Fuzzy Logic Based MATLAB Projects

Fuzzy Signal Detection in Multiple-access Ultra Wide Band Communication Systems

Ultra-wide band (UWB) communications transmits a wide bandwidth signal with an extremely low power spectral density. This property of UWB makes it possible to co-exist with the current narrowband communication systems operating at dedicated frequency bands.

Ultra-wide band can also serve multiple users by using the Spread Spectrum (SS) technique. However, with the number of multiple users increasing, signals associated with users will interfere with each other, resulting in Multi-Access Interference (MAI), a drawback in MA-UWB systems, which could adversely affect the system performance.

An Embedded Simplified Fuzzy ARTMAP Implemented on a Microcontroller for Food Classification

A portable system based on a microcontroller has been developed to classify different kinds of honeys. In order to do this classification, a Simplified Fuzzy ARTMAP network (SFA) implemented in a microcontroller has been used. Due to memory limits when working with microcontrollers, it is necessary to optimize the use of both program and data memory. Thus, a Graphical User Interface (GUI) for MATLAB® has been developed in order to optimize the necessary parameters to programm the SFA in a microcontroller.

The measures have been carried out by potentiometric techniques using a multielectrode made of seven different metals. Next, the neural network has been trained on a PC by means of the GUI in Matlab using the data obtained in the experimental phase. The microcontroller has been programmed with the obtained parameters and then, new samples have been analyzed using the portable system in order to test the model. Results are very promising, as an 87.5% recognition rate has been achieved in the training phase, which suggests that this kind of procedures can be successfully used not only for honey classification, but also for many other kinds of food.

A Dynamic Fuzzy Controller to Meet Thermal Comfort by using Neural Network Forecasted Parameters as the Input

Heating, ventilating and air-conditioning (HVAC) systems are typical non-linear time-variable multivariate systems with disturbances and uncertainties. This paper proposes a combined neuro-fuzzy model for dynamic and automatic regulation of indoor temperature. The artificial neural network performs indoor temperature forecasts that are used to feed a fuzzy logic control unit in order to manage HVAC on/off switching and inlet air speed regulation.

Moreover, the neural network is optimized by analytical calculation of embedding parameters, and the approach is tested through MATLAB. The fuzzy controller is driven by the forecasted indoor temperature and can adjust membership functions dynamically to reflect subjective thermal comfort variations.

Fuzzy Controlled SVC for Transmission Line

The primary purpose of this project is to create and simulate the fuzzy logic for SVC firing angle to achieve smoother and adaptive reactive power control. Design, modeling and simulations are carried out for a λ/8 transmission line with compensation positioned at the receiving (load) end.

Designing an Optimal Fuzzy Logic Controller of a DC Motor

The use of Particle Swarm Optimization for designing an optimal fuzzy logic controller of a DC Motor is presented in this project. The approach is to optimize the membership functions of a fuzzy logic controller using PSO; simulation and evaluation are performed in Simulink.

Neuro-Fuzzy Wavelet based Adaptive Mppt Algorithm for Photovoltaic Systems Using MATLAB

An intelligent control for PV systems is developed combining fuzzy logic, neural learning and wavelet localization (HWNF-based gradient estimator) to create an indirect neuro-fuzzy wavelet-based MPPT controller; MATLAB results show improved response and efficiency over conventional methods.

Evidence based Uncertainty Models and Particles Swarm Optimization for Multiobjective Optimization of Engineering Systems Using MATLAB

The present work develops methodologies for solving engineering analysis and design problems involving uncertainties and evidence from multiple sources. The influence of uncertainties on system safety and warranty costs are investigated. A methodology is developed combining modified Dempster Shafer Theory (DST) and Fuzzy Theory with PSO for uncertain engineering system design.

Genetic Algorithm: An Authentic tool for Agriculture Business System implemented by MATLAB

Genetic Algorithms are probabilistic algorithms inspired by natural evolution. This project demonstrates GA usage for optimization in agriculture systems, covering initial population, fitness evaluation and genetic operators (selection, crossover, mutation).

Power Load Balancing Using Fuzzy Logic Using MATLAB

Phase balancing and load control in distribution systems is addressed using fuzzy logic control. Input to the fuzzy system is the total load of feeders; the output guides a load balancing system that converts kW values into load points for optimization.

Simulation of Riding a Bicycle Using Simulink Using MATLAB

Training to ride a bicycle in a race requires a rider to maintain different cadences for given situations. This project builds a Simulink bicycle model and designs fuzzy controllers for cadence and gear shifting; simulation shows good cadence control and identifies gear shift singularity issues.

Smart Farm: Automated Classifying and Grading System of Tomatoes using Fuzzy Logic Using MATLAB

Design an image-processing and fuzzy inference based system in MATLAB to automatically classify and grade tomatoes (damaged vs not damaged; underripe/ripe/overripe), improving precision agriculture yields.