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Nonlinear Control and Decision Making Using Fuzzy Logic in Logix

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This white paper explores fuzzy logic and how it helps engineers solve nonlinear control problems commonly found in process applications. Fuzzy logic, which mathematically emulates human reasoning, provides an intuitive way to design function blocks for intelligent control systems, advanced fault detection and other complex applications. Control systems deploying fuzzy logic can improve the management of uncertain variables, such as temperature fluctuations.

Fuzzy logic is a technique that attempts to systematically and mathematically emulate human reasoning and decision-making. Fuzzy logic allows engineers to exploit their empirical knowledge and heuristics represented in the “if/then” rules and transfer it to a function block. Fuzzy logic thus provides engineers with a clear and intuitive way to implement control systems, decision-making and diagnostic systems in various branches of industry. Fuzzy logic algorithms can be used for advanced applications in industrial automation such as:

• Intelligent control systems
  Fuzzy control solutions are especially useful for complex systems where standard means such as PID control fails. Fuzzy logic can be an advantage in cases where an explicit analytical-process model is not available or is too complex. Another advantage of fuzzy logic is that it can be easily combined with conventional controllers and substantially enhance their functionality. For example, fuzzy rules interpolate between a series of locally linear controllers and schedule gains of a PID controller based on changing operating conditions. So fuzzy rules do not have to necessarily replace conventional control methods, but rather extend their capabilities.
• Process diagnostics, fault detection
  If an analytical process model is not available or is too complex to be run in real-time, empirical knowledge can be used to classify process conditions and early detect faults.
• Decision-making and expert systems
  Fuzzy rules can emulate an experienced human operator in real time, e.g. select appropriate ingredients, components or machines according to specific situations in the manufacturing process.

File Size: 3.40 MB
File Type: PDF

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