Abstract: One of the major power quality concerns in modern times is the problem of current harmonics. The current harmonics is caused due to the increase in non-linear loads which is largely dominated by power electronics devices. The Shunt active filtering is one of the best solutions for mitigating current harmonics. This paper describes a fuzzy logic controller based (FLC) based three Phase Shunt active Filter to achieve low current harmonic distortion (THD) and Reactive power compensation. The performance of fuzzy logic controller is analysed under both balanced sinusoidal and unbalanced sinusoidal source condition. The above controller serves the purpose of maintaining DC Capacitor Voltage constant. The proposed shunt active filter uses hysteresis current controller for current control of IGBT based PWM inverter. The simulation results of model in Simulink MATLAB reveals satisfying results.
Abstract: Multilevel inverter is a promising inverter topology for high voltage and high power applications. This inverter synthesizes several different levels of DC voltages to produce a stepped AC output that approaches the pure sine waveform. The three different topologies, diode-clamped inverter, capacitor-clamped inverter and cascaded h-bridge multilevel inverter are widely used in these multilevel inverters. Among the three topologies, cascaded h-bridge multilevel inverter is more suitable for photovoltaic applications since each PV array can act as a separate dc source for each h-bridge module. This research especially focus on photovoltaic power source as input to the system and shows the potential of a Single Phase Cascaded H-bridge Eleven level inverter governed by the fuzzy logic controller to improve the power quality by reducing the total harmonic distortion at the output voltage. Hence the efficiency of the system will be improved. Simulation using MATLAB/SIMULINK has been done to verify the performance of cascaded h-bridge eleven level inverter using sinusoidal pulse width modulation technique. The simulated output shows very favorable result.
Abstract: In an interconnected power system, any sudden small
load perturbation in any of the interconnected areas causes the
deviation of the area frequencies, the tie line power and voltage
deviation at the generator terminals. This paper deals with the study
of performance of intelligent Fuzzy Logic controllers coupled with
Conventional Controllers (PI and PID) for Load Frequency Control.
For analysis, an isolated single area and interconnected two area
thermal power systems with and without generation rate constraints
(GRC) have been considered. The studies have been performed with
conventional PI and PID controllers and their performance has been
compared with intelligent fuzzy controllers. It can be demonstrated
that these controllers can successfully bring back the excursions in
area frequencies and tie line powers within acceptable limits in
smaller time periods and with lesser transients as compared to the
performance of conventional controllers under same load disturbance
conditions. The simulations in MATLAB have been used for
comparative studies.
Abstract: In this study an active controller is presented for vibration suppression of a full-bus model. The bus is modeled having seven degrees of freedom. Using the achieved model via Lagrange Equations the system equations of motion are derived. The suspensions of the bus model include air springs with two auxiliary chambers are used. Fuzzy logic controller is used to improve the ride comfort. The numerical results, verifies that the presented fuzzy logic controller improves the ride comfort.
Abstract: In this paper the design, development and testing of a stabilizer control system for a Quad-rotor is presented which is focused on the maneuverability. The mechanical design is performed along with the design of the controlling algorithm which is devised using fuzzy logic controller. The inputs for the system are the angular positions and angular rates of the Quad-rotor relative to three axes. Then the output data is filtered from an accelerometer and a gyroscope through a Kalman filter. In the development of the stability controlling system Mandani fuzzy model is incorporated. The results prove that the fuzzy based stabilizer control system is superior in high dynamic disturbances compared to the traditional systems which use PID integrated stabilizer control systems.
Abstract: This paper presents a new control scheme to control a brushless doubly fed induction generator (BDFIG) using back-to-back PWM converters for wind power generation. The proposed control scheme is a New Self-Tuning Fuzzy Proportional-Derivative Controller (NSTFPDC). The goal of BDFIG control is to achieve a similar dynamic performance to the doubly fed induction generator (DFIG), exploiting the well-known induction machine vector control philosophy. The performance of NSTFPDC controller has been investigated and compared with the two controllers, called Proportional–Integral (PI) and PD-like Fuzzy Logic controller (PD-like FLC) based BDFIG. The simulation results demonstrate the effectiveness and the robustness of the NSTFPDC controller.
Abstract: This paper is based on the bridgeless single-phase Ac–Dc Power Factor Correction (PFC) converters with Fuzzy Logic Controller. High frequency isolated Cuk converters are used as a modular dc-dc converter in Discontinuous Conduction Mode (DCM) of operation of Power Factor Correction. The aim of this paper is to simplify the program complexity of the controller by reducing the number of fuzzy sets of the Membership Functions (MFs) and to improve the efficiency and to eliminate the power quality problems. The output of Fuzzy controller is compared with High frequency triangular wave to generate PWM gating signals of Cuk converter. The proposed topologies are designed to work in Discontinuous Conduction Mode (DCM) to achieve a unity power factor and low total harmonic distortion of the input current. The Fuzzy Logic Controller gives additional advantages such as accurate result, uncertainty and imprecision and automatic control circuitry. Performance comparisons between the proposed and conventional controllers and circuits are performed based on circuit simulations.
