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: In this study, the performance of a high-frequency arc
welding machine including a two-switch inverter is analyzed. The
control of the system is achieved using two different control
techniques i- fuzzy logic control (FLC) ii- state space averaging
based sliding control. Fuzzy logic control does not need accurate
mathematical model of a plant and can be used in nonlinear
applications. The second method needs the mathematical model of
the system. In this method the state space equations of the system are
derived for two different “on" and “off" states of the switches. The
derived state equations are combined with the sliding control rule
considering the duty-cycle of the converter. The performance of the
system is analyzed by simulating the system using SIMULINK tool
box of MATLAB. The simulation results show that fuzzy logic
controller is more robust and less sensitive to parameter variations.
Abstract: In this study, a comparison of two control methods,
Proportional Control (PC) and Fuzzy Logic Control (FLC), which
have been used to develop an ideal thermoelectric renal hypothermia
system in order to use in renal surgery, has been carried out. Since
the most important issues in long-lasting parenchymatous renal
surgery are to provide an operation medium free of blood and to
prevent renal dysfunction in the postoperative period, control of the
temperature has become very important in renal surgery. The final
product is seriously affected from the changes in temperature,
therefore, it is necessary to reach some desired temperature points
quickly and avoid large overshoot. PIC16F877 microcontroller has
been used as controller for both of these two methods. Each control
method can simply ensure extra renal hypothermia in the targeted
way. But investigation of advantages and disadvantages of every
control method to each other is aimed and carried out by the
experimental implementations. Shortly, investigation of the most
appropriate method to use for development of system and that can be
applied to people safely in the future, has been performed. In this
sense, experimental results show that fuzzy logic control gives out
more reliable responses and efficient performance.
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: This paper presents PSS (Power system stabilizer) design based on optimal fuzzy PID (OFPID). OFPID based PSS design is considered for single-machine power systems. The main motivation for this design is to stabilize or to control low-frequency oscillation on power systems. Firstly, describing the linear PID control then to combine this PID control with fuzzy logic control mechanism. Finally, Fuzzy PID parameters (Kp. Kd, KI, Kupd, Kui) are tuned by Genetic Algorthm (GA) to reach optimal global stability. The effectiveness of the proposed PSS in increasing the damping of system electromechanical oscillation is demonstrated in a one-machine-infinite-bus system
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: In this paper, an intelligent automatic parking control method is proposed. First, the dynamical equation of the rear parking control is derived. Then a fuzzy logic control is proposed to perform the parking planning process. Further, a rear neural network is proposed for the steering control. Through the simulations and experiments, the intelligent auto-parking mode controllers have been shown to achieve the demanded goals with satisfactory control performance and to guarantee the system robustness under parametric variations and external disturbances. To improve some shortcomings and limitations in conventional parking mode control and further to reduce consumption time and prime cost.
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.
Abstract: Active power filter continues to be a powerful tool to control harmonics in power systems thereby enhancing the power quality. This paper presents a fuzzy tuned PID controller based shunt active filter to diminish the harmonics caused by non linear loads like thyristor bridge rectifiers and imbalanced loads. Here Fuzzy controller provides the tuning of PID, based on firing of thyristor bridge rectifiers and variations in input rms current. The shunt APF system is implemented with three phase current controlled Voltage Source Inverter (VSI) and is connected at the point of common coupling for compensating the current harmonics by injecting equal but opposite filter currents. These controllers are capable of controlling dc-side capacitor voltage and estimating reference currents. Hysteresis Current Controller (HCC) is used to generate switching signals for the voltage source inverter. Simulation studies are carried out with non linear loads like thyristor bridge rectifier along with unbalanced loads and the results proved that the APF along with fuzzy tuned PID controller work flawlessly for different firing angles of non linear load.
Abstract: Optimization of cutting parameters important in precision machining in regards to efficiency and surface integrity of the machined part. Usually productivity and precision in machining is limited by the forces emanating from the cutting process. Due to the inherent varying nature of the workpiece in terms of geometry and material composition, the peak cutting forces vary from point to point during machining process. In order to increase productivity without compromising on machining accuracy, it is important to control these cutting forces. In this paper a fuzzy logic control algorithm is developed that can be applied in the control of peak cutting forces in milling of spherical surfaces using ball end mills. The controller can adaptively vary the feedrate to maintain allowable cutting force on the tool. This control algorithm is implemented in a computer numerical control (CNC) machine. It has been demonstrated that the controller can provide stable machining and improve the performance of the CNC milling process by varying feedrate.
Abstract: The anti-lock braking systems installed on vehicles
for safe and effective braking, are high-order nonlinear and timevariant.
Using fuzzy logic controllers increase efficiency of such
systems, but impose a high computational complexity as well. The
main concept introduced by this paper is reducing computational
complexity of fuzzy controllers by deploying problem-solution data
structure. Unlike conventional methods that are based on
calculations, this approach is based on data oriented modeling.
Abstract: An active suspension system has been proposed to
improve the ride comfort. A quarter-car 2 degree-of-freedom (DOF)
system is designed and constructed on the basis of the concept of a
four-wheel independent suspension to simulate the actions of an
active vehicle suspension system. The purpose of a suspension
system is to support the vehicle body and increase ride comfort. The
aim of the work described in the paper was to illustrate the
application of fuzzy logic technique to the control of a continuously
damping automotive suspension system. The ride comfort is
improved by means of the reduction of the body acceleration caused
by the car body when road disturbances from smooth road and real
road roughness.
The paper describes also the model and controller used in the
study and discusses the vehicle response results obtained from a
range of road input simulations. In the conclusion, a comparison of
active suspension fuzzy control and Proportional Integration
derivative (PID) control is shown using MATLAB simulations.
Abstract: Fuzzy Load forecasting plays a paramount role in the operation and management of power systems. Accurate estimation of future power demands for various lead times facilitates the task of generating power reliably and economically. The forecasting of future loads for a relatively large lead time (months to few years) is studied here (long term load forecasting). Among the various techniques used in forecasting load, artificial intelligence techniques provide greater accuracy to the forecasts as compared to conventional techniques. Fuzzy Logic, a very robust artificial intelligent technique, is described in this paper to forecast load on long term basis. The paper gives a general algorithm to forecast long term load. The algorithm is an Extension of Short term load forecasting method to Long term load forecasting and concentrates not only on the forecast values of load but also on the errors incorporated into the forecast. Hence, by correcting the errors in the forecast, forecasts with very high accuracy have been achieved. The algorithm, in the paper, is demonstrated with the help of data collected for residential sector (LT2 (a) type load: Domestic consumers). Load, is determined for three consecutive years (from April-06 to March-09) in order to demonstrate the efficiency of the algorithm and to forecast for the next two years (from April-09 to March-11).