Fuzzy Logic and Fuzzy Inference for Python 3

a new observer-based adaptive fuzzy integral sliding mode controller (AFISMC) is proposed based on the Lyapunov stability theorem. The plant under study is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. In addition, a norm-bounded time varying term is introduced to address the possible existence of un-modelled/nonlinear dynamics. Based on the classical sliding mode controller (SMC), the equivalent control effort is obtained to satisfy the sufficient requirement of SMC and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. The sliding surface is compensated based on the observed states in the form of linear matrix inequality (LMI). In order to relax the norm-bounded constrains on the control law and solve the chattering problem of SMC, a fuzzy logic (FL) inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, by aiming at evaluating the validity of the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.

Lib describes core fuzzy logic things for building fuzzy inference systems.

🧠 ANFIS Framework (Java) A generic, extensible Java implementation of ANFIS (Adaptive Neuro-Fuzzy Inference System) — combining neural network learning with fuzzy logic interpretability. Supports configurable membership functions and T-norms for building flexible, trainable models.

Fuzzy Logic and Fuzzy Inference Python 3 Library

This Api makes executes inferences by fuzzy logic concept on Plain Old CLR Object associating an predicate defined in .NET native object called 'Expression'

LuaFuzzy is a simple library, totally written in Lua, to solve problems using fuzzy logic. It was developed based on the fuzzy logic toolbox of Matlab, and is very similar to understand and use. It implements the Mamdani inference system. This repository was converted from a CVS repository on luaforge.net on Jan. 20, 2010. On May 24, 2011 Lucas Lorensi, in coordination with folks at LuaForge, graciously appointed AJ Sherbondy as the official maintainer of the LuaFuzzy project. The initial focus will be to test the code with the most recent release of Lua to determine if there are any bugs. If there are bugs we fix them. We will also prepare the code for the pending release of Lua-5.2 and when this is complete extend the code.

A PyTorch-based framework for building neuro-fuzzy inference systems (NFIS). Combines fuzzy logic reasoning with neural network learning for interpretable AI.

Simple fuzzy rule-based logic inference system based on the Mamdani principles.

Simple fuzzy logic inference for control

This is a fuzzy inference engine written in C++. It is a multi-stage inference engine based on fuzzy logic focused on speed and flexibility.

Implementation of a fuzzy logic-based predictive model for wind farm energy production, utilizing Fuzzy C-Means (FCM) and fuzzy inference systems to forecast short-term energy fluctuations.

Many factors related to river runoff are vague, subjective and difficult to quantify. The fuzzy logic method is very useful for such problem solving approach such as small hydro power generation. The rule base and membership functions have a great influence on the performance and efficacy of the plant and also to optimize the small hydro power generation in the high altitude region particularly in India. The fuzzy linguistic variable performance can be easily characterized by common terms. The paper initially presents a new Fuzzy Logic Controller (FLC) method for safe reservoir control of dams through spillway gates. Finally it presents FLC method for turbine valve to control the water flow through turbine for hydro power generation. Thus it shows overall effective control and operation of the mechanical equipments in a hydro electric power generation project with FLC and its usefulness. The hardware of control system for fuzzifiers and defuzzifiers can be designed according to the need of system. All above proposed simplified models uses " Tabu Search Algorithm " , " Fuzzy Delphi Method " and " Mamdani Inference Method " to evaluate using manual " C.O.G. Defuzzification " and MATLAB FIS editor validation.

fuzzy logic inference system (in golang)

Implementation of FIS (Fuzzy Inference System) using MATLAB fuzzy logic toolbox to evaluate the performance of a student based on academics, co-curricular activities and sports. Overall performance of the student is found out.

LOIS lab works. Inference in Fuzzy logic.

Simple Framework for Fuzzy Logic (fuzzy sets, linguistic variables, (de-)fuzzyfication, fuzzy inference)

Fuzzy Logic inference engine written in python

Evaluator for fuzzy logic systems with several inference models, defuzzification methods and membership functions.

An automatic car game implemented using fuzzy logic, utilizing fuzzification, inference, and defuzzification for gameplay.

In this project involves the application of fuzzy logic and fuzzy Inference techniques to create a personalized recommendation engine. Fuzzy logic allows for handling uncertainty and imprecision in data, making it a valuable tool for recommendation systems.

A (as of yet) simple fuzzy logic API for ruby. It already supports a variety of membership functions and inference rules.

use fuzzy logic inference to predict irrigation duration

Fredy - expert system on fuzzy logic inference engine

Knowledge based system for medical diagnostics using the Bayesian Network, Propositional and Fuzzy Logic for disease inference.

This repository provides an implementation of an Interval Type-2 Adaptive Neuro-Fuzzy Inference System (IT2-ANFIS) using the One-Step Type Reduction Algorithm (OSTRA) in MATLAB. The model is designed for fuzzy modeling applications, leveraging generalized bell-shaped membership functions tailored to IT2 fuzzy logic principles.

The toolbox lets you model complex system behaviors using simple logic rules, and then implement these rules in a fuzzy inference system.

Fuzzy Logic Inference System

Fuzzy Logic with Sugeno Inference

Fuzzy logic inference system for javascript