scholarly journals An Improved Fuzzy Logic Controller Design for PV Inverters Utilizing Differential Search Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Ammar Hussein Mutlag ◽  
Hussain Shareef ◽  
Azah Mohamed ◽  
M. A. Hannan ◽  
Jamal Abd Ali
Keyword(s):  
Fuzzy Logic ◽  
Objective Function ◽  
Output Voltage ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Search Algorithm ◽  
Design Procedure ◽  
Fast Response ◽  
Nonlinear Loads ◽  
Pv Inverter

This paper presents an adaptive fuzzy logic controller (FLC) design technique for photovoltaic (PV) inverters using differential search algorithm (DSA). This technique avoids the exhaustive traditional trial and error procedure in obtaining membership functions (MFs) used in conventional FLCs. This technique is implemented during the inverter design phase by generating adaptive MFs based on the evaluation results of the objective function formulated by the DSA. In this work, the mean square error (MSE) of the inverter output voltage is used as an objective function. The DSA optimizes the MFs such that the inverter provides the lowest MSE for output voltage and improves the performance of the PV inverter output in terms of amplitude and frequency. The design procedure and accuracy of the optimum FLC are illustrated and investigated using simulations conducted for a 3 kW three-phase inverter in a MATLAB/Simulink environment. Results show that the proposed controller can successfully obtain the desired output when different linear and nonlinear loads are connected to the system. Furthermore, the inverter has reasonably low steady state error and fast response to reference variation.

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

2019 ◽  
Vol 14 (2) ◽  
pp. 903 ◽  
Author(s):  
Mohd Faisal Farhan ◽  
Nor Sakinah Abdul Shukor ◽  
Mohd Ashraf Ahmad ◽  
Mohd Helmi Suid ◽  
Mohd Riduwan Ghazali ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Contact Force ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Essential Feature ◽  
Fast Response ◽  
Model Free ◽  
Catenary System ◽  
Three Degree Of Freedom

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

Autogeneration of Fuzzy Logic Rule-Base Controllers

2011 ◽  
Vol 110-116 ◽  
pp. 5123-5130
Author(s):  
M. O. Abdalla ◽  
T.A. Al–Jarrah
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Search Algorithm ◽  
Rule Base ◽  
The Novel ◽  
Binary Search Algorithm ◽  
And Performance ◽  
Control Application ◽  
Logic Rule

A novel Fuzzy Logic controller design methodology is presented. The method utilizes a Particle Swarm Optimization (PSO) binary search algorithm to generate the rules for the Fuzzy Logic controller rule-base stage without human experience intervention. The proposed technique is compared with the well established Lyapunov based Fuzzy Logic controller design in generating the rules. Finally, the controller’s effectiveness and performance are tested, verified and validated using an elevator control application. The novel controller’s results are to be compared with traditional Proportional Integral Derivative (PID) controller and classical Fuzzy Logic (FL) controllers.

Multi-objective adaptive cruise controller design using nonlinear predictive controller with the objective function with variable weights determined by fuzzy logic controller

2021 ◽  
pp. 095440702110147
Author(s):  
Behzad Samani ◽  
Amir H. Shamekhi
Keyword(s):  
Objective Function ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Hierarchical Control ◽  
Control Input ◽  
Cruise Control ◽  
Model Predictive Controller ◽  
Control Step ◽  
Predictive Controller

In this paper, an adaptive cruise control system with a hierarchical control structure is designed. The upper-level controller is a model predictive controller (MPC) that by minimizing an objective function in the presence of the constraints, calculates the desired acceleration as control input and sends it to the lower-level controller. So the lower-level controller, which is a fuzzy controller, determines the amount of throttle valve opening or brake pressure to get the car to this desired acceleration. The model predictive controller performs optimization at each control step to minimize the objective function and achieve the reference values. Usually, the objective function has predetermined and constant weights to meet objectives such as maintain the driver’s desired speed and increase safety and in some cases increase comfort and reduce fuel consumption. In this paper, it is suggested that instead of using constant weights in the objective function, these weights should be determined by a fuzzy controller, depending on the different conditions in which the car is placed. The simulation results show that the variability of the weights of the objective function achieves control objectives much better than the optimization of the objective function with constant weights.

scholarly journals Fuzzy Logic Based Controller For Buck Converter

2019 ◽  
Vol 1 (3) ◽  
pp. 1-12
Author(s):  
Habibullah Salim ◽  
Irma Husnaini ◽  
Asnil Asnil
Keyword(s):  
Fuzzy Logic ◽  
Solar Cell ◽  
Output Voltage ◽  
Fuzzy Logic Controller ◽  
Pulse Generation ◽  
Buck Converter ◽  
Dc Voltage ◽  
Generation Technique ◽  
Fuzzy Logic Method ◽  
The Stability

This research aims to make buck converter prototype for PLTS system by using fuzzy logic controller. Buck converter is required in the PLTS system if the required unidirectional voltage is smaller than the output voltage of the solar cell. Buck converter used to convert 24 Volt dc voltage to 12 Volt dc with 60 watt capability. While fuzzy logic controller is used to improve buck converter performance based on pulse generation technique for switching. The application of fuzzy logic method is expected to improve the performance of the system by maintaining the stability of buck converter output voltage of 12 volts and reduce the output ripple value. Atmega8535 microcontroller is used to generate PWM pulses for switching on power circuits. The results obtained from the test using a 100 Ohm 5 Watt load obtained the buck converter output voltage of 12.4 Volt.

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