Institute of Scientific and Technical Information of China (English)
沈理
1997-01-01
A fuzzy logic control VLSI chip,F100,for industry process real-time control has been designed and fabricated with 0.8μm CMOS technology.The chip has the features of simplicity,felexibility and generality.This paper presents the Fuzzy control inrerence method of the chip,its VLSI implementation,and testing esign consideration.
Learning fuzzy logic control system
Lung, Leung Kam
1994-01-01
The performance of the Learning Fuzzy Logic Control System (LFLCS), developed in this thesis, has been evaluated. The Learning Fuzzy Logic Controller (LFLC) learns to control the motor by learning the set of teaching values that are generated by a classical PI controller. It is assumed that the classical PI controller is tuned to minimize the error of a position control system of the D.C. motor. The Learning Fuzzy Logic Controller developed in this thesis is a multi-input single-output network. Training of the Learning Fuzzy Logic Controller is implemented off-line. Upon completion of the training process (using Supervised Learning, and Unsupervised Learning), the LFLC replaces the classical PI controller. In this thesis, a closed loop position control system of a D.C. motor using the LFLC is implemented. The primary focus is on the learning capabilities of the Learning Fuzzy Logic Controller. The learning includes symbolic representation of the Input Linguistic Nodes set and Output Linguistic Notes set. In addition, we investigate the knowledge-based representation for the network. As part of the design process, we implement a digital computer simulation of the LFLCS. The computer simulation program is written in 'C' computer language, and it is implemented in DOS platform. The LFLCS, designed in this thesis, has been developed on a IBM compatible 486-DX2 66 computer. First, the performance of the Learning Fuzzy Logic Controller is evaluated by comparing the angular shaft position of the D.C. motor controlled by a conventional PI controller and that controlled by the LFLC. Second, the symbolic representation of the LFLC and the knowledge-based representation for the network are investigated by observing the parameters of the Fuzzy Logic membership functions and the links at each layer of the LFLC. While there are some limitations of application with this approach, the result of the simulation shows that the LFLC is able to control the angular shaft position of the
Fuzzy logic controllers on chip
Acosta, Nelson; Simonelli, Daniel Horacio
2002-01-01
This paper analyzes a fuzzy logic (FL) oriented instruction set (micro)controller and their implementations on FIPSOC1. VHDL code is synthesized using a small portion of FIPSOC FPGA2. This circuits are used from the mP8051 FIPSOC built-in microcontroller to provide efficient arithmetic operations such as multipliers, dividers, minimums and maximums.
Fuzzy logic based robotic controller
Attia, F.; Upadhyaya, M.
1994-01-01
Existing Proportional-Integral-Derivative (PID) robotic controllers rely on an inverse kinematic model to convert user-specified cartesian trajectory coordinates to joint variables. These joints experience friction, stiction, and gear backlash effects. Due to lack of proper linearization of these effects, modern control theory based on state space methods cannot provide adequate control for robotic systems. In the presence of loads, the dynamic behavior of robotic systems is complex and nonlinear, especially where mathematical modeling is evaluated for real-time operators. Fuzzy Logic Control is a fast emerging alternative to conventional control systems in situations where it may not be feasible to formulate an analytical model of the complex system. Fuzzy logic techniques track a user-defined trajectory without having the host computer to explicitly solve the nonlinear inverse kinematic equations. The goal is to provide a rule-based approach, which is closer to human reasoning. The approach used expresses end-point error, location of manipulator joints, and proximity to obstacles as fuzzy variables. The resulting decisions are based upon linguistic and non-numerical information. This paper presents a solution to the conventional robot controller which is independent of computationally intensive kinematic equations. Computer simulation results of this approach as obtained from software implementation are also discussed.
Advanced Control Techniques with Fuzzy Logic
2014-06-01
AFRL-RQ-WP-TR-2014-0175 ADVANCED CONTROL TECHNIQUES WITH FUZZY LOGIC James E. Combs Structural Validation Branch Aerospace Vehicles...TECHNIQUES WITH FUZZY LOGIC 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62201F 6. AUTHOR(S) James E. Combs...unlimited. 13. SUPPLEMENTARY NOTES PA Case Number: 88ABW-2014-3281; Clearance Date: 09 Jul 2014. 14. ABSTRACT Research on the Fuzzy Logic control
Temperature Control System Using Fuzzy Logic Technique
Directory of Open Access Journals (Sweden)
Isizoh A N
2012-06-01
Full Text Available Fuzzy logic technique is an innovative technology used in designing solutions for multi-parameter and non-linear control models for the definition of a control strategy. As a result, it delivers solutions faster than the conventional control design techniques. This paper thus presents a fuzzy logic based-temperature control system, which consists of a microcontroller, temperature sensor, and operational amplifier, Analogue to Digital Converter, display interface circuit and output interface circuit. It contains a design approach that uses fuzzy logic technique to achieve a controlled temperature output function.
Refining fuzzy logic controllers with machine learning
Berenji, Hamid R.
1994-01-01
In this paper, we describe the GARIC (Generalized Approximate Reasoning-Based Intelligent Control) architecture, which learns from its past performance and modifies the labels in the fuzzy rules to improve performance. It uses fuzzy reinforcement learning which is a hybrid method of fuzzy logic and reinforcement learning. This technology can simplify and automate the application of fuzzy logic control to a variety of systems. GARIC has been applied in simulation studies of the Space Shuttle rendezvous and docking experiments. It has the potential of being applied in other aerospace systems as well as in consumer products such as appliances, cameras, and cars.
A SELF-ORGANISING FUZZY LOGIC CONTROLLER
African Journals Online (AJOL)
ES Obe
One major drawback of fuzzy logic controllers is the difficulty encountered in the construction of a ... an algorithm that allows a designer to initially specify a possibly inaccurate rule-base, which ... an adaptive FLC strategy based on these ideas.
Fuzzy logic control for camera tracking system
Lea, Robert N.; Fritz, R. H.; Giarratano, J.; Jani, Yashvant
1992-01-01
A concept utilizing fuzzy theory has been developed for a camera tracking system to provide support for proximity operations and traffic management around the Space Station Freedom. Fuzzy sets and fuzzy logic based reasoning are used in a control system which utilizes images from a camera and generates required pan and tilt commands to track and maintain a moving target in the camera's field of view. This control system can be implemented on a fuzzy chip to provide an intelligent sensor for autonomous operations. Capabilities of the control system can be expanded to include approach, handover to other sensors, caution and warning messages.
Implementation of a Fuzzy Logic Speed Controller for a Permanent ...
African Journals Online (AJOL)
Journal of Research in National Development. Journal Home ... Fuzzy logic controlled model of the DC motor was implemented. The purpose is to ... the proposed strategy. Keywords: Brushless DC motor, fuzzy logic control, speed controller ...
control of a dc motor using fuzzy logic control algorithm
African Journals Online (AJOL)
user
conditions such as changes in motor load demand, non- linearity ... Figure 1: Structure of a fuzzy logic controller (Source. [6]). A typical fuzzy logic ... mathematical modeling based on first principles; and via ..... applied. On the premise of these findings, it would be tactful in ... and Sugeno Type Fuzzy Inference Systems for Air.
Zadeh, Lofti A.
1988-01-01
The author presents a condensed exposition of some basic ideas underlying fuzzy logic and describes some representative applications. The discussion covers basic principles; meaning representation and inference; basic rules of inference; and the linguistic variable and its application to fuzzy control.
FUZZY LOGIC CONTROLLED CATHODIC PROTECTION CIRCUIT DESIGN
AKÇAYOL, M. Ali
2010-01-01
In this study, output voltage of automatic transformer-rectifier (TR) unit of impressed current cathodic protection has been controlled by using fuzzy logic controller. To prevent corrosion, voltage between the protection metal and the auxiliary anode has to be controlled on a desired level. Because soil resistance in the environment changes with humidity and soil characteristics, TRs must control the output voltage between protection metal and auxiliary anode automatically. In this study, a ...
Fuzzy logic control of telerobot manipulators
Franke, Ernest A.; Nedungadi, Ashok
1992-01-01
Telerobot systems for advanced applications will require manipulators with redundant 'degrees of freedom' (DOF) that are capable of adapting manipulator configurations to avoid obstacles while achieving the user specified goal. Conventional methods for control of manipulators (based on solution of the inverse kinematics) cannot be easily extended to these situations. Fuzzy logic control offers a possible solution to these needs. A current research program at SRI developed a fuzzy logic controller for a redundant, 4 DOF, planar manipulator. The manipulator end point trajectory can be specified by either a computer program (robot mode) or by manual input (teleoperator). The approach used expresses end-point error and the location of manipulator joints as fuzzy variables. Joint motions are determined by a fuzzy rule set without requiring solution of the inverse kinematics. Additional rules for sensor data, obstacle avoidance and preferred manipulator configuration, e.g., 'righty' or 'lefty', are easily accommodated. The procedure used to generate the fuzzy rules can be extended to higher DOF systems.
Daylight illuminance control with fuzzy logic
Energy Technology Data Exchange (ETDEWEB)
Trobec Lah, Mateja; Peternelj, Joze; Krainer, Ales [University of Ljubljana, Faculty of Civil and Geodetic Engineering, Jamova cesta 2, 1000 Ljubljana (Slovenia); Zupancic, Borut [University of Ljubljana, Faculty of Electrical Engineering, Trzaska 25, 1000 Ljubljana (Slovenia)
2006-03-15
The purpose is to take full advantage of daylight for inside illumination. The inside illuminance and luminous efficacy of the available solar radiation were analyzed. The paper deals with the controlled dynamic illuminance response of built environment in real-time conditions. The aim is controlled functioning of the roller blind as a regulation device to assure the desired inside illuminance with smooth roller blind moving. Automatic illuminance control based on fuzzy logic is realized on a test chamber with an opening on the south side. The development and design of the fuzzy controller for the corresponding positioning of the roller blind with the available solar radiation as external disturbance is the subject of this paper. (author)
FUZZY LOGIC CONTROLLER IMPLEMENTATION FOR PHOTOVOLTAIC STATION
Directory of Open Access Journals (Sweden)
Imad Zein
2014-01-01
Full Text Available Solar panels have a nonlinear voltage-current characteristic, with a distinct maximum power point (MPP, which depends on the environmental factors, such as temperature and irradiation. In order to continuously harvest maximum power from the solar panels, they have to operate at their MPP despite the inevitable changes in the environment. This is why the controllers of all solar power electronic converters employ some method for maximum power point tracking (MPPT . Over the past years many MPPT techniques have been published and based on that the main paper’s objective is to analyze one of the most promising MPPT control algorithms: fuzzy logic controller.
Terminology and concepts of control and Fuzzy Logic
Aldridge, Jack; Lea, Robert; Jani, Yashvant; Weiss, Jonathan
1990-01-01
Viewgraphs on terminology and concepts of control and fuzzy logic are presented. Topics covered include: control systems; issues in the design of a control system; state space control for inverted pendulum; proportional-integral-derivative (PID) controller; fuzzy controller; and fuzzy rule processing.
Active structural control by fuzzy logic rules: An introduction
Energy Technology Data Exchange (ETDEWEB)
Tang, Y.
1995-07-01
An introduction to fuzzy logic control applied to the active structural control to reduce the dynamic response of structures subjected to earthquake excitations is presented. It is hoped that this presentation will increase the attractiveness of the methodology to structural engineers in research as well as in practice. The basic concept of the fuzzy logic control are explained by examples and by diagrams with a minimum of mathematics. The effectiveness and simplicity of the fuzzy logic control is demonstrated by a numerical example in which the response of a single-degree-of-freedom system subjected to earthquake excitations is controlled by making use of the fuzzy logic controller. In the example, the fuzzy rules are first learned from the results obtained from linear control theory; then they are fine tuned to improve their performance. It is shown that the performance of fuzzy logic control surpasses that of the linear control theory. The paper shows that linear control theory provides experience for fuzzy logic control, and fuzzy logic control can provide better performance; therefore, two controllers complement each other.
Active structural control by fuzzy logic rules: An introduction
Energy Technology Data Exchange (ETDEWEB)
Tang, Yu [Argonne National Lab., IL (United States). Reactor Engineering Div.; Wu, Kung C. [Texas Univ., El Paso, TX (United States). Dept. of Mechanical and Industrial Engineering
1996-12-31
A zeroth level introduction to fuzzy logic control applied to the active structural control to reduce the dynamic response of structures subjected to earthquake excitations is presented. It is hoped that this presentation will increase the attractiveness of the methodology to structural engineers in research as well as in practice. The basic concept of the fuzzy logic control are explained by examples and by diagrams with a minimum of mathematics. The effectiveness and simplicity of the fuzzy logic control is demonstrated by a numerical example in which the response of a single- degree-of-freedom system subjected to earthquake excitations is controlled by making use of the fuzzy logic controller. In the example, the fuzzy rules are first learned from the results obtained from linear control theory; then they are fine tuned to improve their performance. It is shown that the performance of fuzzy logic control surpasses that of the linear control theory. The paper shows that linear control theory provides experience for fuzzy logic control, and fuzzy logic control can provide better performance; therefore, two controllers complement each other.
Urban Intersection Traffic Signal Control Based on Fuzzy Logic
Institute of Scientific and Technical Information of China (English)
魏武; 张毅; 张佐; 宋靖雁
2002-01-01
This paper presents a fuzzy logic adaptive traffic signal control method for an isolated four-approach intersection with through and left-turning movements. In the proposed method, the fuzzy logic controller can make adjustments to signal timing in response to observed changes. The "urgency degree" term that can describe different user's demands for a green light is used in the fuzzy logic decision-making. In addition, a three-level fuzzy controller model decides whether to extend or terminate the current signal phase and the sequence of phases. Simulation results show that the fuzzy controller can adjust its signal timing in response to changing traffic conditions on a real-time basis and that the proposed fuzzy logic controller leads to less vehicle delays and a lower percentage of stopped vehicles.
Hybrid Genetic Algorithms with Fuzzy Logic Controller
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In this paper, a new implementation of genetic algorithms (GAs) is developed for the machine scheduling problem, which is abundant among the modern manufacturing systems. The performance measure of early and tardy completion of jobs is very natural as one's aim, which is usually to minimize simultaneously both earliness and tardiness of all jobs. As the problem is NP-hard and no effective algorithms exist, we propose a hybrid genetic algorithms approach to deal with it. We adjust the crossover and mutation probabilities by fuzzy logic controller whereas the hybrid genetic algorithm does not require preliminary experiments to determine probabilities for genetic operators. The experimental results show the effectiveness of the GAs method proposed in the paper.``
Fuzzy logic control and optimization system
Lou, Xinsheng [West Hartford, CT
2012-04-17
A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Application of Fuzzy Logic in Control of Switched Reluctance Motor
Directory of Open Access Journals (Sweden)
Pavel Brandstetter
2006-01-01
Full Text Available The flux linkage of switched reluctance motor (SRM depends on the stator current and position between the rotor and stator poles. The fact determines that during control of SRM current with the help of classical PI controllers in a wide regulation range unsatisfied results occur. The main reasons of the mentioned situation are big changes of the stator inductance depending on the stator current and rotor position. In a switched reluctance motor the stator phase inductance is a non-linear function of the stator phase current and rotor position. Fuzzy controller and fuzzy logic are generally non-linear systems; hence they can provide better performance in this case. Fuzzy controller is mostly presented as a direct fuzzy controller or as a system, which realizes continued changing parameters of other controller, so-called fuzzy supervisor. Referring to the usage of fuzzy logic as a supervisor of conventional PI controller in control of SRM possible improvement occurs.
