Chapter 1
Executive Summary
Rapid advances in computing, communications, and sensing technology offer un-
precedented opportunities for the field of control to expand its contributions to the
economic and defense needs of the nation. This report presents the findings and
recommendations of a panel of experts chartered to examine these opportunities.
We present an overview of the field, review its successes and impact, and describe
the new challenges ahead. We do not attempt to cover the entire field. Rather, we
focus on those areas that are undergoing the most rapid change and that require
new approaches to meet the challenges and opportunities that face the community.
Overview of Control
Control as defined in this report refers to the use of algorithms and feedback in
engineered systems. At its simplest, a control system is a device in which a sensed
quantity is used to modify the behavior of a system through computation and
actuation. Control systems engineering traces its roots to the industrial revolution,
to devices such as the centrifugal governor, shown in Figure 1.1. This device used
a flyball mechanism to sense the rotational speed of a steam turbine and adjust
the flow of steam into the machine using a series of linkages. By thus regulating
the turbine’s speed, it provided the safe , reliable , consistent operation that was
required to enable the rapid spread of steam-powered factories.
Control played an essential part in the development of technologies such as
power, communications, transportation, and manufacturing. Examples include au-
topilots in military and commercial aircraft (Figure 1.2a), regulation and control of
the electrical power grid, and high accuracy positioning of read/write heads in disk
drives (Figure 1.2b). Feedback is an enabling technology in a variety of application
areas and has been reinvented and patented many times in different contexts.
A modern view of control sees feedback as a tool for uncertainty management.
By measuring the operation of a system, comparing it to a reference, and adjusting
available control variables, we can cause the system to respond properly even if its
dynamic behavior is not exactly known or if external disturbances tend to cause it
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Chapter 1. Executive Summary
(a)
(b)
Figure 1.1.
The centrifugal governor (a), developed in the 1780s, was an
enabler of the successful Watt steam engine (b), which fueled the industrial revolu-
tion. Figures courtesy of Cambridge University.
to respond incorrectly. This is an essential feature in engineering systems since they
must operate reliably and efficiently under a variety of conditions. It is precisely
this aspect of control as a means of ensuring robustness to uncertainty that ex-
plains why feedback control systems are all around us in the modern technological
world. They are in our homes, cars and consumer electronics, in our factories and
communications systems, and in our transportation, military and space systems.
The use of control is extremely broad and encompasses a number of different
applications. These include control of electromechanical systems, where computer-
controlled actuators and sensors regulate the behavior of the system; control of elec-
tronic systems, where feedback is used to compensate for component or parameter
variations and provide reliable, repeatable performance; and control of information
and decision systems, where limited resources are dynamically allocated based on
estimates of future needs. Control principles can also be found in areas such as
biology, medicine, and economics, where feedback mechanisms are ever present. In-
creasingly, control is also a mission critical function in engineering systems: the
systems will fail if the control system does not work.
Contributions to the field of control come from many disciplines, including
pure and applied mathematics; aerospace, chemical, mechanical, and electrical en-
gineering; operations research and economics; and the physical and biological sci-
ences. The interaction with these different fields is an important part of the history
and strength of the field.
Successes and Impact
Over the past 40 years, the advent of analog and digital electronics has allowed
control technology to spread far beyond its initial applications, and has made it an
enabling technology in many applications. Visible successes from past investment
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(a)
(b)
Figure 1.2.
Applications of control: (a) the Boeing 777 fly-by-wire aircraft
and (b) the Seagate Barracuda 36ES2 disk drive. Photographs courtesy of the Boeing
Company and Seagate Technology.
in control include:
•
Guidance and control systems for aerospace vehicles, including commercial
aircraft, guided missiles, advanced fighter aircraft, launch vehicles, and satel-
lites. These control systems provide stability and tracking in the presence of
large environmental and system uncertainties.
•
Control systems in the manufacturing industries, from automotive to inte-
grated circuits. Computer controlled machines provide the precise positioning
and assembly required for high quality, high yield fabrication of components
and products.
•
Industrial process control systems, particularly in the hydrocarbon and chemi-
cal processing industries. These maintain high product quality by monitoring
thousands of sensor signals and making corresponding adjustments to hun-
dreds of valves, heaters, pumps, and other actuators.
•
Control of communications systems, including the telephone system, cellular
phones, and the Internet. Control systems regulate the signal power lev-
els in transmitters and repeaters, manage packet buffers in network routing
equipment, and provide adaptive noise cancellation to respond to varying
transmission line characteristics.
These applications have had an enormous impact on the productivity of modern
society.
In addition to its impact on engineering applications, control has also made
significant intellectual contributions. Control theorists and engineers have made
rigorous use of and contributions to mathematics, motivated by the need to develop
provably correct techniques for design of feedback systems. They have been consis-
tent advocates of the “systems perspective,” and have developed reliable techniques
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Chapter 1. Executive Summary
(a)
(b)
Figure 1.3.
Modern networked systems: (a) the California power grid and
(b) the NSFNET Internet backbone. Figures courtesy of the state of California and
the National Center for Supercomputer Applications (NCSA).
for modeling, analysis, design, and testing that enable design and implementation
of the wide variety of very complex engineering systems in use today. Moreover,
the control community has been a major source and training ground for people who
embrace this systems perspective and who wish to master the substantial set of
knowledge and skills it entails.
