Digital Signal Processing Reference
In-Depth Information
Signal Processing for Control
William S. Levine
Abstract
Signal processing and control are closely related. In fact, many controllers
can be viewed as a special kind of signal processor that converts an exogenous input
signal and a feedback signal into a control signal. Because the controller exists
inside of a feedback loop, it is subject to constraints and limitations that do not
apply to other signal processors. A well known example is that a stable controller
in series with a stable plant can, because of the feedback, result in an unstable
closed-loop system. Further constraints arise because the control signal drives a
physical actuator that has limited range. The complexity of the signal processing in
a control system is often quite low, as is illustrated by the Proportional + Integral +
Derivative (PID) controller. Model predictive control is described as an exemplar
of controllers with very demanding signal processing. ABS brakes are used to
illustrate the possibilities for improved controller capability created by digital signal
processing. Finally, suggestions for further reading are included.
1
Introduction
There is a close relationship between signal processing and control. For example, a
large amount of classical feedback control theory was developed by people working
for Bell Laboratories who were trying to solve problems with the amplifiers used for
signal processing in the telephone system. This emphasizes that feedback, which is
a central concept in control, is also a very important technique in signal processing.
Conversely, the Kalman filter, which is now a critical component in many signal
processing systems, was discovered by people working on control systems. In fact,
W.S. Levine (
)
Department of ECE, University of Maryland, College Park, MD 20742, USA
e-mail:
wsl@ece.umd.edu