Type-2 Fuzzy Logic in Intelligent Control Applications
Castillo, Oscar
2012-01-01
We describe in this book, hybrid intelligent systems based mainly on type-2 fuzzy logic for intelligent control. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, and bio-inspired optimization algorithms, which can be used to produce powerful automatic control systems. The book is organized in three main parts, which contain a group of chapters around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which can be the basis for achieving intelligent control with interval type-2 fuzzy logic. The second part of the book is comprised of chapters with the main theme of evolutionary optimization of type-2 fuzzy systems in intelligent control with the aim of designing optimal type-2 fuzzy controllers for complex control problems in diverse areas of application, including mobile robotics, aircraft dynamics systems and hardware implementations. Th...
Fuzzy logic controllers: A knowledge-based system perspective
Bonissone, Piero P.
1993-01-01
Over the last few years we have seen an increasing number of applications of Fuzzy Logic Controllers. These applications range from the development of auto-focus cameras, to the control of subway trains, cranes, automobile subsystems (automatic transmissions), domestic appliances, and various consumer electronic products. In summary, we consider a Fuzzy Logic Controller to be a high level language with its local semantics, interpreter, and compiler, which enables us to quickly synthesize non-linear controllers for dynamic systems.
Fuzzy Logic in Traffic Engineering: A Review on Signal Control
Directory of Open Access Journals (Sweden)
Milan Koukol
2015-01-01
Full Text Available Since 1965 when the fuzzy logic and fuzzy algebra were introduced by Lotfi Zadeh, the fuzzy theory successfully found its applications in the wide range of subject fields. This is mainly due to its ability to process various data, including vague or uncertain data, and provide results that are suitable for the decision making. This paper aims to provide comprehensive overview of literature on fuzzy control systems used for the management of the road traffic flow at road junctions. Several theoretical approaches from basic fuzzy models from the late 1970s to most recent combinations of real-time data with fuzzy inference system and genetic algorithms are mentioned and discussed throughout the paper. In most cases, fuzzy logic controllers provide considerable improvements in the efficiency of traffic junctions’ management.
Fuzzy logic controller to improve powerline communication
Tirrito, Salvatore
2015-12-01
The Power Line Communications (PLC) technology allows the use of the power grid in order to ensure the exchange of data information among devices. This work proposes an approach, based on Fuzzy Logic, that dynamically manages the amplitude of the signal, with which each node transmits, by processing the master-slave link quality measured and the master-slave distance. The main objective of this is to reduce both the impact of communication interferences induced and power consumption.
Type-2 fuzzy logic uncertain systems’ modeling and control
Antão, Rómulo
2017-01-01
This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets. Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.
Optimization of Fuzzy Logic Controller for Supervisory Power System Stabilizers
Directory of Open Access Journals (Sweden)
Y. A. Al-Turki
2012-01-01
Full Text Available This paper presents a powerful supervisory power system stabilizer (PSS using an adaptive fuzzy logic controller driven by an adaptive fuzzy set (AFS. The system under study consists of two synchronous generators, each fitted with a PSS, which are connected via double transmission lines. Different types of PSS-controller techniques are considered. The proposed genetic adaptive fuzzy logic controller (GAFLC-PSS, using 25 rules, is compared with a static fuzzy logic controller (SFLC driven by a fixed fuzzy set (FFS which has 49 rules. Both fuzzy logic controller (FLC algorithms utilize the speed error and its rate of change as an input vector. The adaptive FLC algorithm uses a genetic algorithmto tune the parameters of the fuzzy set of each PSS. The FLC’s are simulated and tested when the system is subjected to different disturbances under a wide range of operating points. The proposed GAFLC using AFS reduced the computational time of the FLC, where the number of rules is reduced from 49 to 25 rules. In addition, the proposed adaptive FLC driven by a genetic algorithm also reduced the complexity of the fuzzy model, while achieving a good dynamic response of the system under study.
Optimal Power Flow Using Adaptive Fuzzy Logic Controllers
Directory of Open Access Journals (Sweden)
Abdullah M. Abusorrah
2013-01-01
Full Text Available This paper presents an approach for optimum reactive power dispatch through the power network with flexible AC transmission systems (FACTSs devices, using adaptive fuzzy logic controller (AFLC driven by adaptive fuzzy sets (AFSs. The membership functions of AFLC are optimized based on 2nd-order fuzzy set specifications. The operation of FACTS devices (particularly, static VAR compensator (SVC and the setting of their control parameters (QSVC are optimized dynamically based on the proposed AFLC to enhance the power system stability in addition to their main function of power flow control. The proposed AFLC is compared with a static fuzzy logic controller (SFLC, driven by a fixed fuzzy set (FFS. Simulation studies were carried out and validated on the standard IEEE 30-bus test system.
DEFF Research Database (Denmark)
Jantzen, Jan
1998-01-01
A logic based on the two truth values True and False is sometimes inadequate when describing human reasoning. Fuzzy logic uses the whole interval between 0 (False) and 1 (True) to describe human reasoning. As a result, fuzzy logic is being applied in rule based automatic controllers, and this paper...
Fuzzy Logic Temperature Control System For The Induction Furnace
Directory of Open Access Journals (Sweden)
Lei Lei Hnin
2015-08-01
Full Text Available This research paper describes the fuzzy logic temperature control system of the induction furnace. Temperature requirement of the heating system varies during the heating process. In the conventional control schemes the switching losses increase with the change in the load. A closed loop control is required to have a smooth control on the system. In this system pulse width modulation based power control scheme for the induction heating system is developed using the fuzzy logic controller. The induction furnace requires a good voltage regulation to have efficient response. The controller controls the temperature depending upon weight of meat water and time. This control system is implemented in hardware system using microcontroller. Here the fuzzy logic controller is designed and simulated in MATLAB to get the desire condition.
Applied intelligent systems: blending fuzzy logic with conventional control
Filev, Dimitar; Syed, Fazal U.
2010-05-01
The aim of this paper is to show that design of applied intelligent control systems requires different types of blending between fuzzy logic and conventional control systems. Two alternative automotive applications - a manufacturing process control problem and an advisory system for fuel efficient driving - that benefit from both fuzzy and control theories are reviewed and different levels of prioritisations of both approaches are discussed based on the specificity of the applications.
Fuzzy logic applications to expert systems and control
Lea, Robert N.; Jani, Yashvant
1991-01-01
A considerable amount of work on the development of fuzzy logic algorithms and application to space related control problems has been done at the Johnson Space Center (JSC) over the past few years. Particularly, guidance control systems for space vehicles during proximity operations, learning systems utilizing neural networks, control of data processing during rendezvous navigation, collision avoidance algorithms, camera tracking controllers, and tether controllers have been developed utilizing fuzzy logic technology. Several other areas in which fuzzy sets and related concepts are being considered at JSC are diagnostic systems, control of robot arms, pattern recognition, and image processing. It has become evident, based on the commercial applications of fuzzy technology in Japan and China during the last few years, that this technology should be exploited by the government as well as private industry for energy savings.
Design and performance comparison of fuzzy logic based tracking controllers
Lea, Robert N.; Jani, Yashvant
1992-01-01
Several camera tracking controllers based on fuzzy logic principles have been designed and tested in software simulation in the software technology branch at the Johnson Space Center. The fuzzy logic based controllers utilize range measurement and pixel positions from the image as input parameters and provide pan and tilt gimble rate commands as output. Two designs of the rulebase and tuning process applied to the membership functions are discussed in light of optimizing performance. Seven test cases have been designed to test the performance of the controllers for proximity operations where approaches like v-bar, fly-around and station keeping are performed. The controllers are compared in terms of responsiveness, and ability to maintain the object in the field-of-view of the camera. Advantages of the fuzzy logic approach with respect to the conventional approach have been discussed in terms of simplicity and robustness.
Fuzzy logic control of the building structure with CLEMR dampers
Zhang, Xiang-Cheng; Xu, Zhao-Dong; Huang, Xing-Huai; Zhu, Jun-Tao
2013-04-01
The semi-active control technology has been paid more attention in the field of structural vibration control due to its high controllability, excellent control effect and low power requirement. When semi-active control device are used for vibration control, some challenges must be taken into account, such as the reliability and the control strategy of the device. This study presents a new large tonnage compound lead extrusion magnetorheological (CLEMR) damper, whose mathematical model is introduced to describe the variation of damping force with current and velocity. Then a current controller based on the fuzzy logic control strategy is designed to determine control currents of the CLEMR dampers rapidly. A ten-floor frame structure with CLEMR dampers using the fuzzy logic control strategy is built and calculated by using MATLAB. Calculation results show that CLEMR dampers can reduce the seismic responses of structures effectively. Calculation results of the fuzzy logic control strategy are compared with those of the semi-active limit Hrovat control structure, the passive-off control structure, and the uncontrolled structure. Comparison results show that the fuzzy logic control strategy can determine control currents of CLEMR dampers quickly and can reduce seismic responses of the structures more effectively than the passive-off control strategy and the uncontrolled structure.
Energy Technology Data Exchange (ETDEWEB)
Ramstroem, Erik [TPS Termiska Processer AB, Nykoeping (Sweden)
2002-04-01
Grate-control is a complex task in many ways. The relations between controlled variables and the values they depend on are mostly unknown. Research projects are going on to create grate models based on physical laws. Those models are too complex for control implementation. The evaluation time is to long for control use. Another fundamental difficulty is that the relationships are none linear. That is, for a specific change in control value, the change in controlled value depends on the original size of control value, process disturbances and controlled values. There are extensive theories for linear process control. Non-linear control theory is used in robotic applications, but not in process and combustion control. The aim of grate control is to use as much of the grate area as possible, without having unburned material in ash. The outlined strategy is: To keep the position of the final bum out zone constant and its extension controlled. The control variables should be primary airflow, distribution of primary air, and fuel flow. Disturbances that should be measured are the fuel moisture content, the temperature of primary air and the grate temperature under the fuel bed. Technologies used are, fuzzy-logic and neural networks. A combination of booth could be used as well as any of them separately. A Fuzzy-logic controller acts as a computerised operator. Rules are specified with 'if - then' thesis. An example of that is: - if temperature is low, then close the valve The boundaries between the rules are made fuzzy. That makes it possible for the temperature to be just a bit low, which makes the valve open a bit. A lot of rules are created so that the controller knows what to do in every situation. Neural networks are sort of multi dimensional curves, with arbitrary degrees of freedom. The nets are used to predict future process values from measured ones. The model is evaluated from collected data. Parameters are adjusted for best correspondence between
Capturing hand tremors with a fuzzy logic wheelchair joystick controller
van der Zwaag, B.J.; Corbett, Dan
1999-01-01
We have designed and built a fuzzy logic wheelchair controller which minimizes the effect of Multiple Sclerosis and tremors. The aim of our project has been to give people with Multiple Sclerosis better control of an electric wheelchair by removing tremors from the joystick signal. The system interc
Capturing hand tremors with a fuzzy logic wheelchair joystick controller
Zwaag, van der Berend-Jan; Corbett, Dan
1999-01-01
We have designed and built a fuzzy logic wheelchair controller which minimizes the effect of Multiple Sclerosis and tremors. The aim of our project has been to give people with Multiple Sclerosis better control of an electric wheelchair by removing tremors from the joystick signal. The system interc
Fuzzy Logic Decoupled Lateral Control for General Aviation Airplanes
Duerksen, Noel
1997-01-01
It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control different airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control aileron or roll spoiler position. This controller was used to control bank angle for both a piston powered single engine aileron equipped airplane simulation and a business jet simulation which used spoilers for primary roll control. Overspeed, stall and overbank protection were incorporated in the form of expert systems supervisors and weighted fuzzy rules. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic lateral controller could be successfully used on two general aviation aircraft types that have very different characteristics. These controllers worked for both airplanes over their entire flight envelopes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle ]ever travel, etc.). This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.
Autonomous vehicle motion control, approximate maps, and fuzzy logic
Ruspini, Enrique H.
1993-01-01
Progress on research on the control of actions of autonomous mobile agents using fuzzy logic is presented. The innovations described encompass theoretical and applied developments. At the theoretical level, results of research leading to the combined utilization of conventional artificial planning techniques with fuzzy logic approaches for the control of local motion and perception actions are presented. Also formulations of dynamic programming approaches to optimal control in the context of the analysis of approximate models of the real world are examined. Also a new approach to goal conflict resolution that does not require specification of numerical values representing relative goal importance is reviewed. Applied developments include the introduction of the notion of approximate map. A fuzzy relational database structure for the representation of vague and imprecise information about the robot's environment is proposed. Also the central notions of control point and control structure are discussed.
Advanced Fuzzy Logic Based Admission Control for UMTS System
Directory of Open Access Journals (Sweden)
P. Kejik
2010-12-01
Full Text Available The capacity of CDMA (Code Division Multiple Access systems is interference limited. Therefore radio resources management (RRM functions are used. They are responsible for supplying optimum coverage, ensuring efficient use of physical resources, and providing the maximum planned capacity. This paper deals with admission control techniques for UMTS (Universal Mobile Telecommunication System. A UMTS system model and four fuzzy logic based admission control algorithms are presented in this paper. Two new versions of fuzzy logic based admission control algorithms are presented there. All algorithms are mutually compared via simulations. Simulations show that the novel advanced fuzzy algorithm outperforms the other simulated algorithms (in terms of blocking probability, dropping probability and the number of active UEs in cell.
Distributed traffic signal control using fuzzy logic
Chiu, Stephen
1992-01-01
We present a distributed approach to traffic signal control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic condition and of the signal timing parameters at adjacent intersections. Thus, the signal timing parameters evolve dynamically using only local information to improve traffic flow. This distributed approach provides for a fault-tolerant, highly responsive traffic management system. The signal timing at an intersection is defined by three parameters: cycle time, phase split, and offset. We use fuzzy decision rules to adjust these three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. We show the effectiveness of this method through simulation of the traffic flow in a network of controlled intersections.
Fuzzy Logic Decoupled Longitudinal Control for General Aviation Airplanes
Duerksen, Noel
1996-01-01
It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control difference airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control throttle position and another to control elevator position. These two controllers were used to control flight path angle and airspeed for both a piston powered single engine airplane simulation and a business jet simulation. Overspeed protection and stall protection were incorporated in the form of expert systems supervisors. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic longitudinal controller could be successfully used on two general aviation aircraft types that have very difference characteristics. These controllers worked for both airplanes over their entire flight envelopes including configuration changes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle lever travel, etc.). The controllers also handled configuration changes without mode switching or knowledge of the current configuration. This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.
Control of a flexible beam using fuzzy logic
Mccullough, Claire L.
1991-01-01
The goal of this project, funded under the NASA Summer Faculty Fellowship program, was to evaluate control methods utilizing fuzzy logic for applicability to control of flexible structures. This was done by applying these methods to control of the Control Structures Interaction Suitcase Demonstrator developed at Marshall Space Flight Center. The CSI Suitcase Demonstrator is a flexible beam, mounted at one end with springs and bearing, and with a single actuator capable of rotating the beam about a pin at the fixed end. The control objective is to return the tip of the free end to a zero error position (from a nonzero initial condition). It is neither completely controllable nor completely observable. Fuzzy logic control was demonstrated to successfully control the system and to exhibit desirable robustness properties compared to conventional control.
Directory of Open Access Journals (Sweden)
Raj kumar
2012-08-01
Full Text Available This paper presents a self-tuning method of fuzzy logic controllers. The consequence part of the fuzzy logic controller is self-tuned through the Q-learning algorithm of reinforcement learning. The off policy temporal difference algorithm is used for tuning which directly approximate the action value function which gives the maximum reward. In this way, the Q-learning algorithm is used for the continuous time environment. The approach considered is having the advantage of fuzzy logic controller in a way that it is robust under the environmental uncertainties and no expert knowledge is required to design the rule base of the fuzzy logic controller.
