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.
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Levine, W.S. (2010). Signal Processing for Control. In: Bhattacharyya, S., Deprettere, E., Leupers, R., Takala, J. (eds) Handbook of Signal Processing Systems. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6345-1_1
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DOI: https://doi.org/10.1007/978-1-4419-6345-1_1
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