Genetically tuned fuzzy controlled flywheel powered micro-grid for improved frequency control

2020 ◽  
pp. 0309524X2093254
Author(s):  
Saira Manzoor ◽  
Mairaj-ud-Din Mufti
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Frequency Deviation ◽  
Electrical Machine ◽  
Membership Functions ◽  
Micro Grid ◽  
Simulation Results ◽  
Operational Constraints ◽  
System Frequency

In this article, hybrid wind-diesel system is powered with a genetically tuned fuzzy controlled flywheel for improving its frequency control. Flywheel is interfaced with the system through an electrical machine (generator/motor) and an electronic converter for synchronization. Fuzzy logic controller for the flywheel is designed in such a way that it continuously controls the system frequency and simultaneously satisfies the operational constraints of flywheel. Fuzzy logic controller is optimized by genetically tuning its membership functions. Regulated variable based on frequency deviation of system and speed characteristics of flywheel is introduced to reach out to the optimized membership functions. Necessary modeling has been done and effectiveness of the assembly has been confirmed by the simulation results.

Frequency control of PV-connected micro grid system using fuzzy logic controller

2020 ◽  
Author(s):  
T. Rajesh ◽  
B. Gunapriya ◽  
M. Sabarimuthu ◽  
S. Karthikkumar ◽  
R. Raja ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Grid System ◽  
Micro Grid

Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

2019 ◽  
Vol 20 (1) ◽  
pp. 51-62
Author(s):  
Rajmeet Singh ◽  
Tarun Kumar Bera
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Bond Graph ◽  
Membership Functions ◽  
Current Position ◽  
Dc Motors

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

Fuzzy Logic Controller for Force Feedback Control of Quadcopter via Tether

2020 ◽  
Author(s):  
Bennett Breese ◽  
Drew Scott ◽  
Shraddha Barawkar ◽  
Manish Kumar
Keyword(s):  
Fuzzy Logic ◽  
Control Strategy ◽  
Fuzzy Logic Controller ◽  
Force Feedback ◽  
Power Transmission ◽  
Extensive Simulation ◽  
Control Scheme ◽  
Area Surveillance ◽  
Simulation Results ◽  
Long Endurance

Abstract Tethered drone systems can be used to perform long-endurance tasks such as area surveillance and relay stations for wireless communication. However, all the existing systems use tethers only for data and power transmission from a stationary point on the ground. This work presents a control strategy that enables a quadcopter to follow a moving tether anchor. A force feedback controller is implemented using Fuzzy Logic. Using force-based strategy provides effective compliance between the tether’s anchor and the drone. The drone can thus be controlled by mere physical movement/manipulation of tether. This enhances the safety of current tethered drone systems and simplifies the flying of drones. Fuzzy Logic provides an intuitive edge to the control of such systems and allows handling noise in force sensors. Extensive simulation results are presented in this paper showing the effectiveness of the proposed control scheme.

Design of fuzzy logic controller for load frequency control in an isolated hybrid power system

2020 ◽  
Vol 39 (6) ◽  
pp. 8273-8283
Author(s):  
N. Kirn Kumar ◽  
V. Indra Gandhi
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Pso Algorithm ◽  
Green Energy ◽  
Load Frequency Control ◽  
Control Technique ◽  
Hybrid Power System ◽  
Hybrid Power

As the world is moving towards green energy generation to reduce the pollution by renewable sources such as wind, solar, geothermal and more. These sources are intermittent in nature, to coordinate and control with traditional power generating units a control technique is necessary. This paper mainly focuses on the design of fuzzy based classical controller using a PSO algorithm for optimal controller gains to control the frequency variations in island hybrid power system. The considered mathematical model comprises of a diesel generating model, wind turbine generator and a battery storage system. Fuzzy is an intelligent controller which is designed with trial and error rules or on the basis of past experience provided by experts or by optimization methods for optimized gains using computational algorithms. To give best solution for these kinds of problems with FLCs traditional controllers are integrated with fuzzy logic. The PSO algorithm is applied to tune the classical controller gains to decrease the frequency deviation of the island power system, during the different load and wind disturbances. The Fuzzy PID classical controller shows the best performance compared with the only fuzzy and Fuzzy-PI controller configurations by illustrating the under shoot, overshoot and settling time and the proposed method is robust for various loading conditions and different wind changes.

scholarly journals Embedded Fuzzy Logic Controller and Wireless Communication for Home Energy Management Systems

Electronics ◽  
2018 ◽  
Vol 7 (9) ◽  
pp. 189 ◽  
Author(s):  
Aryuanto Soetedjo ◽  
Yusuf Nakhoda ◽  
Choirul Saleh
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Cost Reduction ◽  
Fuzzy Logic Controller ◽  
Management Systems ◽  
Fuzzy Membership ◽  
Membership Functions ◽  
Energy Management Systems ◽  
Fuzzy Membership Functions ◽  
Home Energy Management

Energy management systems in residential areas have attracted the attention of many researchers along the deployment of smart grids, smart cities, and smart homes. This paper presents the implementation of a Home Energy Management System (HEMS) based on the fuzzy logic controller. The objective of the proposed HEMS is to minimize electricity cost by managing the energy from the photovoltaic (PV) to supply home appliances in the grid-connected PV-battery system. A fuzzy logic controller is implemented on a low-cost embedded system to achieve the objective. The fuzzy logic controller is developed by the distributed approach where each home appliance has its own fuzzy logic controller. An automatic tuning of the fuzzy membership functions using the Genetic Algorithm is developed to improve performance. To exchange data between the controllers, wireless communication based on WiFi technology is adopted. The proposed configuration provides a simple effective technology that can be implemented in residential homes. The experimental results show that the proposed system achieves a fast processing time on a ten-second basis, which is fast enough for HEMS implementation. When tested under four different scenarios, the proposed fuzzy logic controller yields an average cost reduction of 10.933% compared to the system without a fuzzy logic controller. Furthermore, by tuning the fuzzy membership functions using the genetic algorithm, the average cost reduction increases to 12.493%.

Improvement of Power Quality for Microgrid using Fuzzy Based UPQC Controller

2015 ◽  
Vol 4 (2) ◽  
pp. 37
Author(s):  
Abdul Rasheed ◽  
G. Keshava Rao
Keyword(s):  
Fuzzy Logic ◽  
Power Systems ◽  
Power Quality ◽  
Fuzzy Logic Controller ◽  
Control Strategies ◽  
Renewable Energy Sources ◽  
Distributed Energy ◽  
Micro Grid ◽  
Hybrid Filters ◽  
Micro Grids

<p>Generally, the power systems are mainly effected by the continuous changes in operational requirement and increasing amount of distributed energy systems. This paper proposes a new concept of power-control strategies for a micro grid generation system for better transfer of power. The micro grids are obtained with the general renewable energy sources and this concept provides the maximum utilization of power at environmental free conditions with low losses; then the system efficiency is also improved. This paper proposes a single stage converter based micro grid to reduce the number of converters in an individual ac or dc grid. The proposed micro grid concept can work in both stand-alone mode and also in grid interfaced mode. The distortions that occur in power system due to changes in load or because of usage of non-linear loads, can be eliminated by using control strategies designed for shunt active hybrid filters such as series and shunt converters. A conventional Proportional Integral (PI) and Fuzzy Logic Controllers are used for power quality enhancement by reducing the distortions in the output power. The simulation results are compared among the two control strategies, that fuzzy logic controller and pi controller.</p>

Sign in / Sign up

Export Citation Format

Share Document