Fuzzy Logic Applied to an Oven Temperature Control System
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Nagabhushana KATTE
2011-10-01
Full Text Available The paper describes the methodology of design and development of fuzzy logic based oven temperature control system. As simple fuzzy logic controller (FLC structure with an efficient realization and a small rule base that can be easily implemented in existing underwater control systems is proposed. The FLC has been designed using bell-shaped membership function for fuzzification, 49 control rules in its rule base and centre of gravity technique for defuzzification. Analog interface card with 16-bits resolution is designed to achieve higher precision in temperature measurement and control. The experimental results of PID and FLC implemented system are drawn for a step input and presented in a comparative fashion. FLC exhibits fast response and it has got sharp rise time and smooth control over conventional PID controller. The paper scrupulously discusses the hardware and software (developed using ‘C’ language features of the system.
Novel Approach to Fuzzy Logic Controller Design for Systems With Deadzones
Kim, Jong-Hwan; Park, Jong-Hwan; Lee, Seon-Woo; Chong, Edwin K. P.
1992-01-01
Existing fuzzy control methods do not perform well when applied to systems containing nonlinearities arising from unknown deadzones. In particular, we show that a conventional fuzzy logic controller applied to a system with a deadzone suffers from poor transient performance and a large steady-state error. In this report, we propose a novel two-layered fuzzy logic controller for controlling systems with deadzones. The two-layered control structure consists of a fuzzy logic-based precompensator...
Efficient Fuzzy Logic Controller for Magnetic Levitation Systems
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D. S. Shu’aibu
2016-12-01
Full Text Available Magnetic levitation is a system of suspending a body or a complete system against gravity. Suspending a system in air against gravity without using fixed structure for supporting is highly unstable and complex. In the previous research many techniques of stabilizing magnetic levitation systems were discussed. In this paper magnetic levitation controller using fuzzy logic is proposed. The proposed Fuzzy logic controller (FLC is designed, and developed using triangular membership function with 7×7 rules. The system model was implemented in MATLAB/SIMULINK and the system responses to Fuzzy controller with different input signals were investigated. Using unit step input signal, the proposed controller has a settling time of 0.35 secs, percentage overshoot of 0% and there is no oscillation. The proposed controller is validated with a model of an existing practical conventional proportional plus derivatives (PD controller. The PD controller has a settling time of 0.45 secs, percentage overshoot of 7% and with oscillation. Similarly, with sinusoidal input, the FLC has a phase shift and peak response of 0^0 and 0.9967 respectively, while PD controller has a phase shift and peak response of 24.48o and 0.9616 respectively. A disturbance signal was applied to the input of the control system. Fuzzy controller succeeded in rejecting the disturbance signal without further turning of the parameters whereby PD controller failed.
Switch Reluctance Motor Control Based on Fuzzy Logic System
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S. Aleksandrovsky
2012-01-01
Full Text Available Due to its intrinsic simplicity and reliability, the switched reluctance motor (SRM has now become a promising candidate for variable-speed drive applications as an alternative induction motor in various industrial application. However, the SRM has the disadvantage of nonlinear characteristic and control. It is suggested to use controller based on fuzzy logic system. Design of FLS controller and simulation model presented.
Investigation into Model-Based Fuzzy Logic Control
1993-12-01
Logic, in this context, will be used to bridge the gap between linear systems theory and nonlinear control application. Said another way, the language of...to demonstrate the value of applying both Fuzzy Set theory and linear systems theory to the control of nonlinear plants. It is conjectured that the... linear systems theory , to the extent possible. * The plant should be as simple as possible to dearly demonstrate the the developed controller. The
Different control applications on a vehicle using fuzzy logic control
Indian Academy of Sciences (India)
Nurkan Yagiz; L Emir Sakman; Rahmi Guclu
2008-02-01
In this paper, the active suspension control of a vehicle model that has ﬁve degrees of freedom with a passenger seat using a fuzzy logic controller is studied. Three cases are taken into account as different control applications. In the ﬁrst case, the vehicle model having passive suspensions with an active passenger seat is controlled. In the second case, active suspensions with passive passenger seat combination are controlled. In the third case, both the passenger seat and suspensions have active controllers. Vibrations of the passenger seat in the three cases due to road bump input are simulated. At the end of the study, the results are compared in order to select the combination that supplies the best ride comfort.
Intelligent control based on fuzzy logic and neural net theory
Lee, Chuen-Chien
1991-01-01
In the conception and design of intelligent systems, one promising direction involves the use of fuzzy logic and neural network theory to enhance such systems' capability to learn from experience and adapt to changes in an environment of uncertainty and imprecision. Here, an intelligent control scheme is explored by integrating these multidisciplinary techniques. A self-learning system is proposed as an intelligent controller for dynamical processes, employing a control policy which evolves and improves automatically. One key component of the intelligent system is a fuzzy logic-based system which emulates human decision making behavior. It is shown that the system can solve a fairly difficult control learning problem. Simulation results demonstrate that improved learning performance can be achieved in relation to previously described systems employing bang-bang control. The proposed system is relatively insensitive to variations in the parameters of the system environment.
Pneumatic motor speed control by trajectory tracking fuzzy logic controller
Indian Academy of Sciences (India)
Cengiz Safak; Vedat Topuz; A Fevzi Baba
2010-02-01
In this study, trajectory tracking fuzzy logic controller (TTFLC) is proposed for the speed control of a pneumatic motor (PM). A third order trajectory is deﬁned to determine the trajectory function that has to be tracked by the PM speed. Genetic algorithm (GA) is used to ﬁnd the TTFLC boundary values of membership functions (MF) and weights of control rules. In addition, artiﬁcial neural networks (ANN) modelled dynamic behaviour of PM is given. This ANN model is used to ﬁnd the optimal TTFLC parameters by ofﬂine GA approach. The experimental results show that designed TTFLC successfully enables the PM speed track the given trajectory under various working conditions. The proposed approach is superior to PID controller. It also provides simple and easy design procedure for the PM speed control problem.
Fuzzy Logic Control for Suspension Systems of Tracked Vehicles
Institute of Scientific and Technical Information of China (English)
YU Yang; WEI Xue-xia; ZHANG Yong-fa
2009-01-01
A scheme of fuzzy logic control for the suspension system of a tracked vehicle is presented.A mechanical model for the whole body of a tracked vehicle,which is totally a fifteen-degree-of-freedom system,is established.The model includes the vertical motion,the pitch motion as well as the roll motion of the tracked vehicle.In contrast to most previous studies,the coupling effect among the vertical,the pitch and the roll motions of the suspension system of a tracked vehicle is considered simultaneously.The simulation of fuzzy logic control under road surface with random excitation shows that the acceleration,pitch angle and roll angle of suspension system can be efficiently controlled.
Fuzzy Logic Supervised Teleoperation Control for Mobile Robot
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
The supervised teleoperation control is presented for a mobile robot to implement the tasks by using fuzzy logic. The teleoperation control system includes joystick based user interaction mechanism, the high level instruction set and fuzzy logic behaviors integrated in a supervised autonomy teleoperation control system for indoor navigation. These behaviors include left wall following, right wall following, turn left, turn right, left obstacle avoidance, right obstacle avoidance and corridor following based on ultrasonic range finders data. The robot compares the instructive high level command from the operator and relays back a suggestive signal back to the operator in case of mismatch between environment and instructive command. This strategy relieves the operator's cognitive burden, handle unforeseen situations and uncertainties of environment autonomously. The effectiveness of the proposed method for navigation in an unstructured environment is verified by experiments conducted on a mobile robot equipped with only ultrasonic range finders for environment sensing.
Performance of Networked DC Motor with Fuzzy Logic Controller
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B. Sharmila
2010-07-01
Full Text Available In the recent years the usage of data networks has been increased due to its cost effective and flexible applications. A shared data network can effectively reduce complicated wiring connections, installation and maintenance for connecting a complex control system with various sensors, actuators, and controllers as a networked control system. For the time-sensitive application with networked control system the remote dc motor actuation control has been chosen. Due to time-varying network traffic demands and disturbances, the guarantee of transmitting signals without any delays or data losses plays a vital role for the performances in using networked control systems. This paper proposes Fuzzy Logic Controller methodology in the networked dc motor control and the results are compared with the performance of the system with Ziegler-Nichols Tuned Proportional-Integral-Derivative Controller and Fuzzy Modulated Proportional-Integral-Derivative Controller. Simulations results are presented to demonstrate the proposed schemes in a closed loop control. The effective results show that the performance of networked control dc motor is improved by using Fuzzy Logic Controller than the other controllers.
STATOR FLUX OPTIMIZATION ON DIRECT TORQUE CONTROL WITH FUZZY LOGIC
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Fatih Korkmaz
2012-07-01
Full Text Available The Direct Torque Control (DTC is well known as an effective control technique for high performance drives in a wide variety of industrial applications and conventional DTC technique uses two constant reference value: torque and stator flux. In this paper, fuzzy logic based stator flux optimization technique for DTC drives that has been proposed. The proposed fuzzy logic based stator flux optimizer self-regulates the stator flux reference using induction motor load situation without need of any motor parameters. Simulation studies have been carried out with Matlab/Simulink to compare the proposed system behaviors at vary load conditions. Simulation results show that the performance of the proposed DTC technique has been improved and especially at low-load conditions torque ripple are greatly reduced with respect to the conventional DTC.
Boumediene ALLAOUA; Laoufi, Abdellah; Brahim GASBAOUI; Nasri, Abdelfatah; Abdessalam ABDERRAHMANI
2008-01-01
In this paper, an intelligent controller of the DC (Direct current) Motor drive is designed using fuzzy logic-genetic algorithms optimization. First, a controller is designed according to fuzzy rules such that the systems are fundamentally robust. To obtain the globally optimal values, parameters of the fuzzy controller are improved by genetic algorithms optimization model. Computer MATLAB work space demonstrate that the fuzzy controller associated to the genetic algorithms approach became ve...
Use of UPFC device controlled by fuzzy logic controllers for decoupled power flow control
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Ivković Sanja
2014-01-01
Full Text Available This paper investigates the possibility of decoupled active and reactive power flow control in a power system using a UPFC device controlled by fuzzy logic controllers. A Brief theoretical review of the operation principles and applications of UPFC devices and design principles of the fuzzy logic controller used are given. A Matlab/Simulink model of the system with UPFC, the fuzzy controller setup, and graphs of the results are presented. Conclusions are drawn regarding the possibility of using this system for decoupled control of the power flow in power systems based on analysis of these graphs.
Motion Control of the Soccer Robot Based on Fuzzy Logic
Coman, Daniela; Ionescu, Adela
2009-08-01
Robot soccer is a challenging platform for multi-agent research, involving topics such as real-time image processing and control, robot path planning, obstacle avoidance and machine learning. The conventional robot control consists of methods for path generation and path following. When a robot moves away the estimated path, it must return immediately, and while doing so, the obstacle avoidance behavior and the effectiveness of such a path are not guaranteed. So, motion control is a difficult task, especially in real time and high speed control. This paper describes the use of fuzzy logic control for the low level motion of a soccer robot. Firstly, the modelling of the soccer robot is presented. The soccer robot based on MiroSoT Small Size league is a differential-drive mobile robot with non-slipping and pure-rolling. Then, the design of fuzzy controller is describes. Finally, the computer simulations in MATLAB Simulink show that proposed fuzzy logic controller works well.
A reinforcement learning-based architecture for fuzzy logic control
Berenji, Hamid R.
1992-01-01
This paper introduces a new method for learning to refine a rule-based fuzzy logic controller. A reinforcement learning technique is used in conjunction with a multilayer neural network model of a fuzzy controller. The approximate reasoning based intelligent control (ARIC) architecture proposed here learns by updating its prediction of the physical system's behavior and fine tunes a control knowledge base. Its theory is related to Sutton's temporal difference (TD) method. Because ARIC has the advantage of using the control knowledge of an experienced operator and fine tuning it through the process of learning, it learns faster than systems that train networks from scratch. The approach is applied to a cart-pole balancing system.
Abihana, Osama A.; Gonzalez, Oscar R.
1993-01-01
The main objectives of our research are to present a self-contained overview of fuzzy sets and fuzzy logic, develop a methodology for control system design using fuzzy logic controllers, and to design and implement a fuzzy logic controller for a real system. We first present the fundamental concepts of fuzzy sets and fuzzy logic. Fuzzy sets and basic fuzzy operations are defined. In addition, for control systems, it is important to understand the concepts of linguistic values, term sets, fuzzy rule base, inference methods, and defuzzification methods. Second, we introduce a four-step fuzzy logic control system design procedure. The design procedure is illustrated via four examples, showing the capabilities and robustness of fuzzy logic control systems. This is followed by a tuning procedure that we developed from our design experience. Third, we present two Lyapunov based techniques for stability analysis. Finally, we present our design and implementation of a fuzzy logic controller for a linear actuator to be used to control the direction of the Free Flight Rotorcraft Research Vehicle at LaRC.
On-line fuzzy logic control of tube bending
Lieh, Junghsen; Li, Wei Jie
2005-11-01
This paper describes the simulation and on-line fuzzy logic control of tube bending. By combining elasticity and plasticity theories, a conventional model was developed. The results from simulation were compared with those obtained from testing. The experimental data reveal that there exists certain level of uncertainty and nonlinearity in tube bending, and its variation could be significant. To overcome this, a on-line fuzzy logic controller with self-tuning capabilities was designed. The advantages of this on-line system are (1) its computational requirement is simple in comparison with more algorithmic-based controllers, and (2) the system does not need prior knowledge of material characteristics. The device includes an AC motor, a servo controller, a forming mechanism, a 3D optical sensor, and a microprocessor. This automated bending machine adopts primary and secondary errors between the actual response and desired output to conduct on-line rule reasoning. Results from testing show that the spring back angle can be effectively compensated by the self- tuning fuzzy system in a real-time fashion.
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Mohammed Shoeb Mohiuddin
2014-09-01
Full Text Available It is often difficult to develop an accurate mathematical model of DC motor due to unknown load variation, unknown and unavoidable parameter variations or nonlinearities due to saturation temperature variations and system disturbances. Fuzzy logic application can handle such nonlinearities so that the controller design is fundamentally robust which is not possible in conventional controllers. The knowledge base of a fuzzy logic controller (FLC encapsulates expert knowledge and consists of the Data base (membership functions and Rule-Base of the controller. Optimization of both these knowledge base components is critical to the performance of the controller and has traditionally been achieved through a process of trial and error. Such an approach is convenient for FLCs having low numbers of input variables however for greater numbers of inputs, more formal methods of knowledge base optimization are required. In this work, we study the challenging task of controlling the speed of DC motor. The feasibility of such controller design is evaluated by simulation in the MATLAB/Simulink environment. In this study Conventional Proportional Integral Derivative controller, Fuzzy logic controller using a chopper circuit and Fuzzy tuned PID controller are analyzed and compared. Simulation software like MATLAB with Simulink has been used for modeling and simulation purpose. The performance comparison of conventional controller with Fuzzy logic controller using chopper circuit and Fuzzy tuned PID controller has been done in terms of several performance measures Such as Settling time, Rise time and Overshoot.
Stabilization of synchronous generator by fuzzy logic controlled braking resistor
Energy Technology Data Exchange (ETDEWEB)
Ali, M.H.; Funamoto, T.; Murata, T.; Tamura, J. [Kitami Inst. of Technology, Dept. of Electrical and Electronic Engineering, Hokkaido (Japan)
2000-08-01
In order to enhance the transient stability of synchronous generator, a fuzzy logic switching control scheme for the braking resistor is proposed. Following a fault, variable rotor speed of the generator is measured and the firing-angle of the thyristor switch in the braking resistor is determined from the crispy output of the fuzzy controller. By controlling the firing-angle of the thyristor, braking resistor can control the accelerating power in generator and thus improves the transient stability. Simulation results have been demonstrated for both balanced and unbalanced faults. It can be concluded from the simulation results that the proposed strategy provides a simple and effective method of stabilization of synchronous generator under transient conditions. (orig.)