Future Opportunities and Challenges
As we look forward, the opportunities for new applications that will build on ad-
vances in control expand dramatically. The advent of ubiquitous, distributed com-
putation, communication, and sensing systems has begun to create an environment
in which we have access to enormous amounts of data and the ability to process
and communicate that data in ways that were unimagined 20 years ago. This will
have a profound effect on military, commercial and scientific applications, especially
as software systems begin to interact with physical systems in more and more in-
tegrated ways. Figure 1.3 illustrates two systems where these trends are already
evident. Control will be an increasingly essential element of building such intercon-
nected systems, providing high performance, high confidence, and reconfigurable
operation in the presence of uncertainties.
In all of these areas, a common feature is that system level requirements far
exceed the achievable reliability of individual components. This is precisely where
control (in its most general sense) plays a central role, since it allows the system
to ensure that it is achieving its goal through correction of its actions based on
sensing its current state. The challenge to the field is to go from the traditional
view of control systems as a single process with a single controller, to recognizing
control systems as a heterogeneous collection of physical and information systems,
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with intricate interconnections and interactions.
In addition to inexpensive and pervasive computation, communication, and
sensing—and the corresponding increased role of information-based systems—an
important trend in control is the move from low-level control to higher levels of de-
cision making. This includes such advances as increased autonomy in flight systems
(all the way to complete unmanned operation), and integration of local feedback
loops into enterprise-wide scheduling and resource allocation systems. Extending
the benefits of control to these non-traditional systems offers enormous opportuni-
ties in improved efficiency, productivity, safety, and reliability.
Control is a critical technology in defense systems and is increasingly impor-
tant in the fight against terrorism and asymmetric threats. Control allows the
operation of autonomous and semi-autonomous unmanned systems for difficult and
dangerous missions, as well as sophisticated command and control systems that
enable robust, reconfigurable decision making systems. The use of control in mi-
crosystems and senosr webs will improve our ability to detect threats before they
cause damage. And new uses of feedback in communications systems will provide
reliable, flexible, and secure networks for operation in dynamic, uncertain, and ad-
versarial environments.
In order to realize the potential of control applied to these emerging appli-
cations, new methods and approaches must be developed. Among the challenges
currently facing the field, a few examples provide insight into the difficulties ahead:
•
Control of systems with both symbolic and continuous dynamics.
Next gener-
ation systems will combine logical operations (such as symbolic reasoning and
decision making) with continuous quantities (such as voltages, positions, and
concentrations). The current theory is not well-tuned for dealing with such
systems, especially as we scale to very large systems.
•
Control in distributed, asynchronous, networked environments.
Control dis-
tributed across multiple computational units, interconnected through packet-
based communications, will require new formalisms for ensuring stability, per-
formance and robustness. This is especially true in applications where one
cannot ignore computational and communications constraints in performing
control operations.
•
High level coordination and autonomy.
Increasingly, feedback is being de-
signed into enterprise-wide decision systems, including supply chain manage-
ment and logistics, airspace management and air traffic control, and C4ISR
systems. The advances of the last few decades in analysis and design of ro-
bust control systems must be extended to these higher level decision making
systems if they are to perform reliably in realistic settings.
•
Automatic synthesis of control algorithms, with integrated verification and val-
idation.
Future engineering systems will require the ability to rapidly de-
sign, redesign and implement control software. Researchers need to develop
much more powerful design tools that automate the entire control design pro-
cess from model development to hardware-in-the-loop simulation, including
system-level software verification and validation.
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Chapter 1. Executive Summary
•
Building very reliable systems from unreliable parts.
Most large engineering
systems must continue to operate even when individual components fail. In-
creasingly, this requires designs that allow the system to automatically recon-
figure itself so that its performance degrades gradually rather than abruptly.
Each of these challenges will require many years of effort by the research community
to make the results rigorous, practical, and widely available. They will also require
investments by funding agencies to ensure that current progress is continued and
that forthcoming technologies are realized to their fullest.
Recommendations
To address these challenges and deliver on the promise of the control field, the Panel
recommends that the following actions be undertaken:
1. Substantially increase research aimed at the
integration
of control, computer
science, communications, and networking. This includes principles, methods
and tools for modeling and control of high level, networked, distributed sys-
tems, and rigorous techniques for reliable, embedded, real-time software.
2. Substantially increase research in control at higher levels of decision making,
moving toward enterprise level systems. This includes work in dynamic re-
source allocation in the presence of uncertainty, learning and adaptation, and
artificial intelligence for dynamic systems.
3. Explore high-risk, long-range applications of control to new domains such
as nanotechnology, quantum mechanics, electromagnetics, biology, and envi-
ronmental science. Dual investigator, interdisciplinary funding might be a
particularly useful mechanism in this context.
4. Maintain support for theory and interaction with mathematics, broadly in-
terpreted. The strength of the field relies on its close contact with rigorous
mathematics, and this will be increasingly important in the future.
5. Invest in new approaches to education and outreach for the dissemination of
control concepts and tools to non-traditional audiences. The community must
do a better job of educating a broader range of scientists and engineers on the
principles of feedback and the use of control to alter the dynamics of systems
and manage uncertainty.
The impact of control is one which will come through many applications, in
aerospace and transportation, information and networking, robotics and intelligent
machines, materials and processing, and biology and medicine. It will enable us to
build more complex systems and to ensure that the systems we build are reliable,
efficient, and robust. The Panel’s recommendations are founded on the diverse
heritage of rigorous work in control and are key actions to realize the opportunities
of control in an information rich world.