Omer Faruk Bay

A type-2 fuzzy logic controller design for buck and boost DC–DC converters

Conventional (type-1) fuzzy logic controllers have been commonly used in various power converter applications. Generally, in these controllers, the experience and knowledge of human experts are needed to decide parameters associated with the rule base and membership functions. The rule base and the membership function parameters may often mean different things to different experts. This may cause rule uncertainty problems. Consequently, the performance of the controlled system, which is controlled with type-1 fuzzy logic controller, is undesirably affected. In this study, a type-2 fuzzy logic controller is proposed for the control of buck and boost DC–DC converters. To examine and analysis the effects of the proposed controller on the system performance, both converters are also controlled using the PI controller and conventional fuzzy logic controller. The settling time, the overshoot, the steady state error and the transient response of the converters under the load and input voltage changes are used as the performance criteria for the evaluation of the controller performance. Simulation results show that buck and boost converters controlled by type-2 fuzzy logic controller have better performance than the buck and boost converters controlled by type-1 fuzzy logic controller and PI controller.

Fuzzy control of dc–dc converters based on user friendly design

The aim of this paper is to show how to build a fuzzy controller and its membership functions automatically. In a fuzzy logic controller (FLC), the proposed method allows one easily to construct a set of membership functions, called shrinking-span membership functions (SSMFs). The FLC uses Mamdani-type fuzzy controllers for the defuzzification strategy and inference operators. The FLC hardware implementation is performed on an 8-bit microcontroller. Simulation results and experimental results demonstrate that the converter can be regulated with good performance even when subjected to input disturbance and load variation. The presented approach is generally valid for the design of an FLC, and can be applied to any dc–dc converter topologies.

Survey of Fuzzy Logic Applications in Brain-Related Researches

The aim of this study was to survey fuzzy logic (FL) applications in brain researches. In general, these applications are related to pattern recognition for localization in brain structures or tumor detection, image segmentation, and simulations. In recent years, neural networks and FL are gaining popularity. FL is based on the observation of people. The enormous amount of information representation by the brain suggests that FL principles can be useful, especially for complex brain functions. Causal models based on functional neuroanatomy can be then implemented in computer simulations to reflect the dynamical intersection of brain structures. FL is considered as an appropriate tool for modelling and control. FL has been applied in different ways to brain researches. This paper surveys the utilization of FL in brain researches.

Realization of a Single Phase DSP Based Neuro-Fuzzy Controlled Uninterruptible Power Supply

In this study, a neuro-fuzzy (NF) control algorithm is proposed for the application in control of a single phase, power factor corrected (PFC), uninterruptible power supply (UPS). To make a comparison, the designed UPS is also controlled using traditional proportional and integral (PI) controller. The average current control technique is used in the PFC stage of the UPS and the current mode control technique is used in the inverter stage of the UPS. Performances of these two controllers are compared through the computer simulation and practical studies. The results of the simulation and experimental studies based on TMS320F2812 digital signal processor show that the NF controlled UPS has better performance than the PI controlled UPS in input power factor correction and total harmonic distortion (THD) of output voltage under nonlinear loading conditions.

Modeling of the Inductance Variation and Control of the Switched Reluctance Motor Based on Fuzzy Logic

Abstract Switched Reluctance Motors (SRNs) aze increasingly popular machines in electrical drives, whose performances are directly related to their operating conditions. Their dynamic characteristics vary as conditions change. Recently, several methods of the modeling of the magnetic saturation of SRNs have been proposed as analytical functions. However, the SRM system is nonlinear and cannot be adequately described by such models. Fuzzy Logic (FL) is known that might overcome this problem. This paper introduces an attempt to use fuzzy logic to model of the inductance variation of the switched reluctance motor and to control the switched reluctance motor using fuzzy model. Fuzzy based modelling does not require an accurate mathematical model which is very difficult to obtain from a switched reluctance motor because of its inherit nonlinearities. The modelling method in this paper differs significantly from previous modelling methods. An application of fuzzy sets to the SRM drive control was also applied t...

