Fuzzy Control of Inverted Pendulum System

Getting more satisfactory result by the new branch of fuzzy logic control system

This document is dedicated to explaining briefly how the Fractional Fuzzy Inference Systems (FFISs) can be implemented in MATLAB through the use of the second version of the function FFIS.m, i.e., (the version No. 240301). This version has been built by MATLAB Version: R2020a and is compatible with Windows 64-bit. In this package the example of control of an inverted pendulum system has been examined showing that you can get more satisfactory result than the application of Mamdani's fuzzy controller.

The package includes the following files:

The help file: Help_FFIS240301.pdf

FFIS.m

Supplementary Mex files namely: HMFunction.mexw64, eval_trapmf.mexw64, eval_trimf.mexw64, and mexFidsPoly.mexw64

Supplementary m-files: evalmf2.m and checkPolynomialRange.m(Optional)

The example files: (example.m, IP_example.fis})

The main file that should be used is FFIS.m. This function evaluates fractional fuzzy inference system. Its role is similar to the evalfis.m in the MATLAB software.

Note. The mex files and the evalmf2.m must be in the same folder along with FFIS.m.

Before using the FFIS.m please watch the tutorial published on YouTube.

Detail information about FFISs may be found in the following references:

https://youtu.be/DXiO4oNrohk

https://www.youtube.com/watch?v=U4YmRDhOLno

https://youtu.be/t3DR0Ajgd1Q

Mehran Mazandarani, L. Xiu,Interval Type-2 Fractional Fuzzy Inference Systems: Towards an evolution in fuzzy inference systems, Expert Systems with Applications, 2022.

Link: https://www.sciencedirect.com/science/article/pii/S0957417421013002

Mehran Mazandarani, Li Xiu, Fractional Fuzzy Inference System: The New Generation of Fuzzy Inference Systems, IEEE Access, Vol. 8, pp. 126066-126082, 2020.

DOI: 10.1109/ACCESS.2020.3008064

Link: https://ieeexplore.ieee.org/document/9136681