Fuzzy Logic PI Controller

Introduction

The term Fuzzy logic has been used in two different senses. It is thus essential to clarify the distinctions between these two different usages of the term. In a narrow sense, Fuzzy logic refers to a logical system that generalizes classical two-valued logic for reasoning under uncertainty. In a broad sense, Fuzzy logic refers to all of the theories and technologies that employ Fuzzy sets, which are classes with unsharp boundaries.

Fuzzy logic is all about the relative importance of correctness: how supreme is it to be exactly right when a rough answer will do?

Here is a list of general experience about fuzzy logic.

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  Fuzzy logic is as simple to understand. The mathematical ideas behind fuzzy reasoning are straightforward. What makes fuzzy simple is the “naturalness” of its approach and not its far-reaching difficulty.

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  Fuzzy logic is malleable. With any given system, it’s simple to massage it or layer more functionality on top of it without starting again from scratch.

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  Fuzzy logic is based on unfocused data. Everything is unfocused if you look closely enough, but more than that, most things are unfocused even on careful examination. Fuzzy reasoning made this understanding into the procedure rather than tacking it onto the end.

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  Fuzzy logic can model nonlinear functions of capricious difficulty. A fuzzy system can be developed to match any set of input-output data. This procedure is built particularly simple by adaptive techniques like ANFIS (Adaptive Neuro-Fuzzy Inference Systems), which can get in the Fuzzy Logic Toolbox.

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  Fuzzy logic can be made on top of the experience of resource persons. In direct contrast to neural networks, which take training data and create cloudy, impenetrable models, fuzzy logic depends on the experience of people who already interpret your system.

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  Fuzzy logic can be mixed with conventional control methods.

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  Fuzzy systems don’t necessarily change the conventional control techniques. In many cases, fuzzy systems increase them and simplify their implementation.

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  Fuzzy logic is rested on natural language.

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  The foundation for fuzzy logic is the foundation for human communication. This examination underpins many of the other statements about fuzzy logic.