Development of a hybrid web application firewall to prevent web based attacks

Firewall and intrusion detection systems are used by the purposes of preventing information loss and weakness on internet and providing security for web applications. However attacks to web applications do not only come from network layer. Web applications use Hyper Text Transfer Protocol (HTTP) and attacks come from this protocol to web pages. Tools used for providing security on network layer become inefficient for HTTP attacks. These attacks to web applications can be prevented by detection of HTTP. In this study, a hybrid web application firewall is developed by using proposed signature based detection and anomaly detection methods, to prevent attacks by detection of HTTP requests.

A practical application of the interval type-2 fuzzy controller for a photovoltaic sourced DC – DC boost converter

This paper presents an implementation of type-2 fuzzy controller for DC - DC boost converter fed by photovoltaic panels. High power boost converter is the imperative part of the renewable energy power system that transfers energy to the utility or standalone study. Power circuit applications require fast dynamic response, lower overshoot and lower steady state error. Intelligent control algorithms are used to obtain these features. Type-1 fuzzy logic control is one of the intelligent control algorithms. Power circuits are non-linear structure and contain uncertainties. Conventional controllers and type-1 fuzzy controllers cannot be enough to overcome uncertainties. In this study, type-2 fuzzy controller which has high performance for modeling uncertainties has been developed as control algorithm for DC - DC boost converter. The converter has been also controlled with proportional-integral (PI) and type-1 fuzzy controller separately to show the superiority of the developed type-2 fuzzy controller. The converter has been controlled with TMS320F28335 DSP for real time application. Each control algorithm has been used to control of the converter individually. Settling time, overshoot and load variation responses have been investigated for the converter. Results showed that type-2 fuzzy controller has pointed out the best performance.

Region based Brain Computer Interface for a home control application

Environment control is one of the important challenges for disabled people who suffer from neuromuscular diseases. Brain Computer Interface (BCI) provides a communication channel between the human brain and the environment without requiring any muscular activation. The most important expectation for a home control application is high accuracy and reliable control. Region-based paradigm is a stimulus paradigm based on oddball principle and requires selection of a target at two levels. This paper presents an application of region based paradigm for a smart home control application for people with neuromuscular diseases. In this study, a region based stimulus interface containing 49 commands was designed. Five non-disabled subjects were attended to the experiments. Offline analysis results of the experiments yielded 95% accuracy for five flashes. This result showed that region based paradigm can be used to select commands of a smart home control application with high accuracy in the low number of repetitions successfully. Furthermore, a statistically significant difference was not observed between the level accuracies.

Classification of P300 event related potentials with Discrete Wavelet Transform

Brain Computer Interfaces (BCIs) are the systems that enable users who lost their motor capabilities due to neuromuscular diseases to communicate with their environment through the analysis of brain activity. P300 event related potential is one of the widely used signals in BCI applications. In this study, it is aimed classification of P300 potentials by using Discrete Wavelet Transform (DWT) and Linear Discriminant Analysis (LDA) techniques. The proposed method is validated on BCI Competition III P300 dataset provided by the Wadsworth Center. The features that are extracted by wavelet transform showed significant differences between target and non-target stimuli. According to the classification results, 58% and 93% character prediction accuracy is achieved for 5 and 15 intensifications, respectively.

Computerized Control of the Procedure for Detecting and Removing Airborne Particles in Operating Rooms

Surgical-site infections are still a major problem in modern medicine. Normal skin flora of patients or healthcare workers causes more than half of all infections following clean surgery, but the importance of airborne particles in this setting remains controversial. The use of ultraclean air in operating rooms has been shown to reduce infection rates significantly. High efficiency particulate air (HEPA) filters are used in some modern operating rooms. Although the uses of HEPA filters, the air quality should be controlled by another device to make safe the air in operating rooms and intensive care units. In this study, a computerized system was established to control the cleanliness of the air by measuring the presence of airborne particles of varying sizes and numbers in operating rooms. When the maximum values are exceeded, the system warns the authorized people by phone, sound, or displays.