Performance Of Fuzzy Logic Controller Research Articles

Power Management Strategy for Battery Electric Vehicles

This study presents a novel power management strategy (PMS) for a small urban electric vehicle. Enhancing battery electric vehicles driving range and their batteries’ lifetime are possible through developing a more effective PMS for them. Fuzzy logic control (FLC) is proposed to control the power control unit (PCU) of the battery management system. The control devices used are verified and experimented by simulations to evaluate their performance using the MATLAB software. The good performance of FLC can be observed in terms of settling time and peak overshoot from the simulations result. The simulation results show that the proposed PCU can decrease the energy loss inside the battery and increase the battery lifetime.

Fuzzy Logic Control of SLMMC-Based SAPF Under Nonlinear Loads

This work proposes fuzzy logic controller (FLC) for seven-level modular multilevel converter (SLMMC)-based shunt active power filter (SAPF) to reduce harmonics in source current. Half-bridge submodule is proposed for SLMMC due to its simple configuration and low conduction losses. An instantaneous real and reactive power (IPQ) method is proposed to extract reference currents. The multicarrier-based in-phase disposition (IPD) pulse width modulation method is proposed to control the switches in efficient approach. The performance of FLC in SLMMC and seven-level cascade H-bridge SAPF is verified in terms of harmonic reduction under nonlinear loads. The capacitor voltage balancing is achieved using the proposed FLC. The proposed work is simulated using MATLAB/Simulink software package.

Adaptive Fuzzy Logic Controllers Using Hybrid Genetic Algorithms

In this paper, an integration of fuzzy logic controllers (FLCs) with hybrid genetic algorithms (HGAs) is developed with a view to make the design process fully automatic, without requiring any human expert and numerical data. Our approach consists of two phases: first phase involves selection and definition of fuzzy control rules as well as adjustment of membership functions parameters, while the second phase performs an optimal selection of membership function types corresponding to fuzzy control rules. Learning both parts concurrently represents a way to improve the accuracy of the FLCs to minimize the errors. It has been argued that the performance of FLCs greatly depends on the parameters as well as types of membership functions. Thus, the aforementioned HGAs are a viable solution for designing an efficient adaptive FLCs system. To demonstrate the effectiveness of the proposed method for optimal design of the FLCs, the proposed approach is applied to a well-known benchmark controller design tasks, car and truck-and-trailer like robot system. Simulation results illustrates that proposed optimization approach can find optimal fuzzy rules and their corresponding membership functions types with a high rate of accuracy. The new HGAs optimized adaptive FLCs outperforms not only a passive control strategy but also human-designed FLCs, a neural coded controller with clustering and a neural-fuzzy control algorithm.

Performance Assessment of Fuzzy Logic Controller for Load Frequency Control in multi source multi area system

This article confers the performance of Fuzzy logic controller for Load Frequency Control (LFC) in multi-source multi area power system .The suggested multi area systems are studied for various operating load conditions to realize the deviations found in system frequency and the interchange power through tie-line. The distinct energy sources include hydro, thermal, wind and diesel power plants. The system models are compared for the conventional PI controller and suggested fuzzy logic controller. It is remarked from the simulation results that the proposed fuzzy logic controller contributes superior dynamic response over conventional controller.

An approach for parameterized shadowed type-2 fuzzy membership functions applied in control applications

At present time, general type-2 fuzzy logic provides better uncertainty modeling when compared to interval type-2 fuzzy logic, and this has been shown with the improvement in the performance of fuzzy logic controllers and fuzzy edge detectors. However, higher computational cost represents a limitation for many applications and implementation platforms, and it is because of this that the computational cost reduction is the main goal of this paper. The aim of this work is to model a GT2 FLS based on shadowed type-2 fuzzy sets (ST2 FS) and apply this approach to control problems. The ST2 FS consists of approximating the secondary membership function by shadowed sets and is because of this, that we present an analytic approach to obtain the shadowed set for triangular and Gaussian membership functions for any parameters. Based on this, we achieve a representation of the ST2 FS as a parameterized function, facilitating its implementation. The results are compared against the performance when a generalized type-2 fuzzy inference system is approximated using α-planes for control applications.

