Analisis Stabilitas Sistem Tenaga Listrik Dengan Automatic Generation Control (AGC) Dua Area Menggunakan Fuzzy Logic Controller

In order to solve the problem of excessive understeer of four-wheel -steering vehicle with zero mass-center side-slip angle and proportional control at high speed, using fuzzy logical control method, adding direct yaw moment control of four wheel steering to solve this question. a two DOF four-wheel-steering vehicle model with integrated control of steering angle and yaw moment was established. The Four wheel steering system (4WS) which takes yaw rate and side-slip angle as the control object was realized with fuzzy control method. The fuzzy controller was designed with Fuzzy Logic Toolbox of MATLAB, and dynamic simulation has been carried out with SIMULINK. The result showed that fuzzy logic control method can improve vehicle handling stability effectively and doesn't increase the driver's driving burden at the same time.

Technological advances that occur today also have an impact on the development of technology in the world of robotics, on the world scale there is an international scale research organization called Robocup which focuses on the development of soccer robots. The RoboCup organization itself has a vision and goal to build a football robot team that will be competed with the winners of the world cup in 2050. The Robocup Competition has several divisions, one of which is the Middle Size League (MSL) which matches the wheeled soccer robot. The wheeled soccer robot itself has various abilities such as searching the ball, determining the goal point, avoiding the opponent, feed the ball to a friend s robot until the execution process kicking the ball into the opponent's goal. The ability to kick the ball is something that must be possessed by a soccer robot. The focus of this project is to create a new kicker system to be able to improve the ability to kick the ball on the wheeled soccer robot which is then controlled using the implementation of the fuzzy logic controller method, the method serves as the controller of a system or process by using fuzzy logic as a way of making decisions, so robots can kick with variations in distance and height of the ball that has been determined. The decision-making process with fuzzy logic was then given two inputs namely the falling ball distance and the height of the ball which is processed with a fuzzy logic method then produces an output power of kicking and touch angle kicker with the ball. The power of the kick is divided into 5 parts, namely very slow in the numbers 0 - 170 RPM, slow is in the numbers 180-220 RPM, middle 230-270 RPM, fast in numbers 280 - 320 RPM, and very fast in numbers 330 - 400 RPM. With maximum kick power and kicker angle of 50o produces a maximum distance of 110 cm and a maximum height of 30 cm, the minimum distance that can be taken is 10 cm and a minimum height of 1 cm with a speed of 200 RPM and kicker angle of 65o. Based on the results of testing the kick to the ball using the fuzzy logic controller method has an average error of 0.008%

An efficient intelligent system (FUZZY LOGIC) for the power transformer residual life assessment is presented in this paper. In the fuzzy method, different inputs and one output is used, that strictly depends on the number of membership function and their rule base and the type of the defuzzification method. The residual life of the transformers greatly influenced by the condition of the transformer insulation system. The insulation of winding de-teriorates during the normal ageing of the transformers. Paper insulation that contains cellulose molecules degrades due to heating or electrical breakdown dissolved in the transformer oil. Hence, the analysis of the Transformer oil gives correct evidence of variation in the property of the winding insulation during operation. Deterioration in transformer oil-paper insulation decreases both its electrical and mechanical strength that influence the age of the transformer. This paper presents a fuzzy logic method that has been implemented on three samples of power transformer oil for the residual life assessment of the transformers.

This paper is presented to examine and improve the performance of the torque ripple suppression for direct torque controlled permanent magnet synchronous motor by using fuzzy control method. On the basis of analyzing the torque ripple of the direct torque control in details, the fuzzy controllers are designed for two parts. Since the errors of the torque and flux could not assess accurately in hysteresis structure, the hysteresis controllers of the conventional DTC method are replaced by the fuzzy controller which could select the optimal voltage vector by judging the deviation degree of the torque and flux errors according to the fuzzy logic inference. Then the action time of the selected optimal voltage vector is determined by using the fuzzy duty ratio control method, the ripples of torque and flux can be attenuated effectively. The comprehensive simulation experiment is exhibited to reveal the excellent response performance of the system and verify the feasibility of the proposed fuzzy control scheme.

This paper describes a fuzzy directional control method for directional correction of a small-diameter tunnelling robot which constructs conduits of telecomunication cables. The directional control of a tunnelling robot conventionally depends on both the experience and intuition of the operator, and there have been no studies with regard to its automation. Therefore, in order to establish automatic control technology for a small-diameter tunnelling robot we proposed the fuzzy directional control method which can utilize both the expeience and knowledge of operators as a control rule. This fuzzy control uses a fuzzy rule set for [deviation, angular deviation] and [head angle (control input)]. We obtained an optimum fuzzy rule and optimum fuzzy set of values by using a dynamic simulator. Moreover, we obtained a fuzzy control method which can be applied to change the initial position of the robot. Simulation results clarified the validity of the proposed fuzzy control methods.