Realization of Fuzzy Logic Controlled Brushless DC Motor Drives Using Matlab/Simulink
Çunkas, Mehmet; Aydoğdu, Omer
2010-01-01
In this paper, an efficient simulation model for fuzzy logic controlled brushless direct current motor drives using Matlab/Simulink is presented. The brushless direct current (BLDC) motor is efficiently controlled by Fuzzy logic controller (FLC). The control algorithms, fuzzy logic and PID are compared. Also, the dynamic characteristics of the BLDC motor (i.e. speed and torque) and as well as currents and voltages of the inverter components are easily observed and analyzed by using the develo...
Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation
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Hajer Omrane
2016-01-01
Full Text Available This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation and obstacle avoidance. The used mobile robot is equipped with DC motor, nine infrared range (IR sensors to measure the distance to obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent navigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform. Simulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path.
Fuzzy Logic Control of a Ball on Sphere System
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Seyed Alireza Moezi
2014-01-01
Full Text Available The scope of this paper is to present a fuzzy logic control of a class of multi-input multioutput (MIMO nonlinear systems called “system of ball on a sphere,” such an inherently nonlinear, unstable, and underactuated system, considered truly to be two independent ball and wheel systems around its equilibrium point. In this work, Sugeno method is investigated as a fuzzy controller method, so it works in a good state with optimization and adaptive techniques, which makes it very attractive in control problems, particularly for such nonlinear dynamic systems. The system’s dynamic is described and the equations are illustrated. The outputs are shown in different figures so as to be compared. Finally, these simulation results show the exactness of the controller’s performance.
Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation
Masmoudi, Mohamed Slim; Masmoudi, Mohamed
2016-01-01
This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation and obstacle avoidance. The used mobile robot is equipped with DC motor, nine infrared range (IR) sensors to measure the distance to obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent navigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform. Simulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path. PMID:27688748
Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation.
Omrane, Hajer; Masmoudi, Mohamed Slim; Masmoudi, Mohamed
This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation and obstacle avoidance. The used mobile robot is equipped with DC motor, nine infrared range (IR) sensors to measure the distance to obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent navigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform. Simulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path.
Toward a fuzzy logic control of the infant incubator.
Reddy, Narender P; Mathur, Garima; Hariharan, S I
2009-10-01
Premature birth is a world wide problem. Thermo regulation is a major problem in premature infants. Premature infants are often kept in infant incubators providing convective heating. Currently either the incubator air temperature is sensed and used to control the heat flow, or infant's skin temperature is sensed and used in the close loop control. Skin control often leads to large fluctuations in the incubator air temperature. Air control also leads to skin temperature fluctuations. The question remains if both the infant's skin temperature and the incubator air temperature can be simultaneously used in the control. The purpose of the present study was to address this question by developing a fuzzy logic control which incorporates both incubator air temperature and infant's skin temperature to control the heating. The control was evaluated using a lumped parameter mathematical model of infant-incubator system (Simon, B. N., N. P. Reddy, and A. Kantak, J. Biomech. Eng. 116:263-266, 1994). Simulation results confirmed previous experimental results that the on-off skin control could lead to fluctuations in the incubator air temperature, and the air control could lead to too slow rise time in the core temperature. The fuzzy logic provides a smooth control with the desired rise time.
Composite Fuzzy Logic Control Approach to a Flexible Joint Manipulator
Directory of Open Access Journals (Sweden)
Mohd Ashraf Ahmad
2013-01-01
Full Text Available The raised complicatedness of the dynamics of a robot manipulator considering joint elasticity makes conventional model‐based control strategies complex and hard to synthesize. This paper presents investigations into the development of hybrid intelligent control schemes for the trajectory tracking and vibration control of a flexible joint manipulator. To study the effectiveness of the controllers, a collocated proportional‐derivative (PD‐type Fuzzy Logic Controller (FLC is first developed for the tip angular position control of a flexible joint manipulator. This is then extended to incorporate a non‐collocated Fuzzy Logic Controller, a non‐collocated proportional‐ integral‐derivative (PID and an input‐shaping scheme for the vibration reduction of the flexible joint system. The positive zero‐vibration‐derivative‐derivative (ZVDD shaper is designed based on the properties of the system. The implementation results of the response of the flexible joint manipulator with the controllers are presented in time and frequency domains. The performances of the hybrid control schemes are examined in terms of input tracking capability, level of vibration reduction and time response specifications. Finally, a comparative assessment of the control techniques is presented and discussed.
Fuzzy Logic Controller for Low Temperature Application
Hahn, Inseob; Gonzalez, A.; Barmatz, M.
1996-01-01
The most common temperature controller used in low temperature experiments is the proportional-integral-derivative (PID) controller due to its simplicity and robustness. However, the performance of temperature regulation using the PID controller depends on initial parameter setup, which often requires operator's expert knowledge on the system. In this paper, we present a computer-assisted temperature controller based on the well known.
A new approach of active compliance control via fuzzy logic control for multifingered robot hand
Jamil, M. F. A.; Jalani, J.; Ahmad, A.
2016-07-01
Safety is a vital issue in Human-Robot Interaction (HRI). In order to guarantee safety in HRI, a model reference impedance control can be a very useful approach introducing a compliant control. In particular, this paper establishes a fuzzy logic compliance control (i.e. active compliance control) to reduce impact and forces during physical interaction between humans/objects and robots. Exploiting a virtual mass-spring-damper system allows us to determine a desired compliant level by understanding the behavior of the model reference impedance control. The performance of fuzzy logic compliant control is tested in simulation for a robotic hand known as the RED Hand. The results show that the fuzzy logic is a feasible control approach, particularly to control position and to provide compliant control. In addition, the fuzzy logic control allows us to simplify the controller design process (i.e. avoid complex computation) when dealing with nonlinearities and uncertainties.
Fuzzy Logic Trajectory Tracking Controller for a Tanker
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Dur Muhammad Pathan
2012-04-01
Full Text Available This paper proposes a fuzzy logic controller for design of autopilot of a ship. Triangular membership functions have been use for fuzzification and the centroid method for defuzzification. A nonlinear mathematical model of an oil tanker has been considered whose parameters vary with the depth of water. The performance of proposed controller has been tested under both course changing and trajectory keeping mode of operations. It has been demonstrated that the performance is robust in shallow as well as deep waters.
An Adaptive Fuzzy-Logic Traffic Control System in Conditions of Saturated Transport Stream
Marakhimov, A. R.; Igamberdiev, H. Z.; Umarov, Sh. X.
2016-01-01
This paper considers the problem of building adaptive fuzzy-logic traffic control systems (AFLTCS) to deal with information fuzziness and uncertainty in case of heavy traffic streams. Methods of formal description of traffic control on the crossroads based on fuzzy sets and fuzzy logic are proposed. This paper also provides efficient algorithms for implementing AFLTCS and develops the appropriate simulation models to test the efficiency of suggested approach. PMID:27517081
Control of Rotary Cranes Using Fuzzy Logic
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Amjed A. Al-mousa
2003-01-01
Full Text Available Rotary cranes (tower cranes are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them has become difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control attractive.
Moini, A
2002-01-01
In this paper, genetic algorithms are used in the design and robustification various mo el-ba ed/non-model-based fuzzy-logic controllers for robotic manipulators. It is demonstrated that genetic algorithms provide effective means of designing the optimal set of fuzzy rules as well as the optimal domains of associated fuzzy sets in a new class of model-based-fuzzy-logic controllers. Furthermore, it is shown that genetic algorithms are very effective in the optimal design and robustification of non-model-based multivariable fuzzy-logic controllers for robotic manipulators.
Error Correction, Control Systems and Fuzzy Logic
Smith, Earl B.
2004-01-01
This paper will be a discussion on dealing with errors. While error correction and communication is important when dealing with spacecraft vehicles, the issue of control system design is also important. There will be certain commands that one wants a motion device to execute. An adequate control system will be necessary to make sure that the instruments and devices will receive the necessary commands. As it will be discussed later, the actual value will not always be equal to the intended or desired value. Hence, an adequate controller will be necessary so that the gap between the two values will be closed.
Design of a Tele-Control Electrical Vehicle System Using a Fuzzy Logic Control
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M. Boukhnifer
2012-11-01
Full Text Available This paper presents a fuzzy logic design of a tele-control electrical vehicle system. We showed that the application of fuzzy logic control allows the stability of tele-vehicle system in spite of communication delays between the operator and the vehicle. A robust bilateral controller design using fuzzy logic frameworks was proposed. This approach allows a convenient means to trade off robustness and stability for a pre-specified time-delay margin. Both the performance and robustness of the proposed method were demonstrated by simulation results for a constant time delay between the operator and the electrical vehicle system.
Control of Single Axis Magnetic Levitation System Using Fuzzy Logic Control
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Tania Tariq Salim
2013-12-01
Full Text Available This paper presents a fuzzy logic controller design for the stabilization of magnetic levitation system (Maglev 's.Additionally, the investigation on Linear Quadratic Regulator Controller (LQRC also mentioned here. This paper presents the difference between the performance of fuzzy logic control (FLC and LQRC for the same linear model of magnetic levitation system .A magnetic levitation is a nonlinear unstable system and the fuzzy logic controller brings the magnetic levitation system to a stable region by keeping a magnetic ball suspended in the air. The modeling of the system is simulated using Matlab Simulink and connected to Hilink platform and the maglev model of Zeltom company. This paper presents a comparison for both LQRC and FLC to control a ball suspended on the air. The performance results of simulation shows that the fuzzy logic controller had better performance than the LQR control.
A Development of Self-Organization Algorithm for Fuzzy Logic Controller
Energy Technology Data Exchange (ETDEWEB)
Park, Y.M.; Moon, U.C. [Seoul National Univ. (Korea, Republic of). Coll. of Engineering; Lee, K.Y. [Pennsylvania State Univ., University Park, PA (United States). Dept. of Electrical Engineering
1994-09-01
This paper proposes a complete design method for an on-line self-organizing fuzzy logic controller without using any plant model. By mimicking the human learning process, the control algorithm finds control rules of a system for which little knowledge has been known. To realize this, a concept of Fuzzy Auto-Regressive Moving Average(FARMA) rule is introduced. In a conventional fuzzy logic control, knowledge on the system supplied by an expert is required in developing control rules. However, the proposed new fuzzy logic controller needs no expert in making control rules. Instead, rules are generated using the history of input-output pairs, and new inference and defuzzification methods are developed. The generated rules are strode in the fuzzy rule space and updated on-line by a self-organizing procedure. The validity of the proposed fuzzy logic control method has been demonstrated numerically in controlling an inverted pendulum. (author). 28 refs., 16 figs.
An Application of Fuzzy Logic Control to a Classical Military Tracking Problem
1994-05-19
of Fuzzy Logic Fuzzy logic was born in 1965 with the publication of Lofti Zadeh’s landmark paper, "Fuzzy Sets".’ Human beings, Zadeh observed, make...hundreds of decisions every day based on limited information. These observations grew into the concept of "fuzzy logic", the term Zadeh coined to...Section 7 - References Cited 1. Zadeh , L.A. "Fuzzy Sets", Information and Control, vol.8, 1965, pp.338-353. 2. Brubaker, David I., and Cedric Sheerer
FUZZY LOGIC CONTROL OF ELECTRIC MOTORS AND MOTOR DRIVES: FEASIBILITY STUDY
The report gives results of a study (part 1) of fuzzy logic motor control (FLMC). The study included: 1) reviews of existing applications of fuzzy logic, of motor operation, and of motor control; 2) a description of motor control schemes that can utilize FLMC; 3) selection of a m...
Institute of Scientific and Technical Information of China (English)
刘叙华; 邓安生
1994-01-01
A new approach of operator fuzzy logic, Boolean operator fuzzy logic (BOFL) based on Boolean algebra, is presented. The resolution principle is also introduced into BOFL. BOFL is a natural generalization of classical logic and can be applied to the qualitative description of fuzzy knowledge.
Nguyen, Hung T
2005-01-01
THE CONCEPT OF FUZZINESS Examples Mathematical modeling Some operations on fuzzy sets Fuzziness as uncertainty Exercises SOME ALGEBRA OF FUZZY SETS Boolean algebras and lattices Equivalence relations and partitions Composing mappings Isomorphisms and homomorphisms Alpha-cuts Images of alpha-level sets Exercises FUZZY QUANTITIES Fuzzy quantities Fuzzy numbers Fuzzy intervals Exercises LOGICAL ASPECTS OF FUZZY SETS Classical two-valued logic A three-valued logic Fuzzy logic Fuzzy and Lukasiewi
Fuzzy logic control of vehicle suspensions with dry friction nonlinearity
Indian Academy of Sciences (India)
L Emir Sakman; Rahmi Guclu; Nurkan Yagiz
2005-10-01
We design and investigate the performance of fuzzy logic-controlled (FLC) active suspensions on a nonlinear vehicle model with four degrees of freedom, without causing any degeneration in suspension working limits. Force actuators were mounted parallel to the suspensions. In this new approach, linear combinations of the vertical velocities of the suspension ends and accelerations of the points of connection of the suspension to the body have been used as input variables. The study clearly demonstrates the effectiveness of the fuzzy logic controller for active suspension systems. Suspension working space degeneration is the most important problem in various applications. Decreasing the amplitudes of vehicle body vibrations improves ride comfort. Body bounce and pitch motion of the vehicle are presented both in time domain when travelling over a ramp-step road proﬁle and in frequency domain. The results are compared with those of uncontrolled systems. At the end of this study, the performance and the advantage of the suggested approach and the improvement in ride comfort are discussed.
Controlling Smart Green House Using Fuzzy Logic Method
Directory of Open Access Journals (Sweden)
Rafiuddin Syam
2015-10-01
Full Text Available To increase agricultural output it is needed a system that can help the environmental conditions for optimum plant growth. Smart greenhouse allows for plants to grow optimally, because the temperature and humidity can be controlled so that no drastic changes. It is necessary for optimal smart greenhouse needed a system to manipulate the environment in accordance with the needs of the plant. In this case the setting temperature and humidity in the greenhouse according to the needs of the plant. So using an automated system for keeping such environmental condition is important. In this study, the authors use fuzzy logic to make the duration of watering the plants more dynamic in accordance with the input temperature and humidity so that the temperature and humidity in the green house plants maintained in accordance to the reference condition. Based on the experimental results using fuzzy logic method is effective to control the duration of watering and to maintain the optimum temperature and humidity inside the greenhouse
Adaptive process control using fuzzy logic and genetic algorithms
Karr, C. L.
1993-01-01
Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.
Control of a dc motor using fuzzy logic control algorithm | Usoro ...
African Journals Online (AJOL)
This study sought to establish the impact of a fuzzy logic controller (FLC) and a ... A choice of seven membership functions was designed for the error and change in ... Based on the findings, it was observed that the fuzzy speed controlled DC ...
Metamathematics of fuzzy logic
Hájek, Petr
1998-01-01
This book presents a systematic treatment of deductive aspects and structures of fuzzy logic understood as many valued logic sui generis. Some important systems of real-valued propositional and predicate calculus are defined and investigated. The aim is to show that fuzzy logic as a logic of imprecise (vague) propositions does have well-developed formal foundations and that most things usually named `fuzzy inference' can be naturally understood as logical deduction.