Development of Fuzzy Logic Control for Indoor Lighting Using LEDs Group

This paper presents the design and the development of an indoor lighting control based on fuzzy logic controller (FLC). The objective of this study is to demonstrate how the FLC can optimize the lighting based on indoor and outdoor lighting environments. The FLC system uses two inputs with Light Dependent Resistors (LDR) as a sensor at indoor and outdoor lighting environments. The output is Light Emitting Diodes (LEDs) to provide lighting at the room automatically. The Pulse Width Modulation (PWM) is used to adjust the LEDs lighting in the room. FLC has successfully demonstrated performance to control the output of LEDs as needed. If the LDR 1 input as indoor sensor shows dim, it will automatically turn on brightly. The MSE values for simulation and experiment of LDR 1 and LDR 2 were 34.42 and 30.11 respectively. The results of FLC performance in the simulation work are further validated by an experimental work. Experimental results show similarities compared to the simulation results.

PID and Fuzzy Logic Controller Design for Balancing Robot Stabilization

This paper addresses the problem of position control and stabilization for the two wheeled balancing robot. A mathematical model is derived based on the robot’s position and tilt angle and a fuzzy logic control is proposed for the balancing robot control. The fuzzy logic controller performance is compared with a conventional PID controller to show the difference between them. Both controllers were tested on the balancing robot in simulation using MATLAB software and the results were put together for a comparative point of view. The simulations shows a relative advantage for the fuzzy logic controller over the conventional PID controller especially in reducing the time required for stabilization which takes about 2 seconds and almost without overshoot while in the PID case the robot will have about 10% overshoot in position and about 20 degrees in tilt angle.

Fuzzy Control of Active Suspension System Using Full Car Model

Fuzzy logic technique has been proposed to control full car model based active suspension system. The full car model has been used to simulate the mathematical model of active suspension system. The performance of proposed controller mainly depends on body displacement, acceleration, roll and pitch angle of full car model. But the roll and pitch angle cannot be measured in quarter car model of active suspension system. The dynamic nature of suspension system and complex nonlinear characteristics of actuating system has increased the difficulty of creating mathematical model for active suspension system. In real time, the controller designed based on analytical method will not give better result due to its complex mathematical model. The fuzzy logic technique has able to give better performance for active suspension system irrespective of the complex nature of mathematical model of suspension system. This paper describes mathematical model of suspension system with fuzzy controller in order to obtain vehicle response for range of road input. The result of simulation will confirm the performance of fuzzy logic controller for active suspension system.DOI: http://dx.doi.org/10.5755/j01.mech.24.2.17457

Line Follower Robot Optimization based Fuzzy Logic Controller Using Membership Function Tuning

The study was aimed to measure the performance of Fuzzy Logic Controller (FLC) on Line Follower Robot (LFR). FLC output is a deviation value of Pulse Width Modulation (PWM) to determine the rotational speed of the left and the right wheel. As input variables are current and previous line sensors. Tuning was applied to input and output variables in each membership function (MF) to conduct the best performance. This study used triangular membership function that consists of three MF. Mamdani Fuzzy Inference System (FIS) is used using nine rules. The result obtains that after MF tuning, the performance of the LFR settling time is 0.63s faster compare to that without tuning.

Fuzzy Takagi-Sugeno Method in Microcontroller Based Water Tank System

This paper present the performance of Fuzzy logic controller in maintain level of water in water tank system. The mathematical modelling was developed to get the initial idea of the system performance. Later, the prototype of water tank system were constructed and tested to get the real time results. The Takagi-Sugeno “on” and “off” interference technique method was implemented due to the control limitation of the pump motor that being used in the experimental setup. The fuzzy logic controller was realized by embedded the algorithm in microcontroller of the water tank system. The experimental results show acceptable level of water within the range of 18cm to 20.5cm and settling time 59 seconds with 20 cm set point.

