Current mode fuzzy based controller for multilevel inverter

Multilevel Inverter (MLI) has come to attention from industries for its practical and convenient solution especially in high power application. It produces staircase voltage waveform which gives more sinusoidal like waveform and as a result it has a lower THD percentage. Through the evolution in MLI topologies and advancement of power electronic devices, it become more viable technology and attracted wide interest for its number of advantages such as above. However, the selection of suitable switching technique to control the MLI has an effective and important role in generating an ideal output voltage that reduce the error as well as the harmonic content. A controller that been introduced into the system must has a characteristic of very fast and responsive, so that it will give more advantage to the MLI. This project will propose and design a current mode fuzzy based controller for five level cascaded multilevel inverter. It is a current mode-based control method offers good performance with faster response as compared to voltage mode control with an expense of additional current sensor. While, the employment of fuzzy control provides a better regulation performance with nonlinear load by manipulating the fuzzy logic structure through heuristic knowledge characteristic of the controller. Hence a system perform with tuneable controller is expected. To validate its performance, a simulation base on MATLAB/SIMULINK® will be conducted with a single phase five-level cascaded multilevel inverter where it been controlled by a proposed fuzzy controller in a current feedback loop. The results of the simulation were observed and analysed

Modelling, Simulation and Fuzzy Self-Tuning Control of D-STATCOM in a Single Machine Infinite Bus Power System

© 2019 Bentham Science Publishers. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.2174/2352096511666180314141205In recent years, demand for electricity has increased considerably, while the expansion of generation and transmission has been very slow due to limited investment in resources and environmental restrictions. Methods: As a result, the power system becomes vulnerable to disturbances and instability. FACTS (Flexible AC Transmission Systems) technology has now been accepted as a potential solution to this problem. This paper deals with the modelling, simulation and fuzzy self-tuning control of a D-STATCOM to enhance the stability and improve the critical fault clearing time(CCT) in a single machine infinite bus (SMIB).A detailed modelling of the D-STATCOM and comprehensive derivation of the fuzzy logic self-tuning control is presented. Results: The dynamic performance of the power system with the proposed control scheme is validated through in a simulation study carried out under Matlab/Simulink and SimPowerSystems toolbox. Conclusion: The results demonstrate a significant enhancement of the power system stability under the simulated fault conditions considered.Peer reviewe

Speed Control of a Single Taipei Mass Rapid Transit System Train by Using a Single Input Fuzzy Logic Controller

The purpose of this study was to design a speed controller for mass rapid transit (MRT) train by using a single input fuzzy logic controller (SIFLC). A complete train model, which was designed according to the design of a Taipei MRT train was used for analyzing both mechanical and electrical parts. The SIFLC was used for improving a fuzzy logic controller (FLC) by reducing its number of control rules. The results indicated that the SIFLC exhibited more favorable performance than the FLC did and a substantial reduction in the number of fuzzy rules and processing time. Therefore, tuning the SIFLC was easier compared with tuning the FLC; furthermore, the simulation time of the SIFLC was shorter than that of the FLC, exhibiting reductions of up to 17.3% in a constant track (track without gradient and curvature) and up to 12.27% in a variable track (track with gradient and curvature)

Design Nonlinear Model Reference with Fuzzy Controller for Nonlinear SISO Second Order Systems

Model reference controller is considering as one of the most useful controller to specific performance of systems where the desired output is produced for a given input. This system used the difference between the outputs of the plant and the desired model by comparing them to produce the signals of the control. This paper focus on design a model reference controller (MRC) combined with (type-1 and interval type-2) fuzzy control scheme for single input-single output (SISO) systems under uncertainty and external disturbance. The model reference controller is designed firstly without fuzzy scheme based on an optimal desired model and Lyapunov stability theory. Then a (type-1 and Interval type-2) fuzzy controller Takagi-Sugeno type is combine with the suggested MRC in order to enhance the performer of it, the common parts between the two fuzzy systems such as: fuzzifier, inference engine, fuzzy rule-base and defuzzifier are illustrated. In this paper the proposed controller is applied to controla (SISO) inverted pendulum sustem and the Matlab R2015 software is used to carry out two simulation cases for the overall controlled scheme. The obtained results for the two cases show that the proposed MRC with both fuzzy control schemes have acceptable performance, but it have better performance with the interval type-2 fuzzy scheme

Review on auto-depth control system for an unmanned underwater remotely operated vehicle (ROV) using intelligent controller

