Fuzzy Logic Controller

 Fuzzy Logic Controller


In our day to day life, we might face situations where we are unable to determine whether the state is true or false. Fuzzy refers to something which is unclear or vague. Fuzzy logic control (FLC) is the most active research area in the application of fuzzy set theory, fuzzy reasoning, and fuzzy logic. The application of FLC extends from industrial process control to biomedical instrumentation and securities.

What is Fuzzy Logic?

Fuzzy Logic resembles the human decision-making methodology. It deals with vague and imprecise information. This is gross oversimplification of the real-world problems and based on degrees of truth rather than usual true/false or 1/0 like Boolean logic.




Why Use Fuzzy Logic in Control Systems


A control system is an arrangement of physical components designed to alter another physical system so that this system exhibits certain desired characteristics. Following are some reasons of using Fuzzy Logic in Control Systems − While applying traditional control, one needs to know about the model and the objective function formulated in precise terms. This makes it very difficult to apply in many cases.
By applying fuzzy logic for control we can utilize the human expertise and experience for designing a controller.
The fuzzy control rules, basically the IF-THEN rules, can be best utilized in designing a controller.


Major Components of FLC

Followings are the major components of the FLC as shown in the above figure −

  • Fuzzifier − The role of fuzzifier is to convert the crisp input values into fuzzy values.

  • Fuzzy Knowledge Base − It stores the knowledge about all the input-output fuzzy relationships. It also has the membership function which defines the input variables to the fuzzy rule base and the output variables to the plant under control.

  • Fuzzy Rule Base − It stores the knowledge about the operation of the process of domain.

  • Inference Engine − It acts as a kernel of any FLC. Basically it simulates human decisions by performing approximate reasoning.

  • Defuzzifier − The role of defuzzifier is to convert the fuzzy values into crisp values getting from fuzzy inference engine

Advantages of Fuzzy Logic Control

Let us now discuss the advantages of Fuzzy Logic Control.

  • Cheaper − Developing a FLC is comparatively cheaper than developing model based or other controller in terms of performance.

  • Robust − FLCs are more robust than PID controllers because of their capability to cover a huge range of operating conditions.

  • Customizable − FLCs are customizable.

  • Emulate human deductive thinking − Basically FLC is designed to emulate human deductive thinking, the process people use to infer conclusion from what they know.

  • Reliability − FLC is more reliable than conventional control system.

  • Efficiency − Fuzzy logic provides more efficiency when applied in control system.

Disadvantages of Fuzzy Logic Control

We will now discuss what are the disadvantages of Fuzzy Logic Control.

  • Requires lots of data − FLC needs lots of data to be applied.
    Useful in case of moderate historical data − FLC is not useful for programs much smaller or larger than historical data.
    Needs high human expertise − This is one drawback as the accuracy of the system depends on the knowledge and expertise of human beings.

  • Needs regular updating of rules − The rules must be updated with time.


Applications:

  • Aerospace:

In aerospace, fuzzy logic is used in the following areas −

  • Altitude control of spacecraft
  • Satellite altitude control
  • Flow and mixture regulation in aircraft deicing vehicles

  • Automotive:

In automotive, fuzzy logic is used in the following areas −

  • Trainable fuzzy systems for idle speed control
  • Shift scheduling method for automatic transmission
  • Intelligent highway systems
  • Traffic control
  • Improving efficiency of automatic transmissions

  • Pattern Recognition and Classification:

In Pattern Recognition and Classification, fuzzy logic is used in the following areas −

  • Fuzzy logic based speech recognition
  • Fuzzy logic based
  • Handwriting recognition
  • Fuzzy logic based facial characteristic analysis
  • Command analysis
  • Fuzzy image search
Fields such as Defense, Electronics, Medical, Industrial Sector are also using Fuzzy Logic Systems.


THANK YOU !! 


Blog By: Raman Kulkarni
Roll no. 61

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