Single axis control of ball position in magnetic levitation system using fuzzy logic control

This paper presents the design and real time implementation of Fuzzy logic control(FLC) for the control of the position of a ferromagnetic ball by manipulating the current flowing in an electromagnet that changes the magnetic field acting on the ball. This system is highly nonlinear and open loop unstable. Many un-measurable disturbances are also acting on the system, making the control of it highly complex but interesting for any researcher in control system domain. First the system is modelled using the fundamental laws, which gives a nonlinear equation. The nonlinear model is then linearized at an operating point. Fuzzy logic controller is designed after studying the system in closed loop under PID control action. The controller is then implemented in real time using Simulink real time environment. The controller is tuned manually to get a stable and robust performance. The set point tracking performance of FLC and PID controllers were compared and analyzed.

Type-2 fuzzy elliptic membership functions for modeling uncertainty

Whereas type-1 and type-2 membership functions (MFs) are the core of any fuzzy logic system, there are no performance criteria available to evaluate the goodness or correctness of the fuzzy MFs. In this paper, we make extensive analysis in terms of the capability of type-2 elliptic fuzzy MFs in modeling uncertainty. Having decoupled parameters for its support and width, elliptic MFs are unique amongst existing type-2 fuzzy MFs. In this investigation, the uncertainty distribution along the elliptic MF support is studied, and a detailed analysis is given to compare and contrast its performance with existing type-2 fuzzy MFs. Furthermore, fuzzy arithmetic operations are also investigated, and our finding is that the elliptic MF has similar features to the Gaussian and triangular MFs in addition and multiplication operations. Moreover, we have tested the prediction capability of elliptic MFs using interval type-2 fuzzy logic systems on oil price prediction problem for a data set from 2nd Jan 1985 till 25th April 2016. Throughout the simulation studies, an extreme learning machine is used to train the interval type-2 fuzzy logic system. The prediction results show that, in addition to their various advantages mentioned above, elliptic MFs have comparable prediction results when compared to Gaussian and triangular MFs. Finally, in order to test the performance of fuzzy logic controller with elliptic interval type-2 MFs, extensive real-time experiments are conducted for the 3D trajectory tracking problem of a quadrotor. We believe that the results of this study will open the doors to elliptic MFs’ wider use of real-world identification and control applications as the proposed MF is easy to interpret in addition to its unique features.

Development of Fuzzy Logic Controller for Quanser Bench-Top Helicopter

Bench–top helicopter is a laboratory scale helicopter that usually used as a testing bench of the real helicopter behavior. This helicopter is a 3 Degree of Freedom (DOF) helicopter which works by three different axes wshich are elevation, pitch and travel. Thus, fuzzy logic controller has been proposed to be implemented into Quanser bench-top helicopter because of its ability to work with non-linear system. The objective for this project is to design and apply fuzzy logic controller for Quanser bench-top helicopter. Other than that, fuzzy logic controller performance system has been simulated to analyze and verify its behavior over existing PID controller by using Matlab & Simulink software. In this research, fuzzy logic controller has been designed to control the elevation angle. After simulation has been performed, it can be seen that simulation result shows that fuzzy logic elevation control is working for 4°, 5° and 6°. These three angles produce zero steady state error and has a fast response. Other than that, performance comparisons have been performed between fuzzy logic controller and PID controller. Fuzzy logic elevation control has a better performance compared to PID controller where lower percentage overshoot and faster settling time have been achieved in 4°, 5° and 6° step response test. Both controller are have zero steady state error but fuzzy logic controller is managed to produce a better performance in term of settling time and percentage overshoot which make the proposed controller is reliable compared to the existing PID controller.

Design and Implementation of Optimized Fuzzy Logic Controller for a Nonlinear Dynamic Industrial Plant Using Hysys and Matlab Simulation Packages

A fuzzy logic controller (FLC) is appropriate for systems with high complexity and nonlinearity. FLC is implemented directly on a chemical process simulator in dynamic mode to handle some uncertainty of the system. Also because accurate tuning of the fuzzy membership functions (MFs) is difficult and has an important effect on FLC performance, particle swarm optimization (PSO) is utilized. To display capability of this method, FLC is optimized with PSO. Next PSO-FLC is used to control pressure of a distillation column in an ethane plus recovery process in dynamic mode. Results show that the proposed method can use PSO-FLC in the Hysys dynamic efficiently.

