adjustment is needed. A second element is the sensor. The control algorithm needs a sensor to observe (see, hear, feel, count) some variable that indicates quality, termed the Controlled Variable, or CV. In cruise control this is the speedometer value. The human parallel to sensors would be our eyes that sense visual things, skin nerves that sense touch and temperature, and ears that sense sounds. A third is the control element that closes the loop, the knob that is adjusted with the intention of causing a change in the CV value. In cruise control this is the accelerator pedal. In general it is termed the Manipulated Variable, or MV. In our bodies, the MV may be a muscle, for example. Finally, the fourth element in automatic control is the communication system that sends the sensed information to the computer, then transmits the output of the algorithm to the final element. In automatic control the communication system could be a wired or wireless network or point-to-point connection, but hydraulic, pneumatic or other signaling systems can be used. Also, signals can be digital (discretized) or analog (continuum). The human parallel is our nerve system that transmits the sensory data to the brain, then the action information to the muscles.
A fifth element can also be included in this discussion. This is not a physical thing, but it is also important. It is the desired value for the CV, the set point.
What is Automatically Controlled?
Just as muscles adjust our eyes to focus on objects, modern cameras largely focus themselves using a combination of small sensors (to gauge distance), motors (to move the lenses), and algorithms running on tiny computers (to make decisions about how to command the motors based on sensor inputs). Our bodies self-regulate themselves all the way from sweat to regulate overall temperature, down to the mechanisms in generating antibodies and regulating hormones. In fact, many diseases – including cancer and diabetes – can be cast as failures in our body ability to regulate itself.
A great boon of casting things this way is that the abstraction, the control theory, helps us use examples from our engineering world to attack diseases, and helps us to follow Nature’s examples to build new devices.
Control is all around us. When we travel, our mobile phones must switch from one tower to another. When should the switch happen, and to what tower? It is automatically decided. When pasteurizing milk we must heat it to the right temperature for a brief time then cool it back down. A computer watches the process and adjusts the steam and cooling valves. Anti-skid brake systems automatically pump the brakes to improve traction even if the driver holds the pedal fully pressed. Our radios lock onto a broadcast frequency. Our heating and air conditioning systems regulate the temperature of our living spaces even when doors to the outside are opened and closed, or when more people come into a room.
Control happens on a micro scale (within computer chips), and at a very large continental scale (regulating a national electricity transmission system). It happens in drilling (deep underground) or on exploration vehicles (way out in deep space). Train schedules, airplane flight and landing, automatic transmission shifting, broadcasting power, electrical generation, and purity of foods are all automatically controlled. As varied as all these examples are, at their core they are governed by the same principles, the same abstraction, and the same five elements. This is why the AACC is made up of folks from such different fields. We may apply control to widely differing devices, processes, systems, or procedures; but our understanding is all driven by similar aspects of the purpose.
Describing the Automatic Control Loop
Consider adjusting the temperature of a shower. The steps that we all take are to turn on the water, wait a moment, then sense the water temperature with our hand, decide if it is too hot, too cold, or just right, and then make some adjustment. We repeat this process until we are happy with the water temperature and can get into the shower. But, once it is set, other things happen that affect our comfort. For example, as the pipes in our house heat up, the water temperature may drift upward slightly, and we will sense the temperature rise and once again make an adjustment. When automated by machines, this ongoing process of measurement, comparison, adjustment is termed automatic control.
Entering from the left is the reference signal, or the desired set point value for the process or system. If this were describing the cruise control of a car, the reference would be the speed set point. The block “Compare” typically computes the difference between the measured response value and the set point, the actuating error. The block “Feedback Adjustment” decides what action is needed (it does the calculation), and sends this decision (about the right accelerator pedal position) to a device, “Actuate” (the vacuum operated levers and bellows) that makes the pedal position change. This action becomes the input (fuel flow rate) to the “Physical System” (engine and car) that causes its output (speed) to change. The “Measurement” device (the speedometer) senses the output and reports the value to the “Compare” operation.
In the earliest days of human built control systems, most of these functions were done via mechanical linkages, with floats or the effects of centrifugal acceleration providing sensing. The early 1900s saw the invention of the first electronics, which provided much greater opportunities for sensing, actuating, and decision making. Analog electronics opened the door to all sorts of systems (e.g. telephone, radio, television), including many control systems. Digital computers (what we simply call computers now) were invented in the late 1940s and early 1950s, and began commercial applications in process control in the late 50s. But, those were too slow and bulky for control systems work in aerospace applications. However, as the size of digital computers shrunk and their capabilities rose, they began to replace analog electronics. A watershed for this phenomenon was the Apollo program, in which NASA opted for the repeatability and reliability of computer control over the previous analog electronic control.
Today, most new control systems are built using digital computers. The elements of measurement, comparison, and actuation have not gone away, but have gotten more sophisticated. In fact, the continual push of this technology has opened the door to both more complex computer controlled systems, and many, many more simple computer controlled systems. From robots that clean our floors and mow our lawns to the future of self-driving cars and drones that deliver packages to our doorsteps, advances in small footprint computers as well as inexpensive sensor packages means that the number of autonomous machines that we interact with on a daily basis is about to shoot up dramatically. All of these machines rely on feedback control loops to make them operate safely, which means that there is a bit of control theory at the heart of each of these.
But not all is computerized! Watt’s fly-ball governor on a steam engine 150 years ago was one of the first examples of a sophisticated automatic control mechanism, and yet today’s farm and lawn tractors use similar mechanical devices for engine speed control.
Why Have Automatic Control?
An automatic control system never takes a break, never goes to sleep, and often works much faster than any human can. A computer can observe data from hundreds of sensors, and each thousands of times a second, and make that many adjustments that rapidly. However, with full attention, humans can only observe a few items, and each only a few times a second. The automation, whether it be in-flight navigation or in having a dryer shut itself off when it senses that clothes are dry, saves the human operator from having to constantly be there for the system. It frees the human to work at a higher level, knowing that the system is operating itself.
What Disciplines do Control?
Although these days control is mostly performed by computers, it is not just about computer science and control engineering. Automatic control interacts with a physical system, with the real world. To attempt to create a controller with no knowledge of the physical system is futile, naïve, and potentially dangerous. Thus, engineers who build control systems are often experts in the specific physical systems that they want to control. Aerospace engineers apply control to guidance systems. Biosystems engineers apply control to medical and farm operations. Chemical engineers need feedback control to run processes that make products as diverse as fuels, medicines, and nanoparticles. Electrical and mechanical engineers build control systems in a wide variety of systems including communications systems, robots, machinery, and wind turbines. Engineers and material scientists apply control to computer chip fabrication. Systems biologists apply the principles of feedback control and system theory to understand and model the complex networks of interaction and feedback in biological systems. While the abstract models for these different systems share a lot of similarity, the specific details of the physical problems have a lot to do with how the control systems are constructed.
Thus, control brings in disciplines of materials, mechanics, biology, chemistry, and electricity. Practically any scientific or engineering discipline—and most aspects of our personal and professional lives—have been or will be affected by automatic control.
To those that realize how enabled they are because of automatic control, “You’re welcome. We love what we do.”
May 2, 2016
Daniel Abramovitch - Agilent
R. Russell Rhinehart – Oklahoma State University
Tariq Samad – Honeywell