Design and implementation of a fuzzy logic yaw controller
Wu, Kung C.; Swift, Andrew H.; Craver, W. Lionel, Jr.; Chang, Yi-Chieh
1993-08-01
This paper describes a fuzzy logic controller (FLC) designed and implemented to control the yaw angle of a 10 kW fixed speed teetered-rotor wind turbine presently being commissioned at the University of Texas at El Paso. The technical challenge of this project is that the wind turbine represents a highly stochastic nonlinear system. The problems associated with the wind turbine yaw control are of a similar nature as those experienced with position control of high inertia equipment like tracking antenna, gun turrets, and overhead cranes. Furthermore, the wind turbine yaw controller must be extremely cost-effective and highly reliable in order to be economically viable compared to the fossil fueled power generators.
Design and Simulation of Fuzzy Logic controller for DSTATCOM In Power System
Anju Gupta; SHARMA, P. R.
2011-01-01
In this paper design of self tuned fuzzy set theory based PI controller is incorporated in typical FACTS device DSTATCOM. Its effects are tested in power systems. The modeling and the controller block diagram for DSTATCOM with detailed design of self tuned fuzzy logic controller is presented. The performance of proposed fuzzy logic DSTATCOM has been simulated for current balancing and harmonic compensation for both linear and non-linear loads. The results show the capability of proposed model...
Fuzzy Logic Controller based on geothermal recirculating aquaculture system
Directory of Open Access Journals (Sweden)
Hanaa M. Farghally
2014-01-01
Full Text Available One of the most common uses of geothermal heat is in recirculation aquaculture systems (RAS where the water temperature is accurately controlled for optimum growing conditions for sustainable and intensive rearing of marine and freshwater fish. This paper presents a design for RAS rearing tank and brazed heat exchanger to be used with geothermal energy as a source of heating water. The heat losses from the RAS tank are calculated using Geo Heat Center Software. Then a plate type heat exchanger is designed using the epsilon – NTU analysis method. For optimal growth and abundance of production, a Fuzzy Logic control (FLC system is applied to control the water temperature (29 °C. A FLC system has several advantages over conventional techniques; relatively simple, fast, adaptive, and its response is better and faster at all atmospheric conditions. Finally, the total system is built in MATLAB/SIMULINK to study the overall performance of control unit.
Application of Fuzzy Logic Controller to Level Control of Twin-Roll Strip Casting
Institute of Scientific and Technical Information of China (English)
QI Chun-yu; DI Hong-shuang; ZHANG Xiao-ming; GAO De-fu
2003-01-01
An intelligent fuzzy-PID controller consisting of fuzzy logic controller and PID controller was developed to control the molten steel level of twin-roll strip caster. Additionally, a feedforward differential PID controller was used for stopper position control in order to avoid differential kick. It is proved by simulation that the proposed intelligent controller is able to obtain zero steady state error asymptotically and the control system is robust due to its fuggy behavior of the controller.
Directory of Open Access Journals (Sweden)
Boumediene ALLAOUA
2008-12-01
Full Text Available In this paper, an intelligent controller of the DC (Direct current Motor drive is designed using fuzzy logic-genetic algorithms optimization. First, a controller is designed according to fuzzy rules such that the systems are fundamentally robust. To obtain the globally optimal values, parameters of the fuzzy controller are improved by genetic algorithms optimization model. Computer MATLAB work space demonstrate that the fuzzy controller associated to the genetic algorithms approach became very strong, gives a very good results and possesses good robustness.
Implementation of a fuzzy logic PSS using Intel 8051 micro-controller
Energy Technology Data Exchange (ETDEWEB)
El-Metwally, K.A.; Malik, O.P. [Univ. of Calgary (Canada). Dept. of Electrical and Computer Engineering
1995-11-01
Implementation of a fuzzy logic based power system stabilizer using the general purpose low cost Intel 8051FA micro-controller is described in the paper. Results of extensive on-line tests performed for a variety of disturbances and operating conditions are presented. These results amply demonstrate the effectiveness of the fuzzy logic based stabilizer. 8 refs, 9 figs, 1 tab
Fuzzy Logic Controller Scheme for Floor Vibration Control
Directory of Open Access Journals (Sweden)
Nyawako Donald Steve
2015-01-01
Full Text Available The design of civil engineering floors is increasingly being governed by their vibration serviceability performance. This trend is the result of advancements in design technologies offering designers greater flexibilities in realising more lightweight, longer span and more open-plan layouts. These floors are prone to excitation from human activities. The present research work looks at analytical studies of active vibration control on a case study floor prototype that has been specifically designed to be representative of a real office floor structure. Specifically, it looks at tuning fuzzy control gains with the aim of adapting them to measured structural responses under human excitation. Vibration mitigation performances are compared with those of a general velocity feedback controller, and these are found to be identical in these sets of studies. It is also found that slightly less control force is required for the fuzzy controller scheme at moderate to low response levels and as a result of the adaptive gain, at very low responses the control force is close to zero, which is a desirable control feature. There is also saturation in the peak gain with the fuzzy controller scheme, with this gain tending towards the optimal feedback gain of the direct velocity feedback (DVF at high response levels for this fuzzy design.
A fuzzy logic controller for an autonomous mobile robot
Yen, John; Pfluger, Nathan
1993-01-01
The ability of a mobile robot system to plan and move intelligently in a dynamic system is needed if robots are to be useful in areas other than controlled environments. An example of a use for this system is to control an autonomous mobile robot in a space station, or other isolated area where it is hard or impossible for human life to exist for long periods of time (e.g., Mars). The system would allow the robot to be programmed to carry out the duties normally accomplished by a human being. Some of the duties that could be accomplished include operating instruments, transporting objects, and maintenance of the environment. The main focus of our early work has been on developing a fuzzy controller that takes a path and adapts it to a given environment. The robot only uses information gathered from the sensors, but retains the ability to avoid dynamically placed obstacles near and along the path. Our fuzzy logic controller is based on the following algorithm: (1) determine the desired direction of travel; (2) determine the allowed direction of travel; and (3) combine the desired and allowed directions in order to determine a direciton that is both desired and allowed. The desired direction of travel is determined by projecting ahead to a point along the path that is closer to the goal. This gives a local direction of travel for the robot and helps to avoid obstacles.
Howard, Ayanna
2005-01-01
The Fuzzy Logic Engine is a software package that enables users to embed fuzzy-logic modules into their application programs. Fuzzy logic is useful as a means of formulating human expert knowledge and translating it into software to solve problems. Fuzzy logic provides flexibility for modeling relationships between input and output information and is distinguished by its robustness with respect to noise and variations in system parameters. In addition, linguistic fuzzy sets and conditional statements allow systems to make decisions based on imprecise and incomplete information. The user of the Fuzzy Logic Engine need not be an expert in fuzzy logic: it suffices to have a basic understanding of how linguistic rules can be applied to the user's problem. The Fuzzy Logic Engine is divided into two modules: (1) a graphical-interface software tool for creating linguistic fuzzy sets and conditional statements and (2) a fuzzy-logic software library for embedding fuzzy processing capability into current application programs. The graphical- interface tool was developed using the Tcl/Tk programming language. The fuzzy-logic software library was written in the C programming language.
Autonomous Control of a Quadrotor UAV Using Fuzzy Logic
Sureshkumar, Vijaykumar
UAVs are being increasingly used today than ever before in both military and civil applications. They are heavily preferred in "dull, dirty or dangerous" mission scenarios. Increasingly, UAVs of all kinds are being used in policing, fire-fighting, inspection of structures, pipelines etc. Recently, the FAA gave its permission for UAVs to be used on film sets for motion capture and high definition video recording. The rapid development in MEMS and actuator technology has made possible a plethora of UAVs that are suited for commercial applications in an increasingly cost effective manner. An emerging popular rotary wing UAV platform is the Quadrotor A Quadrotor is a helicopter with four rotors, that make it more stable; but more complex to model and control. Characteristics that provide a clear advantage over other fixed wing UAVs are VTOL and hovering capabilities as well as a greater maneuverability. It is also simple in construction and design compared to a scaled single rotorcraft. Flying such UAVs using a traditional radio Transmitter-Receiver setup can be a daunting task especially in high stress situations. In order to make such platforms widely applicable, a certain level of autonomy is imperative to the future of such UAVs. This thesis paper presents a methodology for the autonomous control of a Quadrotor UAV using Fuzzy Logic. Fuzzy logic control has been chosen over conventional control methods as it can deal effectively with highly nonlinear systems, allows for imprecise data and is extremely modular. Modularity and adaptability are the key cornerstones of FLC. The objective of this thesis is to present the steps of designing, building and simulating an intelligent flight control module for a Quadrotor UAV. In the course of this research effort, a Quadrotor UAV is indigenously developed utilizing the resources of an online open source project called Aeroquad. System design is comprehensively dealt with. A math model for the Quadrotor is developed and a
Abdul Kareem; Mohammad Fazle Azeem
2012-01-01
This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness ...
Virtual Reality Simulation of Fuzzy-logic Control during Underwater Dynamic Positioning
Institute of Scientific and Technical Information of China (English)
Midhin Das Thekkedan; Cheng Siong Chin; Wai Lok Woo
2015-01-01
In this paper, graphical-user-interface (GUI) software for simulation and fuzzy-logic control of a remotely operated vehicle (ROV) using MATLABTM GUI Designing Environment is proposed. The proposed ROV’s GUI platform allows the controller such as fuzzy-logic control systems design to be compared with other controllers such as proportional-integral-derivative (PID) and sliding-mode controller (SMC) systematically and interactively. External disturbance such as sea current can be added to improve the modelling in actual underwater environment. The simulated results showed the position responses of the fuzzy-logic control exhibit reasonable performance under the sea current disturbance.
Identiﬁcation of Optimal Operating Point Of PV Modules Using Fuzzy Logic Control
Directory of Open Access Journals (Sweden)
Hadi nabizadeh
2013-11-01
Full Text Available This paper introduces an intelligent control method for maximum power point tracking in solar array in dealing with the rapid variations in temperature and radiation. Fuzzy logic controller and DC/DC boost converter are the most important components of this system. The simulation results of fuzzy logic controller are compared with simulation results of PI controller in both cases without noise and with Gaussian noise in solar cell voltage. The results show that fuzzy logic controller performance is better than PI controller especially in the presence of noise.
Virtual reality simulation of fuzzy-logic control during underwater dynamic positioning
Thekkedan, Midhin Das; Chin, Cheng Siong; Woo, Wai Lok
2015-03-01
In this paper, graphical-user-interface (GUI) software for simulation and fuzzy-logic control of a remotely operated vehicle (ROV) using MATLAB™ GUI Designing Environment is proposed. The proposed ROV's GUI platform allows the controller such as fuzzy-logic control systems design to be compared with other controllers such as proportional-integral-derivative (PID) and sliding-mode controller (SMC) systematically and interactively. External disturbance such as sea current can be added to improve the modelling in actual underwater environment. The simulated results showed the position responses of the fuzzy-logic control exhibit reasonable performance under the sea current disturbance.
Energy Technology Data Exchange (ETDEWEB)
Derrouazin, A., E-mail: derrsid@gmail.com [University Hassiba BenBouali of Chlef, LGEER,Chlef (Algeria); Université de Lorraine, LMOPS, EA 4423, 57070 Metz (France); CentraleSupélec, LMOPS, 57070 Metz (France); Aillerie, M., E-mail: aillerie@metz.supelec.fr; Charles, J. P. [Université de Lorraine, LMOPS, EA 4423, 57070 Metz (France); CentraleSupélec, LMOPS, 57070 Metz (France); Mekkakia-Maaza, N. [Université des sciences et de la Technologie d’Oran, Mohamed Boudiaf-USTO MB,LMSE, Oran Algérie (Algeria)
2016-07-25
Several researches for management of diverse hybrid energy systems and many techniques have been proposed for robustness, savings and environmental purpose. In this work we aim to make a comparative study between two supervision and control techniques: fuzzy and classic logics to manage the hybrid energy system applied for typical housing fed by solar and wind power, with rack of batteries for storage. The system is assisted by the electric grid during energy drop moments. A hydrogen production device is integrated into the system to retrieve surplus energy production from renewable sources for the household purposes, intending the maximum exploitation of these sources over years. The models have been achieved and generated signals for electronic switches command of proposed both techniques are presented and discussed in this paper.
Derrouazin, A.; Aillerie, M.; Mekkakia-Maaza, N.; Charles, J. P.
2016-07-01
Several researches for management of diverse hybrid energy systems and many techniques have been proposed for robustness, savings and environmental purpose. In this work we aim to make a comparative study between two supervision and control techniques: fuzzy and classic logics to manage the hybrid energy system applied for typical housing fed by solar and wind power, with rack of batteries for storage. The system is assisted by the electric grid during energy drop moments. A hydrogen production device is integrated into the system to retrieve surplus energy production from renewable sources for the household purposes, intending the maximum exploitation of these sources over years. The models have been achieved and generated signals for electronic switches command of proposed both techniques are presented and discussed in this paper.
Semiactive Self-Tuning Fuzzy Logic Control of Full Vehicle Model with MR Damper
Directory of Open Access Journals (Sweden)
Mahmut Paksoy
2014-09-01
Full Text Available Intelligent controllers are studied for vibration reduction of a vehicle consisting in a semiactive suspension system with a magnetorheological(MR damper. The vehicle is modeled with seven degrees of freedom as a full vehicle model. The semiactive suspension system consists of a linear spring and an MR damper. MR damper is modeled using Bouc-Wen hysteresis phenomenon and applied to a full vehicle model. Fuzzy Logic based controllers are designed to determine the MR damper voltage. Fuzzy Logic and Self-Tuning Fuzzy Logic controllers are applied to the semiactive suspension system. Results of the system are investigated by simulation studies in MATLAB-Simulink environment. The performance of the semiactive suspension system is analyzed with and without control. Simulation results showed that both Fuzzy Logic and Self-Tuning Fuzzy Logic controllers perform better compared to uncontrolled case. Furthermore, Self-Tuning Fuzzy Logic controller displayed a greater improvement in vibration reduction performance compared to Fuzzy Logic controller.
Efficiency of particle swarm optimization applied on fuzzy logic DC motor speed control
Directory of Open Access Journals (Sweden)
Allaoua Boumediene
2008-01-01
Full Text Available This paper presents the application of Fuzzy Logic for DC motor speed control using Particle Swarm Optimization (PSO. Firstly, the controller designed according to Fuzzy Logic rules is such that the systems are fundamentally robust. Secondly, the Fuzzy Logic controller (FLC used earlier was optimized with PSO so as to obtain optimal adjustment of the membership functions only. Finally, the FLC is completely optimized by Swarm Intelligence Algorithms. Digital simulation results demonstrate that in comparison with the FLC the designed FLC-PSO speed controller obtains better dynamic behavior and superior performance of the DC motor, as well as perfect speed tracking with no overshoot.
Carlsson, Christer; Fullér, Robert
2004-01-01
Fuzzy Logic in Management demonstrates that difficult problems and changes in the management environment can be more easily handled by bringing fuzzy logic into the practice of management. This explicit theme is developed through the book as follows: Chapter 1, "Management and Intelligent Support Technologies", is a short survey of management leadership and what can be gained from support technologies. Chapter 2, "Fuzzy Sets and Fuzzy Logic", provides a short introduction to fuzzy sets, fuzzy relations, the extension principle, fuzzy implications and linguistic variables. Chapter 3, "Group Decision Support Systems", deals with group decision making, and discusses methods for supporting the consensus reaching processes. Chapter 4, "Fuzzy Real Options for Strategic Planning", summarizes research where the fuzzy real options theory was implemented as a series of models. These models were thoroughly tested on a number of real life investments, and validated in 2001. Chapter 5, "Soft Computing Methods for Reducing...