Current-controlled voltage source inverters offer substantial advantages in improving motor system dynamics for high-performance AC drive systems. The controller switches follow a set of reference current waveforms. Fixed-band hysteresis and sinusoidal-band hysteresis controllers have been studied. Neural network and fuzzy logic based current-controlled voltage source inverters are developed. The models and learning techniques are investigated by simulation. The implementation of neural networks is described and simulation results are presented. The application of fuzzy control to DC-DC power converters operating at finite switching frequency is studied. Several control methods currently used for buck and boost converters are compared to the fuzzy converter control. Simulation results for several control methods are presented. The simulations show that the fuzzy control method has better dynamic performance and less steady state error. >

A robotic fish mimicking cownose ray is developed and a fuzzy depth control method is presented in this paper. With dosoventrally flattened body wich is disigned by imitating body shape of cownose ray, the robotic fish has preferable pitch stability. A tail-unit, which consists of a pair of horizontal tails and a vertical tail, is used to realize turning motion in the horizontal plane and up-and-down motion in the vertical plane. By adjusting rotation angles of the horizontal tail, the robotic fish can swim upward or downward. Due to the complex hydrodynamics and uncertaintyies exist in the environment, fuzzy logic method is applied to realize automatic depth control of the robotic fish. The experimental results on the prototype verify that the fuzzy logic depth control method is effective in design and implemention.

Wound rotor induction motors are commonly used in high torque, adjustable speed industrial applications. The provision to add external resistances to the rotor offers high starting torque and smooth starting at a low starting current. In this paper, the look-up table method and fuzzy logic methods are introduced to estimate the rotor resistance value. This is achieved by controlling the firing angle of the thyristor converter circuit connected to the rotor. The smooth variation in speed with constant starting current and high torque is achieved for various reference values. The performance of the look-up table method and fuzzy logic controller method are compared with the traditional external resistance method. The results show that the speed error in the look-up table method is higher than in the fuzzy logic method but less than the traditional external resistance method. The performance of the fuzzy logic method is closer to the traditional external resistance method with less speed error and settling time.

Chapter 7 - Hybrid systems

Studies in literature and the increasing trend of electrification show that electric vehicles (EVs) will become more widespread in the future. However, the growing demand for EV chargers causes an overload on the grid. Furthermore, EV chargers generate power factor distortion and harmonics, which contaminate the grid and lower the quality of power. Therefore, power factor correction (PFC) is applied by EV chargers to mitigate the harmonics. As defined in the IEC 61000-3-2 standard, the total harmonic distortion (THD) shall be less than 5%. In this study, a better PFC operation is achieved with the proposed bridgeless isolated single ended primary inductor converter (BL SEPIC) topology as an EV charger instead of conventional converter topologies that have diode bridge rectifiers (DBR). Also, the study has better THD outputs as compared with the similar bridgeless (BL) topologies in literature thanks to the simulated control methods of the proportion-integration (PI) and fuzzy control. Moreover, these control methods are compared with each other in terms of THD suppression performance, stability, robustness, and computational effort. The results showed that the fuzzy controller has advantages of stability and robustness against the transient conditions, input voltages and load changes for THD suppression while the PI controller has better THD results only for steady state operation with nominal input voltage and full load conditions. The implemented PI and fuzzy controllers are simulated in a MATLAB Simulink environment.

Research on A Fuzzy Adaptive PID Control Method for Four Rotor UAV Control System With the continuous improvement of national living standards, people have higher and higher requirements for the reliability of power supply. The emergence of unmanned aerial vehicle inspection technology provides a new idea to solve the contradiction between the increasing equipment scale and the increasing inspection requirements. However, at present, the stability of the traditional proportion integration differentiation (PID) control system of the four rotor unmanned aerial vehicle (UAV) is not high enough. During the inspection, there are accidents of drones hitting power equipment from time to time. In view of the above problems, this paper studies the fuzzy adaptive PID control method to support the stable flight of four rotor UAV. The principle of fuzzy control is analyzed. The fuzzy control method and PID control method are deeply integrated. A fuzzy adaptive PID control system is designed. The universe and membership function of the relevant control parameters of the system are formulated. The tuning rules of fuzzy adaptive PID control system are formulated. Finally, the improved control system is simulated. The simulation results show that the fuzzy adaptive PID control algorithm can effectively improve the stability, reliability and emergency ability of UAV. This method can effectively improve the adaptability of UAV to perform complex missions in complex environments. The research results have guiding significance for expanding the application field of UAV.

