Fuzzy Control: Setting Membership Ranges

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In summary, the conversation discusses setting ranges for memberships in a fuzzy control system. The speaker is familiar with the rules but is unsure how to set the ranges. They mention using a step as the input and a transfer function after the fuzzy block. A possible solution is suggested, using the fuzzy logic GUI in Simulink to implement the desired rules.
  • #1
luca99
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How can I set the ranges of memberships in a fuzzy control? I know my rules, but I don't know how to set ranges, the input of the entire system is a step and after the fuzzy block there is a transfer function and the output.
 

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  • #2
Here's some discussion on fuzzy logic that may guide you to an answer:

http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol2/jp6/article2.html
 
  • #3
luca99 said:
How can I set the ranges of memberships in a fuzzy control? I know my rules, but I don't know how to set ranges, the input of the entire system is a step and after the fuzzy block there is a transfer function and the output.
you're doing that in simulink and using the fuzzy logix block?
simply use the fuzzy logic GUI to implement the rules you have in mind
 

What is fuzzy control?

Fuzzy control is a control system that uses fuzzy logic to make decisions based on imprecise or uncertain information. It allows for a more flexible and human-like approach to control systems, as it can handle vague or subjective inputs.

What are membership functions in fuzzy control?

Membership functions in fuzzy control define the degree to which a variable belongs to a specific set. They map the input values to a range of membership values between 0 and 1, representing the degree of membership in a fuzzy set.

How are membership ranges set in fuzzy control?

Membership ranges in fuzzy control are typically set through expert knowledge or experimentation. The membership ranges can be adjusted to achieve the desired output and can vary depending on the specific application.

What are the benefits of using fuzzy control?

Fuzzy control allows for more flexibility and adaptability in control systems, as it can handle imprecise or uncertain inputs. It also does not require precise mathematical models, making it suitable for complex systems. Additionally, it can handle non-linear relationships between inputs and outputs.

What are some common applications of fuzzy control?

Fuzzy control is commonly used in a variety of fields, including robotics, artificial intelligence, and process control. It has also been applied in areas such as traffic control, stock market analysis, and medical diagnosis.

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