Abstract: This paper demonstrates the potential of applying PD-like fuzzy logic controller for active vibration control of piezoelectric Stewart platforms. Through simulation, the control authority of the piezo stack actuators for effectively damping the Stewart platform vibration can be evaluated for further implementation of the system. Each leg of the piezoelectric Stewart platform consists of a linear piezo stack actuator, a collocated velocity sensor, a collocated displacement sensor and flexible tips for the connections with the two end plates. The piezoelectric stack is modeled as a bar element and the electro-mechanical coupling property is simulated using Matlab/Simulink software. Then, the open loop and closed loop dynamic responses are performed for the system to characterize the effect of the control on the vibration of the piezoelectric Stewart platform. A significant improvement in the damping of the structure can be observed by using the PD-like fuzzy controller.
Abstract: Modern industrial processes are based on a large amount of electronic devices such as programmable logic controllers and adjustable speed drives. Unfortunately, electronic devices are sensitive to disturbances, and thus, industrial loads become less tolerant to power quality problems such as sags, swells, and harmonics. Voltage sags are an important power quality problem. In this paper proposed a new configuration of Static Var Compensator (SVC) considering three different conditions named as topologies and Booster transformer with fuzzy logic based controller, capable of compensating for power quality problems associated with voltage sags and maintaining a prescribed level of voltage profile. Fuzzy logic controller is designed to achieve the firing angles for SVC such that it maintains voltage profile. The online monitoring system for voltage sag mitigation in the laboratory using the hardware is used. The results are presented from the performance of each topology and Booster transformer considered in this paper.
Abstract: This paper is based on the performance of the Switched Reluctance Motor (SRM) drives using Z-Source Inverter with the simplified rule base of Fuzzy Logic Controller (FLC) with the output scaling factor (SF) self-tuning mechanism are proposed. The aim of this paper is to simplify the program complexity of the controller by reducing the number of fuzzy sets of the membership functions (MFs) without losing the system performance and stability via the adjustable controller gain. ZSI exhibits both voltage-buck and voltage-boost capability. It reduces line harmonics, improves reliability, and extends output voltage range. The output SF of the controller can be tuned continuously by a gain updating factor, whose value is derived from fuzzy logic, with the plant error and error change ratio as input variables. Then the results, carried out on a four-phase 6/8 pole SRM based on the dSPACEDS1104 platform, to show the feasibility and effectiveness of the devised methods and also performance of the proposed controllers will be compared with conventional counterpart.
Abstract: The purpose of suspension system in automobiles is to
improve the ride comfort and road handling. In this research the ride
and handling performance of a specific automobile with passive
suspension system is compared to a proposed fuzzy logic semi active
suspension system designed for that automobile. The bodysuspension-
wheel system is modeled as a two degree of freedom
quarter car model. MATLAB/SIMULINK [1] was used for
simulation and controller design. The fuzzy logic controller is based
on two inputs namely suspension velocity and body velocity. The
output of the fuzzy controller is the damping coefficient of the
variable damper. The result shows improvement over passive
suspension method.
Abstract: This paper presents design and implements a voltage
source inverter type space vector pulse width modulation (SVPWM)
for control a speed of induction motor. This scheme leads to be able
to adjust the speed of the motor by control the frequency and
amplitude of the stator voltage, the ratio of stator voltage to
frequency should be kept constant. The fuzzy logic controller is also
introduced to the system for keeping the motor speed to be constant
when the load varies. The experimental results in testing the 0.22 kW
induction motor from no-load condition to rated condition show the
effectiveness of the proposed control scheme.
Abstract: The objective of this study is to present the test
results of variable air volume (VAV) air conditioning system
optimized by two objective genetic algorithm (GA). The objective
functions are energy savings and thermal comfort. The optimal set
points for fuzzy logic controller (FLC) are the supply air temperature
(Ts), the supply duct static pressure (Ps), the chilled water
temperature (Tw), and zone temperature (Tz) that is taken as the
problem variables. Supply airflow rate and chilled water flow rate are
considered to be the constraints. The optimal set point values are
obtained from GA process and assigned into fuzzy logic controller
(FLC) in order to conserve energy and maintain thermal comfort in
real time VAV air conditioning system. A VAV air conditioning
system with FLC installed in a software laboratory has been taken for
the purpose of energy analysis. The total energy saving obtained in
VAV GA optimization system with FLC compared with constant air
volume (CAV) system is expected to achieve 31.5%. The optimal
duct static pressure obtained through Genetic fuzzy methodology
attributes to better air distribution by delivering the optimal quantity
of supply air to the conditioned space. This combination enhanced
the advantages of uniform air distribution, thermal comfort and
improved energy savings potential.
