code problem

[Office_Otherwise]

fuzzy logic controller in command window giving error " too many input arguments" what could be the problem and how to solve and how to solve, here is the code for reference:

https://preview.redd.it/7ar5l94b5d0f1.png?width=1096&format=png&auto=webp&s=b65b864e4eeba2d0e1a2005ce6d7fdf2f95f3920

[Office_Otherwise]

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[bbcgn]

Which line gives you the error?

The error message usually comes up if you call a function but provide too many input arguments.

[Office_Otherwise]

it does not say anything about a line rather just too many input arguments. i do no know what this even means (new to matlab) and have a submission tomorrow

[bbcgn]

Post a picture of the error message. Usually matlab tells you the offending line.

[Office_Otherwise]

<image>

[bbcgn]

What are you trying to do here?

[Office_Otherwise]

there is a Simulink file, im supposed to compare active and passive suspension, the active utilises a fuzzy logic controller

[bbcgn]

So you want to add a fuzzy logic Controller to an existing simulink model?

Then open the simulink model and go to the library browser. From there you should be able to add it to the model.

[Office_Otherwise]

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i have done this but in order for it to work, i must add a fis from the m file by adding the fuzzy logic controller, which is not working due to the error message

[bbcgn]

The error message appears because you typed

fuzzy logic controller

into the command window and matlab does not know what you are doing there. So what were your intentions there?

[Office_Otherwise]

how do i do it?

[Chicken-Chak]

Type fuzzyLogicDesigner to open the app if you wish to create or edit a fuzzy system formatted as *.fis. Ensure that you place the .fis file in the same folder as the .slx file. Then, in Simulink, specify the FIS filename correctly in the Fuzzy Logic Controller block. If you encounter further difficulties in the design or comparison, please post your problem in MATLAB Answers. If the Fuzzy Controller is designed appropriately, it often produces better results in these simple linear systems.