Systematic methods for the design of a class of fuzzy logic controllers
Yasin, Saad Yaser
2002-09-01
Fuzzy logic control, a relatively new branch of control, can be used effectively whenever conventional control techniques become inapplicable or impractical. Various attempts have been made to create a generalized fuzzy control system and to formulate an analytically based fuzzy control law. In this study, two methods, the left and right parameterization method and the normalized spline-base membership function method, were utilized for formulating analytical fuzzy control laws in important practical control applications. The first model was used to design an idle speed controller, while the second was used to control an inverted control problem. The results of both showed that a fuzzy logic control system based on the developed models could be used effectively to control highly nonlinear and complex systems. This study also investigated the application of fuzzy control in areas not fully utilizing fuzzy logic control. Three important practical applications pertaining to the automotive industries were studied. The first automotive-related application was the idle speed of spark ignition engines, using two fuzzy control methods: (1) left and right parameterization, and (2) fuzzy clustering techniques and experimental data. The simulation and experimental results showed that a conventional controller-like performance fuzzy controller could be designed based only on experimental data and intuitive knowledge of the system. In the second application, the automotive cruise control problem, a fuzzy control model was developed using parameters adaptive Proportional plus Integral plus Derivative (PID)-type fuzzy logic controller. Results were comparable to those using linearized conventional PID and linear quadratic regulator (LQR) controllers and, in certain cases and conditions, the developed controller outperformed the conventional PID and LQR controllers. The third application involved the air/fuel ratio control problem, using fuzzy clustering techniques, experimental
Fuzzy Logic Based Control of Power of PEM Fuel Cell System for Residential Application
Directory of Open Access Journals (Sweden)
Khaled MAMMAR
2009-07-01
Full Text Available This paper presents a dynamic model of Fuel cell system for residential power generation. The models proposed include a fuel cell stack model, reformer model and DC/AC inverter model. Furthermore a fuzzy logic (FLC controller is used to control active power of PEM fuel cell system. The controller modifies the hydrogen flow feedback from the terminal load. Simulation results confirmed the high performance capability of the fuzzy logic controller to control power generation.
Fuzzy Logic Based Control of Power of PEM Fuel Cell System for Residential Application
Khaled MAMMAR; CHAKER, Abdelkader
2009-01-01
This paper presents a dynamic model of Fuel cell system for residential power generation. The models proposed include a fuel cell stack model, reformer model and DC/AC inverter model. Furthermore a fuzzy logic (FLC) controller is used to control active power of PEM fuel cell system. The controller modifies the hydrogen flow feedback from the terminal load. Simulation results confirmed the high performance capability of the fuzzy logic controller to control power generation.
National Research Council Canada - National Science Library
C, Subba Rami Reddy; M, Surya Kalavathi
2011-01-01
This paper introduces an Integrated fuzzy logic controller (IFLC) for brushless dc (BLDC) motor drives using advanced simulation model and presents a comparative study of performances of PID controller and IFLC...
Fuzzy Logic Control for Semi-Active Suspension System of Tracked Vehicle
Institute of Scientific and Technical Information of China (English)
管继富; 顾亮; 侯朝桢; 王国丽
2004-01-01
The model of half a tracked vehicle semi-active suspension is established. The fuzzy logic controller of the semi-active suspension system is constructed. The acceleration of driver's seat and its time derivative are used as the inputs of the fuzzy logic controller, and the fuzzy logic controller output determines the semi-active suspension controllable damping force. The fuzzy logic controller is to minimize the mean square root of acceleration of the driver's seat. The control forces of controllable dampers behind the first road wheel are obtained by time delay, and the delay times are determined by the vehicle speed and axles distances. The simulation results show that this control method can decrease the acceleration of driver's seat and the suspension travel of the first road wheel, the ride quality is improved obviously.
Fuzzy logic particle tracking velocimetry
Wernet, Mark P.
1993-01-01
Fuzzy logic has proven to be a simple and robust method for process control. Instead of requiring a complex model of the system, a user defined rule base is used to control the process. In this paper the principles of fuzzy logic control are applied to Particle Tracking Velocimetry (PTV). Two frames of digitally recorded, single exposure particle imagery are used as input. The fuzzy processor uses the local particle displacement information to determine the correct particle tracks. Fuzzy PTV is an improvement over traditional PTV techniques which typically require a sequence (greater than 2) of image frames for accurately tracking particles. The fuzzy processor executes in software on a PC without the use of specialized array or fuzzy logic processors. A pair of sample input images with roughly 300 particle images each, results in more than 200 velocity vectors in under 8 seconds of processing time.
ANFIS optimized semi-active fuzzy logic controller for magnetorheological dampers
César, Manuel Braz; Barros, Rui Carneiro
2016-11-01
In this paper, we report on the development of a neuro-fuzzy controller for magnetorheological dampers using an Adaptive Neuro-Fuzzy Inference System or ANFIS. Fuzzy logic based controllers are capable to deal with non-linear or uncertain systems, which make them particularly well suited for civil engineering applications. The main objective is to develop a semi-active control system with a MR damper to reduce the response of a three degrees-of-freedom (DOFs) building structure. The control system is designed using ANFIS to optimize the fuzzy inference rule of a simple fuzzy logic controller. The results show that the proposed semi-active neuro-fuzzy based controller is effective in reducing the response of structural system.
Fuzzy logic feedback control for fed-batch enzymatic hydrolysis of lignocellulosic biomass.
Tai, Chao; Voltan, Diego S; Keshwani, Deepak R; Meyer, George E; Kuhar, Pankaj S
2016-06-01
A fuzzy logic feedback control system was developed for process monitoring and feeding control in fed-batch enzymatic hydrolysis of a lignocellulosic biomass, dilute acid-pretreated corn stover. Digested glucose from hydrolysis reaction was assigned as input while doser feeding time and speed of pretreated biomass were responses from fuzzy logic control system. Membership functions for these three variables and rule-base were created based on batch hydrolysis data. The system response was first tested in LabVIEW environment then the performance was evaluated through real-time hydrolysis reaction. The feeding operations were determined timely by fuzzy logic control system and efficient responses were shown to plateau phases during hydrolysis. Feeding of proper amount of cellulose and maintaining solids content was well balanced. Fuzzy logic proved to be a robust and effective online feeding control tool for fed-batch enzymatic hydrolysis.
Design and fuzzy logic control of an active wrist orthosis.
Kilic, Ergin; Dogan, Erdi
2017-08-01
People who perform excessive wrist movements throughout the day because of their professions have a higher risk of developing lateral and medial epicondylitis. If proper precautions are not taken against these diseases, serious consequences such as job loss and early retirement can occur. In this study, the design and control of an active wrist orthosis that is mobile, powerful and lightweight is presented as a means to avoid the occurrence and/or for the treatment of repetitive strain injuries in an effective manner. The device has an electromyography-based control strategy so that the user's intention always comes first. In fact, the device-user interaction is mainly activated by the electromyography signals measured from the forearm muscles that are responsible for the extension and flexion wrist movements. Contractions of the muscles are detected using surface electromyography sensors, and the desired quantity of the velocity value of the wrist is extracted from a fuzzy logic controller. Then, the actuator system of the device comes into play by conveying the necessary motion support to the wrist. Experimental studies show that the presented device actually reduces the demand on the muscles involved in repetitive strain injuries while performing challenging daily life activities including extension and flexion wrist motions.
Fuzzy logic controller based three-phase shunt active power filter under unbalanced network
Energy Technology Data Exchange (ETDEWEB)
Belaidi, R.; Chikouche, A.; Fathi, M. [Unite de Developpement des Equipements Solaires (Algeria); Haddouche, A.; Guendouz, A. [Universite Badji Mokhtar (Algeria)], E-mail: rachidi3434@yahoo.fr
2011-07-01
In recent years, public awareness of power quality issues in distribution systems has arisen. The photovoltaic interactive shunt active power filter is a system which provides harmonic current damping and reactive power compensation and a fuzzy logic controller was created to adjust the energy storage of the DC voltage; the aim of this paper is to study the performance of the fuzzy logic controller. Simulations were performed using Matlab and Simulink and were analyzed to determine the effectiveness of the system; the instantaneous reactive power theory was utilized. Results showed that the use of the fuzzy logic controller achieves a reduction of the total harmonic distortion of the current from 26.54% to 2.27%. This study demonstrated that the fuzzy logic controller combined with the photovoltaic interactive shunt active power filter helps improve power quality by filtering harmonic currents and compensating reactive power generated by non-linear loads.
Fuzzy-logic approach to HTR nuclear power plant model control
Energy Technology Data Exchange (ETDEWEB)
Bubak, M.; Moscinski, J. (Akademia Gorniczo-Hutnicza, Krakow (Poland)); Jewulski, J. (Institute of Physical Chemistry, Krakow (Poland))
1983-01-01
The fuzzy-set theory is used to incorporate linguistic 'rules of the thumb' of a human operator in the HTR nuclear power plant controller. The results of the extensive computer simulations are encouraging and confirm the usefulness of this approach in nuclear power plant control. In the Appendix, a short introduction to fuzzy logic is given.
Using fuzzy logic for automatic control: Case study of a problem of cereals samples classification
Directory of Open Access Journals (Sweden)
Lakhoua Najeh Mohamed
2009-01-01
Full Text Available The aim of this paper is to present the use of fuzzy logic for automatic control of industrial systems particularly the way to approach a problem of classification. We present a case study of a grading system of cereals that allows us to determine the price of transactions of cereals in Tunisia. Our contribution in this work consists in proposing not only an application of the fuzzy logic on the grading system of cereals but also a methodology enabling the proposing of a new grading system based on the concept of 'Grade' while using the fuzzy logic techniques. .
Comparison between Conventional and Fuzzy Logic PID Controllers for Controlling DC Motors
Directory of Open Access Journals (Sweden)
Essam Natsheh
2010-09-01
Full Text Available Fuzzy logic and proportional-integral-derivative (PID controllers are compared for use in direct current (DC motors positioning system. A simulation study of the PID position controller for the armature-controlled with fixed field and field controlled with fixed armature current DC motors is performed. Fuzzy rules and the inferencing mechanism of the fuzzy logic controller (FLC are evaluated by using conventional rule-lookup tables that encode the control knowledge in a rules form. The performance assessment of the studied position controllers is based on transient response and error integral criteria. The results obtained from the FLC are not only superior in the rise time, speed fluctuations, and percent overshoot but also much better in the controller output signal structure, which is much remarkable in terms of the hardware implementation.
Z Source Inverter for Photovoltaic System with Fuzzy Logic Controller
Directory of Open Access Journals (Sweden)
Vijayabalan R
2012-10-01
Full Text Available In this paper, the photovoltaic system is used to extract the maximum power from sun to get the dc voltage. The output dc voltage is boost up into maximum voltage level by using the SEPIC converter. This converter voltage is fed to Z source inverter to get the AC voltage. The Z source inverter system can boost the given input voltage by controlling the boost factor, to obtain the maximum voltage. PWM technique which is used as to given the gating pulse to the inverter switches. Modified system is very promising for residential solar energy system. In stand-alone systems the solar energy yield is matched to the energy demand. Wherever it was not possible to install an electricity supply from the mains utility grid, or desirable, stand-alone photovoltaic systems could be installed. This proposed system is cost-effective for photovoltaic stand-alone applications. This paper describes the design of a rule based Fuzzy Logic Controller (FLC for Z Source inverter. The obtained AC Voltage contains harmonics of both odd and even harmonics of lower and higher order. Higher order harmonics are eliminated with the help of Filters. Here the impedance network act as a filter to reduce the lower order harmonics obtained in the system. So with the help of FFT analysis this value is obtained to be 15.82%.
Fuzzy logic based control system for fresh water aquaculture: A MATLAB based simulation approach
Directory of Open Access Journals (Sweden)
Rana Dinesh Singh
2015-01-01
Full Text Available Fuzzy control is regarded as the most widely used application of fuzzy logic. Fuzzy logic is an innovative technology to design solutions for multiparameter and non-linear control problems. One of the greatest advantages of fuzzy control is that it uses human experience and process information obtained from operator rather than a mathematical model for the definition of a control strategy. As a result, it often delivers solutions faster than conventional control design techniques. The proposed system is an attempt to apply fuzzy logic techniques to predict the stress factor on the fish, based on line data and rule base generated using domain expert. The proposed work includes a use of Data acquisition system, an interfacing device for on line parameter acquisition and analysis, fuzzy logic controller (FLC for inferring the stress factor. The system takes stress parameters on the fish as inputs, fuzzified by using FLC with knowledge base rules and finally provides single output. All the parameters are controlled and calibrated by the fuzzy logic toolbox and MATLAB programming.
Study and simulation of a MPPT controller based on fuzzy logic controller for photovoltaic system
Energy Technology Data Exchange (ETDEWEB)
Belaidi, R.; Chikouche, A.; Fathi, M.; Mohand Kaci, G.; Smara, Z. [Unite de Developpement des Equipements Solaires (Algeria); Haddouche, A. [Universite Badji Mokhtar (Algeria)], E-mail: rachidi3434@yahoo.fr
2011-07-01
With the depletion of fossil fuels and the increasing concerns about the environment, renewable energies have become more and more attractive. Photovoltaic systems convert solar energy into electric energy through the use of photovoltaic cells. The aim of this paper is to compare the capacity of fuzzy logic and perturb and observe controllers in optimizing the control performance of photovoltaic systems. Simulations were performed using Matlab and Simulink and were analyzed to determine the effectiveness of both controllers and compare them. Results showed that the fuzzy controller has a better dynamic performance than the perturb and observe controller in terms of response time and damping characteristics. In addition, the fuzzy controller was found to better follow the maximum power point and to provide faster convergence and lower statistical error. This study demonstrated that the fuzzy controller gives a better performance than traditional controllers in optimizing the performance of photovoltaic systems.
Directory of Open Access Journals (Sweden)
G. Sakthivel
2010-10-01
Full Text Available Fuzzy logic control has met with growing interest in many motor control applications due to its non-linearity, handling features and independence of plant modelling. The hardware implementation of fuzzy logic controller (FLC on FPGA is very important because of the increasing number of fuzzy applications requiring highly parallel and high speed fuzzy processing. Implementation of a fuzzy logic controller and conventional PI controller on an FPGA using VHDL for DC motor speed control is presented in this paper. The proposed scheme is to improve tracking performance of D.C. motor as compared to the conventional (PI control strategy .This paper describes the hardware implementation of two inputs (error and change in error, one output fuzzy logic controller based on PI controller and conventional PI controller using VHDL. Real time implementation FLC and conventional PI controller is made on Spartan-3A DSP FPGA (XC3SD1800A FPGA for the speed control of DC motor. It is observed that fuzzy logic based controllers give better responses than the conventional PI controller for the speed control of dc motor.
Directory of Open Access Journals (Sweden)
Oscar Castillo
2013-01-01
Full Text Available Ant Colony Optimization (ACO is a population-based constructive meta-heuristic that exploits a form of past performance memory inspired by the foraging behaviour of real ants. The behaviour of the ACO algorithm is highly dependent on the values defined for its parameters. Adaptation and parameter control are recurring themes in the field of bio-inspired algorithms. The present paper explores a new approach to diversity control in ACO. The central idea is to avoid or slow down full convergence through the dynamic variation of certain parameters. The performance of different variants of the ACO algorithm was observed to choose one as the basis for the proposed approach. A convergence fuzzy logic controller with the objective of maintaining diversity at some level to avoid premature convergence was created. Encouraging results have been obtained on its application to the design of fuzzy controllers. In particular, the optimization of membership functions for a unicycle mobile robot trajectory control is presented with the proposed method.
Control of convergence in a computational fluid dynamic simulation using fuzzy logic
Institute of Scientific and Technical Information of China (English)
刘训良; 陶文铨; 郑平; 何雅玲; 王秋旺
2002-01-01
A fuzzy control method was used to accelerate iteration convergence in numerical fluid dynamic simulation using SIMPLER algorithm. The residual ratio of momentum or energy equation between two successive iterations was used as the input variable. A fuzzy logic algorithm was developed in order to obtain the relative increment of the under-relaxation factor and its new value was then used for the next iteration. The algorithm was tested by four benchmark problems. In all cases considered, when the fuzzy control logic was used, convergence was achieved with nearly the minimum number of iterations, showing the feasibility of the proposed method.