Abstract: This paper presents a new technique of compensation
of the effect of variation parameters in the direct field oriented
control of induction motor. The proposed method uses an adaptive
tuning of the value of synchronous speed to obtain the robustness for
the field oriented control. We show that this adaptive tuning allows
having robustness for direct field oriented control to changes in rotor
resistance, load torque and rotational speed. The effectiveness of the
proposed control scheme is verified by numerical simulations. The
numerical validation results of the proposed scheme have presented
good performances compared to the usual direct-field oriented
control.
Abstract: This paper presents three-phase evolution search methodology to automatically design fuzzy logic controllers (FLCs) that can work in a wide range of operating conditions. These include varying load, parameter variations, and unknown external disturbances. The three-phase scheme consists of an exploration phase, an exploitation phase and a robustness phase. The first two phases search for FLC with high accuracy performances while the last phase aims at obtaining FLC providing the best compromise between the accuracy and robustness performances. Simulations were performed for direct-drive two-axis robot arm. The evolved FLC with the proposed design technique found to provide a very satisfactory performance under the wide range of operation conditions and to overcome problem associated with coupling and nonlinearities characteristics inherent to robot arms.
Abstract: In this article we address the problem of mobile robot formation control. Indeed, the most work, in this domain, have studied extensively classical control for keeping a formation of mobile robots. In this work, we design an FLC (Fuzzy logic Controller) controller for separation and bearing control (SBC). Indeed, the leader mobile robot is controlled to follow an arbitrary reference path, and the follower mobile robot use the FSBC (Fuzzy Separation and Bearing Control) to keep constant relative distance and constant angle to the leader robot. The efficiency and simplicity of this control law has been proven by simulation on different situation.
Abstract: This paper presents the use of the predictive fuzzy logic controller (PFLC) applied to attitude control system for agile micro-satellite. In order to reduce the effect of unpredictable time delays and large uncertainties, the algorithm employs predictive control to predict the attitude of the satellite. Comparison of the PFLC and conventional fuzzy logic controller (FLC) is presented to evaluate the performance of the control system during attitude maneuver. The two proposed models have been analyzed with the same level of noise and external disturbances. Simulation results demonstrated the feasibility and advantages of the PFLC on the attitude determination and control system (ADCS) of agile satellite.
Abstract: FACTS devices are used to control the power flow, to
increase the transmission capacity and to optimize the stability of the
power system. One of the most widely used FACTS devices is
Unified Power Flow Controller (UPFC). The controller used in the
control mechanism has a significantly effects on controlling of the
power flow and enhancing the system stability of UPFC. According
to this, the capability of UPFC is observed by using different control
mechanisms based on P, PI, PID and fuzzy logic controllers (FLC) in
this study. FLC was developed by taking consideration of Takagi-
Sugeno inference system in the decision process and Sugeno-s
weighted average method in the defuzzification process. Case studies
with different operating conditions are applied to prove the ability of
UPFC on controlling the power flow and the effectiveness of
controllers on the performance of UPFC. PSCAD/EMTDC program
is used to create the FLC and to simulate UPFC model.
Abstract: An integrated vehicle dynamics control system is developed in this paper by a combination of active front steering (AFS) and direct yaw-moment control (DYC) based on fuzzy logic control. The control system has a hierarchical structure consisting of two layers. A fuzzy logic controller is used in the upper layer (yaw rate controller) to keep the yaw rate in its desired value. The yaw rate error and its rate of change are applied to the upper controlling layer as inputs, where the direct yaw moment control signal and the steering angle correction of the front wheels are the outputs. In the lower layer (fuzzy integrator), a fuzzy logic controller is designed based on the working region of the lateral tire forces. Depending on the directions of the lateral forces at the front wheels, a switching function is activated to adjust the scaling factor of the fuzzy logic controller. Using a nonlinear seven degrees of freedom vehicle model, the simulation results illustrate considerable improvements which are achieved in vehicle handling through the integrated AFS/DYC control system in comparison with the individual AFS or DYC controllers.
Abstract: This paper presents an approach for the design of
fuzzy logic power system stabilizers using genetic algorithms. In the
proposed fuzzy expert system, speed deviation and its derivative
have been selected as fuzzy inputs. In this approach the parameters of
the fuzzy logic controllers have been tuned using genetic algorithm.
Incorporation of GA in the design of fuzzy logic power system
stabilizer will add an intelligent dimension to the stabilizer and
significantly reduces computational time in the design process. It is
shown in this paper that the system dynamic performance can be
improved significantly by incorporating a genetic-based searching
mechanism. To demonstrate the robustness of the genetic based
fuzzy logic power system stabilizer (GFLPSS), simulation studies on
multimachine system subjected to small perturbation and three-phase
fault have been carried out. Simulation results show the superiority
and robustness of GA based power system stabilizer as compare to
conventionally tuned controller to enhance system dynamic
performance over a wide range of operating conditions.