Fuzzy Controller and its Industrial Applications

Fuzzy logic is a human model, potentially applicable to a wide range of processes and tasks that require human instinct and experience. In computer, truth-values are either 1 or 0, which corresponds to true/false duality. In fuzzy logic, truth is the matter of degree, hence truth-values ranges between 1 and 0 in a continuous manner. Fuzzy logic is a technique for representing information in a way that resembles human communication. It is a rule-based system. It consists of if…then rules.

Fuzzy logic can be applied by means of software dedicated controllers or fuzzy microprocessor embedded in digital products. Application flexibility combined with inherent simplicity and a wide range of capabilities give fuzzy logic technology a great potential for growth.

Related: What is Sequential Control System?

Fuzzy systems are rule-based with a strong mathematical basis. A fuzzy system is principally made of fuzzifier, a defuzzifier, an inference engine and a rule base. This is illustrated in the block diagram below:

The role of the fuzzifier is to map the crisp input data (a collection of distinct elements) value to fuzzy sets defined by their membership functions depending on the degree of “possibility” of the input data. The goal of the defuzzifier is to map the output fuzzy sets to a crisp output value. It combines the different fuzzy sets with different degrees of possibility to produce a single numerical value.

Fuzzy inference engine defines how the system should infer the rules in the rule base to determine the output fuzzy sets.

Industrial Applications of Fuzzy Logic

Fuzzy technology is already employed in some industrial control applications. Future industrial applications for fuzzy logic might include flow and proximity sensors. Other control applications for fuzzy logic may be in the chemical processing industries.

Related: What is the Controller?

Bottom Line

Fuzzy control is still a technology in development and is not widely used in industries. Fuzzy logic can incorporate nonlinear relationships or knowledge gathered from experience early in the control system design. For some processes, fuzzy logic in the design of control systems may reduce application development time.

You can also read: Proportional-Integral-Derivative (PID) Control Systems