Analysis Of Fuzzy Logic Controller Research Articles

A comparative analysis of PI & FLC based grid connected PV system with power backup to improve power quality

In this article, a fuzzy logiccontroller (FLC) tuned DC-link controller is presented. This controller is utilized to enhance the power quality characteristic of grid-integrated PV systems with power backup in comparison to the PI controller, without any filter at PCC (point of common coupling). The primary purpose of these controllers is to maintain power to the DC/AC sides by maintaining the DC-link voltage under transient conditions. The proposed system is tested with a non-linear load; hence, the proposed system requires power quality enhancements on PCC. By using both controller power flow control, reactive power compensation and harmonic mitigation is done on PCC, after that grid current becomes sinusoidal. For the power quality improvement, no filter/shunt active power filter (SAPF) is connected to PCC, only proposed inverter current controller improves the power quality at PCC by using these controllers. Using the MPPT (maximum power point tracking) Controller, the maximum power extraction feature is also included in this paper to extract maximum power from the PV module under varying atmospheric circumstances. The power backup unit is also connected with this system, power backup unit includes a battery controller which works as a boost and buck converter according to system requirements, along with a battery. On the MATLAB/Simulink platform, the control scheme and functioning of both controllers are tested, and the results are validated as satisfactory. According to IEEE 519, the grid current THD is below 5% when the suggested control system is implemented.

Comparative Analysis of Torque Ripple for Direct Torque Control based Induction Motor Drive with different strategies

ABSTRACT Direct Torque Control (DTC) method is one of the most outstanding and proficient control techniques of the induction motor. The foremost drawback of DTC induction motor drive is high torque pulsation, variable frequency of inverter switching. The main reason of torque pulsation is torque and flux hysteresis band utilised in DTC. DTC method is utilising hysteresis comparators which produce high torque pulsation and unpredictable switching frequency. In this paper, torque ripple analysis of fuzzy logic controller (FLC) based Direct Torque Control (DTC) of three-phase induction motor drive has been discussed. The space vector pulse width modulation (SVPWM) based DTC technique, which operates with the regular switching frequency, helps to solve the fundamental issues of torque pulsation. In addition to this, literature proposes different solutions like a prediction scheme, fuzzy logic controller technique, global minimum torque ripple strategy, constant frequency torque controller (CFTC) Technique, optimal switching instant scheme, duty cycle control scheme, SVPWM DTC for torque ripple reduction. The fuzzy logic controller capabilities for DTC technique are applied with the induction motor (IM) drive for high-performance applications. The simulation results of Conventional DTC, SVPWM DTC, Carrier SVPWM DTC and FLC-DTC method for the induction motor are illustrated. Fuzzy-based DTC technique compared with CSVPWM DTC method and conventional DTC method are presented. The torque ripple of 7.4% for 5 HP induction motor is achieved by FLC-based DTC method. Hardware results for DTC induction motor drive are also demonstrated and discussed. This paper presents improvement in torque ripple reduction with the help of carrier space vector pulse width modulation (CSVPWM) and FLC-based DTC.

Energy, economic and environmental analysis of fuzzy logic controllers used in smart buildings

This article is divided into three parts: the first presents a simulation study of the effect of occupancy level on energy usage pattern of Engineering building of Applied Science Private university, Amman, Jordan. The simulation was created on simulation mechanism by means of EnergyPlus software and improved by using the building’s data such as building’s as built plan, occupant’s density level based on data about who utilize the building throughout operational hours, energy usage level, Heating Ventilating and air conditioning (HVAC) system, lighting and its control systems and etc. Data regarding occupancy density level estimation is used to provide the proposed controller with random number of users grounded on report were arranged by the university’s facilities operational team. The other division of this paper shows the estimated saved energy by the means of suggested advanced add-on, FUZZY-PID controlling system. The energy savings were divided into summer savings and winter savings. The third division presents economic and environmental analysis of the proposed advanced fuzzy logic controllers of smart buildings in Subtropical Jordan. The economic parameters that were used to evaluate the system economy performance are life-cycle analysis, present worth factor and system payback period. The system economic analysis was done using MATLAB software

A study of Comparative analysis of fuzzy logic controller and neural network for dc–dc buck converter

This paper presents the comparative analysis between fuzzy logic controller and neural network for DC-DC Buck converter. The major drawback in the conventional buck converter is when the input voltage or load change, the output voltage also changes which reduces the overall efficiency of the buck converter. So here we are using non linear controllers for buck converter which respond quickly for perturbations and maintains the fixed load voltage even when there are non-linearity’s occurs compared to a linear controllers like P,PI,PID controllers which can’t withstand when perturbations occur. Simplicity, low cost and adaptability to the complex systems without mathematical modeling are the best features of Fuzzy Logic controller and neural networks. The Two implementations are analyzed in detail and simulated in MATLAB/SIMULINK environment and results presented. Proposed approach is implemented on DC to DC step down converter for an input of 230V and performance characteristics like maximum overshoot, settling time and efficiency of the converter are studied.