A Comparison between Fuzzy-PSO Controller and PID-PSO Controller for Controlling a DC Motor

The Direct current motors are in different types and there are several methods for controlling of their speed. In this paper two ways for speed controlling suggested. First a fuzzy logic speed controller for DC motor is designed and it’s parameter calculated by Particle Sward Optimization (PSO). The speed controller designed according to fuzzy rules, then for having better performance, the controller optimized with PSO. Secondly a PID controller that it’s parameter find by PSO, is used for speed controlling of a DC motor. At the end the performance of fuzzy logic controller compared with PID controller. The results show that fuzzy-PSO controller has better performance.

Fuzzy Logic Control of Centralized Chilled Water System

Fuzzy logic controller has been proven to control nonlinear process system and HVAC is a type of nonlinear process systems. This paper studies the performance of fuzzy logic controller with three and five term membership function in centralized chilled water system. Three different cases are simulated and analyzed for both type of controllers. Results show that the performances between both controllers are almost similar with no significant difference. It is also encountered that in certain cases, 3-mf fuzzy logic controller outperformed 5-mf fuzzy logic controller.

Active Control of Thermally Induced Vibrations in Smart Structure Instrumented with Piezoelectric Materials

In this paper, a finite element model of piezolaminated composite shell structure is developed using nine-noded degenerated shell element. The stiffness, mass and thermo-electro-mechanical coupling effect is incorporated in finite element modeling using first order shear deformation theory and linear piezoelectric theory. The sensor voltage is calculated using the same formulation and fuzzy logic controller is used to calculate the actuator voltage. The fuzzy logic controller is designed as double input-single output (DISO) system using 49 If-Then rules. The performance of fuzzy logic controller is compared with convention constant-gain negative feedback controller. The simulation results illustrate the superiority of fuzzy logic controller over constant-gain negative feedback controller.

An Educational Tool for the Genetic Algorithm-Based Fuzzy Logic Controller of a Permanent Magnet Synchronous Motor Drive

In this study, a novel educational tool is introduced for the genetic algorithm (GA)-based fuzzy logic controller (FLC) of a permanent magnet synchronous motor (PMSM) drive. This tool provides the operating principle of PMSM, essentials of GAs, and effects of FLC parameters on the performance of GA-based FLC. The proposed educational tool regarding GA-based FLC is a unique one in its field in the literature, as such a computer-based study aiming to teach the corresponding intelligent system has not been studied before, though both GA and FLC are well-known powerful techniques. The graphical interface, developed in Microsoft Visual C#. NET platform, has a flexible and functional structure. By changing motor operating conditions as well as GA and controller parameters, useful practices can be done on the whole system under various situations without wasting time. An evaluation of the tool is given based on student feedback.

MODELING AND SIMULATION OF ROTOR FLUX OBSERVER BASED INDIRECT VECTOR CONTROL OF INDUCTION MOTOR DRIVE USING FUZZY LOGIC CONTROL

The indirect vector controlled inductor motor (IM) drive involves decoupling of the stator current into torque and flux producing components. This paper proposes the implementation of fuzzy logic control scheme applied to a two d-q current components model of an induction motor. A Fuzzy logic Controller is developed with the help of knowledge rule base for efficient and robust control. The performance of Fuzzy Logic Controller is compared with that of the PI controller with rotor flux observer in terms of the settling time and dynamic response to sudden load changes. The harmonic pattern of the output current is evaluated for both fixed gain proportional integral controller and the Fuzzy Logic based controller. The performance of the IM drive has been analyzed under steady state and transient conditions. Simulation results of both the controllers are presented for comparison.

Fuzzy Logic Control of Double-Fed Induction Generator Wind Turbine

This paper presents fuzzy logic control of Doubly Fed Induction Generator (DFIG) wind turbine in a sample power system. First, a mathematical model of the doubly fed induction generator written in an appropriate d-q reference frame is established to investigate simulations. In order to control the rotor currents of DFIG, a power active and reactive control law is synthesized using PI controllers. Then, the performances of fuzzy logic controller (FLC) are investigated and compared to those obtained from the PI controller. Results obtained in Matlab/Simulink environment show that the FLC is more robust, prove excellent performance for the control unit by improving power quality and stability of wind turbine.