This paper presents a review of auto-depth control system for an Unmanned Underwater Remotely operated Vehicle (ROV), focusing on the Artificial Intelligent Controller Techniques. Specifically, Fuzzy Logic Controller (FLC) is utilized in auto-depth control system for the ROV. This review covered recently published documents for auto-depth control of an Unmanned Underwater Vehicle (UUV). This paper also describes the control issues in UUV especially for the ROV, which has inspired the authors to develop a new technique for auto-depth control of the ROV, called the SIFLC. This technique was the outcome of an investigation and tuning of two parameters, namely the break point and slope for the piecewise linear or slope for the linear approximation. Hardware comparison of the same concepts of ROV design was also discussed. The ROV design is for smallscale, open frame and lower speed. The review on auto-depth control system for ROV, provides insights for readers to design new techniques and algorithms for auto-depth control

A simplify fuzzy logic controller design based safe experimentation dynamics for pantograph-catenary system

Contact force between catenary and pantograph of high speed train is a crucial system to deliver power to the train. The inconsistence force between them can cause the contact wire oscillate a lot and it can damage the mechanical structure of system and produce electric arc that can reduce the performance of system. This project proposes a single-input fuzzy logic controller (SIFLC) to control the contact force between the pantograph-catenary by implement Safe Experimentation Dynamics (SED) method to tune the SIFLC parameters. The essential feature of SIFLC is that it is model-free type controller design with less pre-defined variables as compared to other existing model-based controllers. The performance of the SIFLC is analyzed in terms of input tracking of contact force of pantograph-catenary and time response specifications. A simplified model of three degree of freedom (3-DOF) pantograph-catenary system is considered. In this study, the simulation result shows that the SIFLC successfully track the given contact force with less overshoot with percentage different of peak to peak response from actual force 2% and fast response within 5.27s

Control of brushless DC motor using siingle-input fuzzy proportional-integral controller

Over the years, development in control industry has brought a hybrid controller, Fuzzy Proportional-Integral (PI) Controller (FPIC) as Brushless DC (BLDC) motor speed regulator with as good performance as PI controller. The FPIC suffers from lengthy design time due to the large number of rules and parameter tuning. Thus, this thesis proposes a newly developed Single-Input Fuzzy PI Controller (SIFPIC) to be used as the BLDC motor speed controller. SIFPIC is a simplified version of FPIC with one input variable derived using signed distance method. SIFPIC gives a speed performance comparable to the FPIC but with much faster computing time and simpler tuning process. The motor performance with SIFPIC is evaluated through simulation and experimental approach in terms of speed, current and torque response under several test conditions. The performance is then compared with the motor performance with discrete PI and FPIC speed controller. FPIC is excluded from the comparison in the experiment due to the limitation of DS1104 Digital Signal Processor. From the simulation conducted, SIFPIC produced a comparable performance as FPIC in speed response where both controllers eliminated undershoot and oscillation problems. Under constant speed and changing speed conditions, SIFPIC also showed it superiority from discrete PI controller with average of 36.3% and 11.7% lower ripples than discrete PI controller, respectively. The simulation findings have been verified by the experimental results

Review on Auto-Depth Control System for an Unmanned Underwater Remotely Operated Vehicle (ROV) using Intelligent Controller

This paper presents a review of auto-depth control system for an Unmanned Underwater Remotely operated Vehicle (ROV), focusing on the Artificial Intelligent Controller Techniques. Specifically, Fuzzy Logic Controller (FLC) is utilized in auto-depth control system for the ROV. This review covered recently published documents for auto-depth control of an Unmanned Underwater Vehicle (UUV). This paper also describes the control issues in UUV especially for the ROV, which has inspired the authors to develop a new technique for auto-depth control of the ROV, called the SIFLC. This technique was the outcome of an investigation and tuning of two parameters, namely the break point and slope for the piecewise linear or slope for the linear approximation. Hardware comparison of the same concepts of ROV design was also discussed. The ROV design is for smallscale, open frame and lower speed. The review on auto-depth control system for ROV, provides insights for readers to design new techniques and algorithms for auto-depth contro

Review on Auto-Depth Control System for an Unmanned Underwater Remotely Operated Vehicle (ROV) using Intelligent Controller

This paper presents a review of auto-depth control system for an Unmanned Underwater Remotely operated Vehicle (ROV), focusing on the Artificial Intelligent Controller Techniques. Specifically, Fuzzy Logic Controller (FLC) is utilized in auto-depth control system for the ROV. This review covered recently published documents for auto-depth control of an Unmanned Underwater Vehicle (UUV). This paper also describes the control issues in UUV especially for the ROV, which has inspired the authors to develop a new technique for auto-depth control of the ROV, called the SIFLC. This technique was the outcome of an investigation and tuning of two parameters, namely the break point and slope for the piecewise linear or slope for the linear approximation. Hardware comparison of the same concepts of ROV design was also discussed. The ROV design is for smallscale, open frame and lower speed. The review on auto-depth control system for ROV, provides insights for readers to design new techniques and algorithms for auto-depth contro