Analysis of fuzzy logic controller based bi-directional DC-DC converter for battery energy management in hybrid solar/wind micro grid system

This paper proposes a fuzzy logic-based battery energy management system in hybrid renewable system. The novel topology consists of solar and wind energy system-based input sources and a battery bank to store the energy when in excess. The PV-Wind source is equipped with unidirectional boost converter whereas, the battery storage system is connected to the system with a bi-directional DC/DC converter. The main novelty of this research is the fuzzy logic-based battery management system which charges and discharges into the DC bus system based on the supply-load demand. The fuzzy logic controller (FLC) based maximum power point tracking (MPPT) is used in the PV and wind energy conversion system (WECS) to track the maximum available power for the different irradiance and wind velocity respectively. The obtained results are compared to conventional P&O MPPT control algorithm to find the effectiveness of the system. A 500 W PV system and a 500 W Permanent magnet synchronous generator (PMSG) based WECS is implemented for its simplicity and high efficiency. The proposed control topology is designed and tested using MATLAB/Simulink

Implementation of Fuzzy Logic Controller with Different Membership Function Curves

Generally, the applications of power electronic are widely applied in the industrial, household, renewable energy fields, etc. Fuzzy Logic Controller is considered as an effective support control in the application because this implementation is very useful. Fuzzy Logic Controller is more reliable when compared to conventional control systems. This paper provides a Fuzzy Logic Controller based control method to identify the transformation of the membership function curve by using the dsPIC30F4012 microcontroller. In the implementation, the different membership function curves are adopted to obtain the maximum power output. The fuzzification process is needed to convert numerical numbers into fuzzy numbers. The other process is also required to convert the result of fuzzification process, it is called defuzzification process. To obtain the control system performance, the rule is defined in the rule base matrix. The experimental results were done to verify the analysis of Fuzzy Logic Controller.

An Intelligent Maximum Power Point Tracking Algorithm for Photovoltaic System

This work comprehensively demonstrates the performance analysis of Fuzzy Logic Controller (FLC) with Particle Swarm Optimization (PSO) Maximum Power Point Tracker (MPPT) algorithm on a stand-alone Photovoltaic (PV) applications systems. A PV panel, DC-DC Boost converter and resistive load was utilized as PV system. Three different MPPT algorithms were implemented in the converter. The result obtained from the converter was analyzed and compared to find the best algorithm to be used to identify the point in which maximum power can be achieve in a PV system. The objective is to reduce the time taken for the tracking of maximum power point of PV application system and minimize output power oscillation. The simulation was done by using MATLAB/Simulink with DC-DC Boost converter. The result shows that FLC method with PSO has achieved the fastest response time to track MPP and provide minimum oscillation compared to conventional P&O and FLC techniques.

Harmonic Analysis of Fuzzy Logic Controller Based Active Filter Unit Using Resonant Current Control in Distributed Power System

Wide-ranging utilize of nonlinear loads creates harmonic resonance issues in radial distribution system. Harmonic amplification occurring at different locations in the radial line are due to the behavior of active filter as a harmonic admittance rather conductance. This paper presents fuzzy logic controlled active filter by using resonant current control to damp a harmonic resonance. For controlling active filter as an approximately pure harmonic conductance, collections of different parallel band-pass filters are tuned for resonant current controller at harmonic frequencies. A MATLAB/SIMULINK results illustrate that the fuzzy logic controller based active filter improves higher damping performance correlated with alternative techniques.

A Critical Analysis of Fuzzy Logic Controller for Slip Control in Antilock Braking System (ABS)

This project aims at proposing an innovative way to implement the concept of fuzzy logic to an ABS model. The implementation of this project was conducted using simulation of ABS which is a combination from vehicle speed, wheel speed and slip through MATLAB Simulink software. By implementing fuzzy logic to the ABS system, the fuzzy logic can facilitate in improving the ABS abilities. The ABS model is developed and fuzzy logic controller is implemented to the model. The performance of the Fuzzy ABS is analyzed. The result shows that the fuzzy logic controller can facilitates the performance of the ABS by reducing the stopping time and maintaining the slip value near to 0.2.

Systematic design and analysis of fuzzy-logic control and application to robotics,: Part I. Modeling

A systematic methodology for synthesis and analysis of fuzzy-logic controllers is proposed in this paper (Part I) and its follow up (Part II) [M.R. Emami, et al., Robotics and Autonomous Systems 33 (2000) 89–108]. A robust model-based control structure is suggested that includes a fuzzy-logic inverse dynamics model and several robust fuzzy control rules. The model encapsulates the knowledge of the system dynamics in the form of IF–THEN rules. The paper focuses on how to obtain this knowledge systematically from the input–output data of a complex system; one that is ill-defined or contains complicated phenomena that are difficult to interpret analytically. All practical steps, from data acquisition to model validation, are illustrated using a four degree-of-freedom robot manipulator. Comparing the results with those of a complete analytical model and a heuristic fuzzy modeling technique illustrates the strength of the proposed methodology in terms of capturing effects that are difficult to model. In the follow-up paper, this model is used in the proposed control structure.

On the analysis of fuzzy logic controllers

Abstract In this paper we address the issue of analyzing the properties of the fuzzy logic controller (FLC). We introduce two basic models of the FLC. The first representation uses the concept of the quasilinear fuzzy model — the FLC is approximated by a virtual PID controller, consisting of linear controller connected in parallel. The second interpretation of the FLC is from the point of view of nonlinear control — the FLC is analyzed as a sliding mode — like controller. Based on these two alternative representations are derived rules for designing and tuning fuzzy logic controllers.