Subject. Decoding and decision making models, methods and algorithms for elementary signals of receiving devices of distributed control systems elements. Purpose. Development, research and realization of soft decoding and decision making method for elementary signals (channel symbols) within receiving devices of distributed control systems elements based on the fuzzy logic fundamentals and methods. Methodology of research. The analysis of signals distortions by noise of different sources and forms is carried out in this paper. The «quasioptimum» receiving methods for taking account of distortions are analyzed. A condition of uncertainty often occurs at reception so it is difficult to correlate the distorted signal with any of the possible basic (transmitted) signals. The probability of the error at the same time considerably increases. The application of fuzzy sets and fuzzy logic math fundamentals for taking into account and the subsequent removal of uncertainty when decision making is offered. The elementary signals soft decoding (decision making) method based on the fuzzy sets theory and fuzzy logic methods is developed. The decision making device model with Fuzzy Logic Toolbox (MathWorks MatLab) for the offered decoding method application is developed and researched. The common block circuit of the elementary signals quasioptimum receiver is released and the algorithm of it's functioning is described. Research results. The formal description of elementary signals distortions is executed, the variables for decision making are entered. The decision making method of received symbol based fuzzy logic fundamentals is developed; input and output variables and their membership functions are defined; productional rules are formulated; defuzzyfication algorithm is offered. The common block circuit of receiving device is developed used offered decision making method for conclusion formations about received symbol. The simulation and research of the offered circuit is executed; the quantitative assessments of their functioning are received. Application. The offered decision making method based on fuzzy logic fundamentals is planned to be used within elementary signals decision making device. This device is the general node at the common block circuit of receiving device within distributed control systems elements. Conclusions. The researching of the developed receiving device model has shown that the decision making method provides a preset reliability indicators, assumes the computing complexity decreasing due to the arithmetic operations using and the possibility of decision making model parameters adaptation to the change of external conditions (change of error model parameters in a communication channel, increase in requirements to reliability, etc.). It allows to increase the efficiency and reliability of soft decoding applied algorithms.

Purpose – The purpose of this paper is to present the flight control law based on the fuzzy logic control methods for Mars airplane, and the research emphasis is placed on the attitude hold and the command track using the fuzzy control. Design/methodology/approach – The aircraft model is established with the combination of atmospheric environment, aerodynamic force and propulsive action. Then, the dynamic characteristics are analyzed in response to the different flight points for Mars airplane. Afterward, the flight control law is designed by applying the fuzzy logic theory to realize the attitude hold and the command track for Mars airplane. Findings – The simulation results demonstrate that the proposed control law based on the fuzzy logic control methods is effective to guarantee system stability and relieve coupling dynamics. In addition, this control system can provide strong robustness and good tracking performance for Mars airplane. Practical implications – The current work offers a new approach fo...

The development and distribution of geologically complicated fault structure have the characteristics of uncertainty, randomness, ambiguity, and variability. Therefore, the prediction of complicated fault structures is a typical nonlinear problem. Neither fuzzy logic method nor artificial neural network alone can solve this problem well because the fuzzy method is generally not easy to realize adaptive learning function, and the neural network method is not suitable for describing sedimentary microfacies or geophysical facies. Therefore, taking the marginal subsags in the Jiyang Depression, Eastern China, as a study case, this paper uses the method of combining artificial neural network and fuzzy logic to study geologically complicated fault structure prediction model. This paper expounds on the research status and significance of geologically complicated fault structure prediction model, elaborates the development background, current status, and future challenges of artificial neural networks and fuzzy logic, introduces the method and principle of fuzzy neural network structure and fuzzy logic analysis algorithm, conducts prediction model design and implementation based on fuzzy neural network, proposes the learning algorithm of fuzzy neural network, analyzes the programming realization of fuzzy neural network, constructs complicated fault structure prediction model based on the artificial neural network and fuzzy logic, performs the fuzzy logic system selection of complicated fault structure prediction model, carries out the artificial neural network structure design of complicated fault structure prediction model, compares the prediction effects of the geologically complicated fault structure model based on artificial neural networks and fuzzy logic, and finally discusses the system design and optimization of the prediction model for geologically complicated fault structures. The study results show that the fuzzy neural network fully integrates the advantages of artificial neural network and fuzzy logic system; based on the clear physical background of fuzzy logic system, it effectively integrates powerful knowledge expression ability and fuzzy reasoning ability into the network knowledge structure of neural network, which greatly improves the prediction accuracy of geologically complicated fault structure.

In this paper, analytical techniques and fuzzy logic method are applied to the dynamic modeling and efficient swimming control of a robotic fish. The bioinspired robotic fish, which follows an exact replica of a live mackerel (Scomber scombrus), is modeled by treating the undulating body and flapping tail independently using analytical methods. Comparing the results of simulations and experiments shows the feasibility of the dynamic model. Using this model, we found that the harmonic control of the Strouhal number and caudal fin angle of attack is a principal mechanism through which the robotic fish can obtain high thrust efficiency while swimming. The fuzzy control method, which is based on the knowledge of the robotic fish's dynamic behavior, has successfully utilized this principal mechanism. By comparing the thrust performance of the robotic fish with different control methods via simulation, we established that the fuzzy controller was able to achieve faster acceleration and smaller steady-state error than what could be achieved from an open-loop and conventional proportional-integral-derivative controller. The thrust efficiency during steady state was superior to that with conventional control methods. We also found that, when using the fuzzy control method, robotic fish can always swim near a “universal” Strouhal number that approximates to the swimming of live fish.