Malhas, Othman Qasim
1993-10-01
The concept of “abacus logic” has recently been developed by the author (Malhas, n.d.). In this paper the relation of abacus logic to the concept of fuzziness is explored. It is shown that if a certain “regularity” condition is met, concepts from fuzzy set theory arise naturally within abacus logics. In particular it is shown that every abacus logic then has a “pre-Zadeh orthocomplementation”. It is also shown that it is then possible to associate a fuzzy set with every proposition of abacus logic and that the collection of all such sets satisfies natural conditions expected in systems of fuzzy logic. Finally, the relevance to quantum mechanics is discussed.
speed control of dc motor on load using fuzzy logic controller
African Journals Online (AJOL)
HP
This paper presents the development of a fuzzy logic controller for the driver DC motor in the lube oil ..... The system has a rapid and smooth response to step input ... Tm(s). TL(s) w(s) theta. 60/(2*pi) rad/s-rpm. 0 Td. 1. J.s+b. Motor-Pump. Load.
Adaptive Fuzzy Logic Control of Wind Turbine Emulator
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BOUZID Mohamed Amine
2014-03-01
Full Text Available In this paper, a Wind Turbine Emulator (WTE based on a separately excited direct current (DC motor is studied. The wind turbine was emulated by controlling the torque of the DC motor. The WTE is used as a prime mover for Permanent Magnet Synchronous Machine (PMSM. In order to extract maximum power from the wind, PI and Fuzzy controllers were tested. Simulation results are given to show performance of proposed fuzzy control system in maximum power points tracking in a wind energy conversion system under various wind conditions. The strategy control was implemented in simulation using MATLAB/Simulink.
A FUZZY-LOGIC CONTROL ALGORITHM FOR ACTIVE QUEUE MANAGEMENT IN IP NETWORKS
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the predominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theoretical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.
Maximum Power Point Tracking Using Adaptive Fuzzy Logic control for Photovoltaic System
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Anass Ait Laachir
2015-01-01
Full Text Available This work presents an intelligent approach to the improvement and optimization of control performance of a photovoltaic system with maximum power point tracking based on fuzzy logic control. This control was compared with the conventional control based on Perturb &Observe algorithm. The results obtained in Matlab/Simulink under different conditions show a marked improvement in the performance of fuzzy control MPPT of the PV system.
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Hadi Sefidgar
2014-06-01
Full Text Available in this paper, a fuzzy logic control (FLC is proposed for maximum power point tracking (MPPT in wind turbine connection to Permanent Magnet Synchronous Generator (PMSG. The proposed fuzzy logic controller tracks the maximum power point (MPP by measurements the load voltage and current. This controller calculates the load power and sent through the fuzzy logic system. The main goal of this paper is design of the fuzzy logic controller in the model of DC-DC converter (boost converter. This method allows the MPPT controller output (duty cycle adjusts the voltage input to the converter to track the maximum power point of the wind generator.
Fuzzy logic control strategy for submerged arc automatic welding of digital controlling
Institute of Scientific and Technical Information of China (English)
He Kuanfang; Huang Shisheng; Zhou Yiqing; Wang Zhenmin
2008-01-01
A microcomputer control system based on 80C320 and a switching regulation of wire feeder were designed. A correction factor based double model fuzzy logic controller (FLC) was introduced to achieve welding digital and intellectualized control by means of wire feeding speed feedback. The controller has many functions such as keyboard input, light emitting diode (LED) display and real-time intellectualized control of welding process etc. The controlling performance influenced by the coefficient of correction function was discussed. It was concluded by the experiments the relation between the coefftcient of correction function and welding quality, when the coefficient of correction function is great, the dynamic character of controller is better, when the coefficient of correction function is small, the sensitivity character of controller is better. Experimental results also show that digital and fuzzy logic control method enable the improvement of appearance of weld and stability of welding process to be achieved in submerged arc automatic welding.
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Nirban Chakraborty
2014-04-01
Full Text Available This paper presents the speed control scheme of direct vector control of Induction Motor drive (IM drive. The Fuzzy logic controller is (FLC used as the controller part here for the direct vector control of Induction Motor using Sinusoidal PWM Inverter (SPWM. Fuzzy logic controller has become a very popular controlling scheme in the field of Industrial application. The entire module of this IM is divided into several parts such as IM body module, Inverter module, coordinate transformation module and Sinusoidal pulse width modulation (SPWM production module and so on. With the help of this module we can analyze a variety of different simulation waveforms, which provide an effective means for the analysis and design of the IM control system using FLC technique.
Dialectic operator fuzzy logic
Institute of Scientific and Technical Information of China (English)
程晓春; 姜云飞; 刘叙华
1996-01-01
Dialectic operator fuzzy logic (DOFL) is presented which is relevant,paraconsistent and nonmonotonic.DOFL can vividly describe the belief revision in the cognitive process and can infer reasonably well while the knowledge is inconsistent,imprecise or incomplete.
A minimum-time based fuzzy logic dynamic braking resistor control for sub-synchronous resonance
Energy Technology Data Exchange (ETDEWEB)
Rahim, A.H.M.A. [University of Petroleum and Minerals, Dhahran (Saudi Arabia). Dept. of Electrical Engineering
2004-03-01
Dynamically switched resistor banks connected to the generator transformer bus are known to improve transient stability of the power system. In this article, a braking resistor control strategy designed through fuzzy logic control theory has been proposed to damp the slowly growing sub-synchronous resonant (SSR) frequency oscillations of a power system. The proposed control has been tested on the IEEE second benchmark model for SSR studies. A fuzzy logic controller designed through a classical minimum-time strategy was compared with a general fuzzy strategy employing generator speed variation and acceleration as input to the controller. It was observed that the proposed minimum-time based fuzzy controller provides better damping control; and it is computationally very efficient. (author)
Power and Frequency Control of Induction Furnace Using Fuzzy Logic Controller
Sinafar, Behzad; Ghiasi, Amir Rikhtegar
2015-01-01
This paper introduces a new method to control resonance frequency and output power of induction heating coil. Induction heating coil can be controlled by single phase sinusoidal pulse width modulation (SPWM) inverter .All electrical requirements beside magnetic permeability and resistivity variation for modeling induction heating coil have been considered to make simulations practical .Control blocks using Fuzzy logic which control both active and reactive power have been designed .The system...
Design and Implementation of Takagi-Sugeno Fuzzy Logic Controller for Shunt Compensator
Singh, Alka; Badoni, Manoj
2016-12-01
This paper describes the application of Takagi-Sugeno (TS) type fuzzy logic controller to a three-phase shunt compensator in power distribution system. The shunt compensator is used for power quality improvement and has the ability to provide reactive power compensation, reduce the level of harmonics in supply currents, power factor correction and load balancing. Additionally, it can also be used to regulate voltage at the point of common coupling (PCC). The paper discusses the design of TS fuzzy logic controller and its implementation based on only four rules. The smaller number of rules makes it suitable for experimental verification as compared to Mamdani fuzzy controller. A small laboratory prototype of the system is developed and the control algorithm is verified experimentally. The TS fuzzy controller is compared with the proportional integral based industrial controller and their performance is compared under a wide variation of dynamic load changes.
Institute of Scientific and Technical Information of China (English)
Hongsheng QI; Daizhan CHENG
2008-01-01
This paper gives a matrix expression of logic. Under the matrix expression, a general description of the logical operators is proposed. Using the semi-tensor product of matrices, the proofs of logical equivalences, implications, etc., can be simplified a lot. Certain general properties are revealed. Then, based on matrix expression, the logical operators are extended to multi-valued logic, which provides a foundation for fuzzy logical inference. Finally, we propose a new type of logic, called mix-valued logic, and a new design technique, called logic-based fuzzy control. They provide a numerically computable framework for the application of fuzzy logic for the control of fuzzy systems.
Design of adaptive fuzzy logic controller based on linguistic-hedge concepts and genetic algorithms.
Liu, B D; Chen, C Y; Tsao, J Y
2001-01-01
In this paper, we propose a novel fuzzy logic controller, called linguistic hedge fuzzy logic controller, to simplify the membership function constructions and the rule developments. The design methodology of linguistic hedge fuzzy logic controller is a hybrid model based on the concepts of the linguistic hedges and the genetic algorithms. The linguistic hedge operators are used to adjust the shape of the system membership functions dynamically, and ran speed up the control result to fit the system demand. The genetic algorithms are adopted to search the optimal linguistic hedge combination in the linguistic hedge module, According to the proposed methodology, the linguistic hedge fuzzy logic controller has the following advantages: 1) it needs only the simple-shape membership functions rather than the carefully designed ones for characterizing the related variables; 2) it is sufficient to adopt a fewer number of rules for inference; 3) the rules are developed intuitionally without heavily depending on the endeavor of experts; 4) the linguistic hedge module associated with the genetic algorithm enables it to be adaptive; 5) it performs better than the conventional fuzzy logic controllers do; and 6) it can be realized with low design complexity and small hardware overhead. Furthermore, the proposed approach has been applied to design three well-known nonlinear systems. The simulation and experimental results demonstrate the effectiveness of this design.
An adaptive fuzzy logic controller for robot-manipulator
Directory of Open Access Journals (Sweden)
Tran Thu Ha
2008-11-01
Full Text Available In this paper, an adaptive fuzzy controller is designed for the robot-manipulator. The synthesized controller ensures that 1 the close-loop system is globally stable and 2 the tracking error converges to zero asymptotically and a cost function is minimized. The fuzzy controller is synthesized from a collection of IF-THEN rules. The parameters of the membership functions characterizing the linguistic terms change according to some adaptive law for the purpose of controlling a plant to track a reference trajectory. The proposed control scheme is demonstrated in a typical nonlinear plant two link manipulator. The computer simulation of control is done by the language MATLAB. The results of simulation show that the adaptipresented results are analyzed.
Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms
Siddique, Nazmul
2014-01-01
Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller. The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of t...
Directory of Open Access Journals (Sweden)
Jagdish Prasad Sharma
2016-01-01
Full Text Available In the restructured environment, distributed generation (DG is considered as a very promising option due to a high initial capital cost of conventional plants, environmental concerns, and power shortage. Apart from the above, distributed generation (DG has also abilities to improve performance of feeder. Most of the distribution feeders have radial structure, which compel to observe the impact of distributed generations on feeder performance, having different characteristics and composition of time varying static ZIP load models. Two fuzzy-based expert system is proposed for selecting and ranking the most appropriated periods to an integration of distributed generations with a feeder. Madami type fuzzy logic controller was developed for sizing of distributed generation, whereas Sugeno type fuzzy logic controller was developed for the DG location. Input parameters for Madami fuzzy logic controller are substation reserve capacity, feeder power loss to load ratio, voltage unbalance, and apparent power imbalances. DG output, survivability index, and node distance from substation are chosen as input to Sugeno type fuzzy logic controller. The stochastic performance of proposed fuzzy expert systems was evaluated on a modified IEEE 37 node test feeder with 15 minutes characteristics time interval varying static ZIP load models.
Yan, Gang; Zhou, Lily L.
2006-09-01
This study presents a design strategy based on genetic algorithms (GA) for semi-active fuzzy control of structures that have magnetorheological (MR) dampers installed to prevent damage from severe dynamic loads such as earthquakes. The control objective is to minimize both the maximum displacement and acceleration responses of the structure. Interactive relationships between structural responses and input voltages of MR dampers are established by using a fuzzy controller. GA is employed as an adaptive method for design of the fuzzy controller, which is here known as a genetic adaptive fuzzy (GAF) controller. The multi-objectives are first converted to a fitness function that is used in standard genetic operations, i.e. selection, crossover, and mutation. The proposed approach generates an effective and reliable fuzzy logic control system by powerful searching and self-learning adaptive capabilities of GA. Numerical simulations for single and multiple damper cases are given to show the effectiveness and efficiency of the proposed intelligent control strategy.
Mathematics of Fuzzy Sets and Fuzzy Logic
Bede, Barnabas
2013-01-01
This book presents a mathematically-based introduction into the fascinating topic of Fuzzy Sets and Fuzzy Logic and might be used as textbook at both undergraduate and graduate levels and also as reference guide for mathematician, scientists or engineers who would like to get an insight into Fuzzy Logic. Fuzzy Sets have been introduced by Lotfi Zadeh in 1965 and since then, they have been used in many applications. As a consequence, there is a vast literature on the practical applications of fuzzy sets, while theory has a more modest coverage. The main purpose of the present book is to reduce this gap by providing a theoretical introduction into Fuzzy Sets based on Mathematical Analysis and Approximation Theory. Well-known applications, as for example fuzzy control, are also discussed in this book and placed on new ground, a theoretical foundation. Moreover, a few advanced chapters and several new results are included. These comprise, among others, a new systematic and constructive approach for fuzzy infer...
Analyses and Simulation of Fuzzy Logic Control for Suspension System of a Track Vehicle
Institute of Scientific and Technical Information of China (English)
YU Yang; WEI Xue-xia; ZHANG Yong-fa
2008-01-01
The vibration caused by terrible road excitation affects the ride quality and safety of track vehicles. The vibration control of suspension systems is a very important factor for modern track vehicles. A fuzzy logic control for suspension system of a track vehicle is presented. A mechanical model and a system of differential equations of motion taking account of the mass of loading wheel are established. Then the fuzzy logic control is applied to control the vibration of suspension system of track vehicles for sine signal and random road surfaces. Numerical simulation shows that the maximum acceleration of suspension system can be reduced to 44% of the original value for sine signal road surface, and the mean square root of acceleration of suspension system can be reduced to 21% for random road surface. Therefore, the proposed fuzzy logic control is an efficient method for the suspension systems of track vehicles.
Fuzzy logic switching of thyristor controlled braking resistor considering coordination with SVC
Energy Technology Data Exchange (ETDEWEB)
Hiyama, T.; Mishiro, M.; Kihara, H. [Kumamoto Univ. (Japan). Dept. of Electrical Engineering and Computer Science; Ortmeyer, T.H. [Clarkson Univ., Potsdam, NY (United States). Dept. of Electrical and Computer Engineering
1995-10-01
This paper presents a new switching control scheme for braking resistors using a fuzzy logic to enhance overall stability of electric power systems. In addition, the coordination with an SVC is also considered to achieve a wider stable region. The braking resistor is set on one of the generator busbars, where the real power output from the generator is measured to determine the firing-angle of the thyristor switch. The switching control scheme is simple so as not to require heavy computation on the micro-computer based switching controller. An SVC is set on one of the busbars in the transmission system. The switching of the SVC is performed by using a similar fuzzy logic control scheme to the one for the BR. Simulation results show the effectiveness of the proposed fuzzy logic switching control scheme.
A genetic algorithms approach for altering the membership functions in fuzzy logic controllers
Shehadeh, Hana; Lea, Robert N.
1992-01-01
Through previous work, a fuzzy control system was developed to perform translational and rotational control of a space vehicle. This problem was then re-examined to determine the effectiveness of genetic algorithms on fine tuning the controller. This paper explains the problems associated with the design of this fuzzy controller and offers a technique for tuning fuzzy logic controllers. A fuzzy logic controller is a rule-based system that uses fuzzy linguistic variables to model human rule-of-thumb approaches to control actions within a given system. This 'fuzzy expert system' features rules that direct the decision process and membership functions that convert the linguistic variables into the precise numeric values used for system control. Defining the fuzzy membership functions is the most time consuming aspect of the controller design. One single change in the membership functions could significantly alter the performance of the controller. This membership function definition can be accomplished by using a trial and error technique to alter the membership functions creating a highly tuned controller. This approach can be time consuming and requires a great deal of knowledge from human experts. In order to shorten development time, an iterative procedure for altering the membership functions to create a tuned set that used a minimal amount of fuel for velocity vector approach and station-keep maneuvers was developed. Genetic algorithms, search techniques used for optimization, were utilized to solve this problem.
