Washing eggs with fuzzy logic

Arriving at a solution sometimes comes from learning a different way to express the problem.
Fuzzy logic has been around for more than forty years, so it isn’t anything new to the controls community.

Until recently its use has been primarily in the areas of advanced control or in certain embedded OEM applications, where extra performance is required. For example, most manufacturers of singleloop controllers include fuzzy logic as part of their control algorithms. Today, with the advent of sensors that can measure simple quantities that in the past could only be estimated by human operators, fuzzy logic shows new promise for manufacturing end users to solve common problems on the factory floor. For example, simple machine vision sensors today can give good estimates of how ‘clean’ or ‘dirty’ an incoming batch of eggs is, something that until now only an operator could do.

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Rockwell Automation program manager Dave Carr and software project manager Jeff Shearer recently published a 45-page white paper exploring fuzzy logic and how it helps engineers solve nonlinear control problems. They present fuzzy logic as an intuitive way to design function blocks for intelligent control systems, advanced fault detection, and other complex applications.

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