A PI-fuzzy logic controller for the regulation of blood glucose level in diabetic patients.
Ibbini, M
2006-01-01
This manuscript investigates different fuzzy logic controllers for the regulation of blood glucose level in diabetic patients. While fuzzy logic control is still intuitive and at a very early stage, it has already been implemented in many industrial plants and reported results are very promising. A fuzzy logic control (FLC) scheme was recently proposed for maintaining blood glucose level in diabetics within acceptable limits, and was shown to be more effective with better transient characteristics than conventional techniques. In fact, FLC is based on human expertise and on desired output characteristics, and hence does not require precise mathematical models. This observation makes fuzzy rule-based technique very suitable for biomedical systems where models are, in general, either very complicated or over-simplistic. Another attractive feature of fuzzy techniques is their insensitivity to system parameter variations, as numerical values of physiological parameters are often not precise and usually vary from patient to another. PI and PID controllers are very popular and are efficiently used in many industrial plants. Fuzzy PI and PID controllers behave in a similar fashion to those classical controllers with the obvious advantage that the controller parameters are time dependant on the range of the control variables and consequently, result in a better performance. In this manuscript, a fuzzy PI controller is designed using a simplified design scheme and then subjected to simulations of the two common diabetes disturbances--sudden glucose meal and system parameter variations. The performance of the proposed fuzzy PI controller is compared to that of the conventional PID and optimal techniques and is shown to be superior. Moreover, the proposed fuzzy PI controller is shown to be more effective than the previously proposed FLC, especially with respect to the overshoot and settling time.
Fuzzy logic and genetic algorithms for intelligent control of structures using MR dampers
Yan, Gang; Zhou, Lily L.
2004-07-01
Fuzzy logic control (FLC) and genetic algorithms (GA) are integrated into a new approach for the semi-active control of structures installed with MR dampers against severe dynamic loadings such as earthquakes. The interactive relationship between the structural response and the input voltage of MR dampers is established by using a fuzzy controller rather than the traditional way by introducing an ideal active control force. GA is employed as an adaptive method for optimization of parameters and for selection of fuzzy rules of the fuzzy control system, respectively. The maximum structural displacement is selected and used as the objective function to be minimized. The objective function is then converted to a fitness function to form the basis of genetic operations, i.e. selection, crossover, and mutation. The proposed integrated architecture is expected to generate an effective and reliable fuzzy control system by GA"s powerful searching and self-learning adaptive capability.
Energy Technology Data Exchange (ETDEWEB)
Costa, Herbert R. do N.
1998-02-01
This work shows a study on the using of fuzzy control algorithms for the energy optimization of a standard building. The simulation of this type of control was performed using a central conditioned air model and the fuzzy control architecture already used in various control projects. This situation allowed a comparative study among the the control algorithms normally used in conditioned air installations, and the control performed through the building automation system, using an algorithm based on fuzzy logic.
Genetic Fuzzy Logic Control Technique for a Mobile Robot Tracking a Moving Target
Directory of Open Access Journals (Sweden)
Karim Benbouabdallah
2013-01-01
Full Text Available Target tracking is a crucial function for an autonomous mobile robot navigating in unknown environments. This paper presents a mobile robot target tracking approach based on artificial intelligence techniques. The proposed controller calculates both the mobile robot linear and angular velocities from the distance and angle that separate it to the moving target. The controller was designed using fuzzy logics theory and then, a genetic algorithm was applied to optimize the scaling factors of the fuzzy logic controller for better accuracy and smoothness of the robot trajectory. Simulation results illustrate that the proposed controller leads to good performances in terms of computational time and tracking errors convergence.
Marwan Rosyadi; Muyeen, S. M.; Rion Takahashi; Junji Tamura
2012-01-01
In this paper, a design fuzzy logic controller for a variable speed permanent magnet wind generator connected to a grid system through a LC-filter is proposed. A new current control method of grid side conversion is developed by integrating the fuzzy controller, in which both active and reactive power, delivered to a power grid system, is controlled effectively. The fuzzy logic controller is designed to adjust the gain parameters of the PI controllers under any operating conditions, so that t...
CONTROLLING MECHANICAL VENTILATION IN ARDS WITH FUZZY LOGIC
Nguyen, Binh; Bernstein, David B.; Bates, Jason H.T.
2014-01-01
Purpose The current ventilatory care goal for acute respiratory distress syndrome (ARDS), and the only evidence-based approach for managing ARDS, is to ventilate with a tidal volume (VT) of 6 ml/kg predicted body weight (PBW). However, it is not uncommon for some caregivers to feel inclined to deviate from this strategy for one reason or another. To accommodate this inclination in a rationalized manner, we previously developed an algorithm that allows for VT to depart from 6 ml/kg PBW based on physiological criteria. The goal of the present study was to test the feasibility of this algorithm in a small retrospective study. Materials and Methods Current values of peak airway pressure (PAP), positive end-expiratory pressure (PEEP) and arterial oxygen saturation (SaO2) are used in a fuzzy logic algorithm to decide how much VT should differ from 6 ml/kg PBW and how much PEEP should change from its current setting. We retrospectively tested the predictions of the algorithm against 26 cases of decision making in 17 patients with ARDS. Results Differences between algorithm and physician VT decisions were within 2.5 ml/kg PBW except in 1 of 26 cases, and differences between PEEP decisions were within 2.5 cm H2O except in 3 of 26 cases. The algorithm was consistently more conservative than physicians in changing VT, but was slightly less conservative when changing PEEP. Conclusions Within the limits imposed by a small retrospective study, we conclude that our fuzzy logic algorithm makes sensible decisions while at the same time keeping practice close to the current ventilatory care goal. PMID:24721387
DEVELOPMENT OF THE CROSS-COUPLING PHENOMENA OF MIMO FLIGHT SYSTEM USING FUZZY LOGIC CONTROLLER
Directory of Open Access Journals (Sweden)
MUNA H. SALEH
2010-03-01
Full Text Available This paper describes the performance of a simplified dynamic controller with fuzzy logic controllers. The six degree-of-freedom simulation study focuses on the results with and without fuzzy logic controller. One area of interest is the performance of a simulated the cross coupling effect. The controller uses explicit models to produce the desired commands. In this paper the effect of the cross-coupling between channels on the overall performance of the flight system has been considered. Two fuzzy controllers have been added to the system to improve its performance. This paper presents the development and simulation of a modified system is presented using MatLab Simulink. Also it focuses on the use of fuzzy logic controller in model-based control of multiple-input, multiple-output systems. Here, we address the question of how the overall performance of the system is affected when both fuzzy logic controllers are applied at the same time. Simulation and experimental results of a flight system , as an illustrative example, are presented.
Directory of Open Access Journals (Sweden)
ThetKoKo
2015-07-01
Full Text Available Abstract This research paper describes the design and simulation of the automatic wiper speed and headlight modes controllers using fuzzy logic. This proposed system consists of a fuzzy logic controller to control a cars wiper speed and headlight modes. The automatic wiper system detects the rain and its intensity. And according to the rain intensity the wiper speed is automatically controlled. Headlight modes automatically changes either from low beam mode to high beam mode or form high beam mode to low beam mode depending on the light intensity from the other vehicle coming from the opposite direction. The system comprises of PIC impedance sensor piezoelectric vibration sensor LDR headlamps and a DC motor to accurate the windshield wiper. Piezoelectric sensor is used to detect the rain intensity which is based on the piezoelectric effect. MATLAB software is used to achieve the designed goal.
T Atanassov, Krassimir
2017-01-01
The book offers a comprehensive survey of intuitionistic fuzzy logics. By reporting on both the author’s research and others’ findings, it provides readers with a complete overview of the field and highlights key issues and open problems, thus suggesting new research directions. Starting with an introduction to the basic elements of intuitionistic fuzzy propositional calculus, it then provides a guide to the use of intuitionistic fuzzy operators and quantifiers, and lastly presents state-of-the-art applications of intuitionistic fuzzy sets. The book is a valuable reference resource for graduate students and researchers alike.
Energy Technology Data Exchange (ETDEWEB)
Larbes, C.; Ait Cheikh, S.M.; Obeidi, T.; Zerguerras, A. [Laboratoire des Dispositifs de Communication et de Conversion Photovoltaique, Departement d' Electronique, Ecole Nationale Polytechnique, 10, Avenue Hassen Badi, El Harrach, Alger 16200 (Algeria)
2009-10-15
This paper presents an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and irradiance conditions. First, for the purpose of comparison and because of its proven and good performances, the perturbation and observation (P and O) technique is briefly introduced. A fuzzy logic controller based MPPT (FLC) is then proposed which has shown better performances compared to the P and O MPPT based approach. The proposed FLC has been also improved using genetic algorithms (GA) for optimisation. Different development stages are presented and the optimized fuzzy logic MPPT controller (OFLC) is then simulated and evaluated, which has shown better performances. (author)
Saini, J. S.; Jain, V.
2015-03-01
This paper presents a genetic algorithm (GA)-based design and optimization of fuzzy logic controller (FLC) for automatic generation control (AGC) for a single area. FLCs are characterized by a set of parameters, which are optimized using GA to improve their performance. The design of input and output membership functions (mfs) of an FLC is carried out by automatically tuning (off-line) the parameters of the membership functions. Tuning is based on maximization of a comprehensive fitness function constructed as inverse of a weighted average of three performance indices, i.e., integral square deviation (ISD), the integral of square of the frequency deviation and peak overshoot (Mp), and settling time (ts). The GA-optimized FLC (GAFLC) shows better performance as compared to a conventional proportional integral (PI) and a hand-designed fuzzy logic controller not only for a standard system (displaying frequency deviations) but also under parametric and load disturbances.
Directory of Open Access Journals (Sweden)
Angelo A. Beltran Jr.
2014-03-01
Full Text Available —The control and operation of electronic systems relies and depends on the availability of the power supply. Rechargeable batteries have been more pervasively used as the energy storage and power source for various electrical and electronic systems and devices, such as communication systems, electronic devices, renewable power systems, electric vehicles, etc. However, the rechargeable batteries are subjected to the availability of the external power source when it is drained out. Because of the concern of battery life, environmental pollution and a possible energy crisis, the renewable solar energy has received an increasing attention in recent years. A fuzzy logic control based grid tied uninterruptible power supply integrating renewable solar energy can be used for electrical and electronic systems to produce power generation. This paper presents the design and implementation of fuzzy logic control based grid tied uninterruptible power supply integrating the renewable solar power energy system. The uninterruptible power supply (UPS system is characterized by the rechargeable battery that is connected with the Photovoltaic Panel through the DC/DC converter, the utility AC through the AC/DC converter and the load is connected through the DC/AC converter. The whole operation is controlled by the fuzzy logic algorithm. A complete hardware prototype system model of the fuzzy logic control based on the grid tied uninterruptible power supply integrating with the renewable solar energy is designed and implemented. The operation and effectiveness of the proposed system is then demonstrated by the actual and real time implementation of the fuzzy logic control grid tied operation uninterruptible power supply integrating renewable solar energy connected to the rechargeable battery bank and a PIC microcontroller platform for fuzzy logic control and operation
Type-2 Fuzzy Logic Controller of a Doubly Fed Induction Machine
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Keltoum Loukal
2016-01-01
Full Text Available Interval type-2 fuzzy logic controller (IT2FLC method for controlling the speed with a direct stator flux orientation control of doubly fed induction motor (DFIM is proposed. The fuzzy controllers have demonstrated their effectiveness in the control of nonlinear systems, and in many cases it is proved that their robustness and performance are less sensitive to parameters variation over conventional controllers. The synthesis of stabilizing control laws design based on IT2FLC is developed. A comparative analysis between type-1 fuzzy logic controller (T1FLC and IT2FLC of the DFIM is shown. Simulation results show the feasibility and the effectiveness of the suggested method to the control of the DFIM under different operating conditions such as load torque and in the presence of parameters variation.
Q-V droop control using fuzzy logic and reciprocal characteristic
DEFF Research Database (Denmark)
Wanga, Lu; Hu, Yanting; Chen, Zhe
2014-01-01
electric power at distributed voltage level, which not only is an autonomous system, but also can be connected to the main grid. To improve the stability and controllability of the power grid, this paper presents an improved Q-V droop control strategy using fuzzy logic controller and reciprocal...
Realworld maximum power point tracking simulation of PV system based on Fuzzy Logic control
Othman, Ahmed M.; El-arini, Mahdi M. M.; Ghitas, Ahmed; Fathy, Ahmed
2012-12-01
In the recent years, the solar energy becomes one of the most important alternative sources of electric energy, so it is important to improve the efficiency and reliability of the photovoltaic (PV) systems. Maximum power point tracking (MPPT) plays an important role in photovoltaic power systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize their array efficiency. This paper presents a maximum power point tracker (MPPT) using Fuzzy Logic theory for a PV system. The work is focused on the well known Perturb and Observe (P&O) algorithm and is compared to a designed fuzzy logic controller (FLC). The simulation work dealing with MPPT controller; a DC/DC Ćuk converter feeding a load is achieved. The results showed that the proposed Fuzzy Logic MPPT in the PV system is valid.
Realworld maximum power point tracking simulation of PV system based on Fuzzy Logic control
Directory of Open Access Journals (Sweden)
Ahmed M. Othman
2012-12-01
Full Text Available In the recent years, the solar energy becomes one of the most important alternative sources of electric energy, so it is important to improve the efficiency and reliability of the photovoltaic (PV systems. Maximum power point tracking (MPPT plays an important role in photovoltaic power systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize their array efficiency. This paper presents a maximum power point tracker (MPPT using Fuzzy Logic theory for a PV system. The work is focused on the well known Perturb and Observe (P&O algorithm and is compared to a designed fuzzy logic controller (FLC. The simulation work dealing with MPPT controller; a DC/DC Ćuk converter feeding a load is achieved. The results showed that the proposed Fuzzy Logic MPPT in the PV system is valid.
Fuzzy Logic Controlled Solar Module for Driving Three- Phase Induction Motor
Afiqah Zainal, Nurul; Sooi Tat, Chan; Ajisman
2016-02-01
Renewable energy produced by solar module gives advantages for generated three- phase induction motor in remote area. But, solar module's ou tput is uncertain and complex. Fuzzy logic controller is one of controllers that can handle non-linear system and maximum power of solar module. Fuzzy logic controller used for Maximum Power Point Tracking (MPPT) technique to control Pulse-Width Modulation (PWM) for switching power electronics circuit. DC-DC boost converter used to boost up photovoltaic voltage to desired output and supply voltage source inverter which controlled by three-phase PWM generated by microcontroller. IGBT switched Voltage source inverter (VSI) produced alternating current (AC) voltage from direct current (DC) source to control speed of three-phase induction motor from boost converter output. Results showed that, the output power of solar module is optimized and controlled by using fuzzy logic controller. Besides that, the three-phase induction motor can be drive and control using VSI switching by the PWM signal generated by the fuzzy logic controller. This concluded that the non-linear system can be controlled and used in driving three-phase induction motor.
ENERGY EFFICIENT FLOW AND LEVEL CONTROL IN A HYDRO POWER PLANT USING FUZZY LOGIC
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A. Selwin Mich Priyadharson
2014-01-01
Full Text Available The main objective and an innovative design of this work is to improve the energy efficiency by controlling the variables flow and level in a hydroelectric power plant using Programmable Logic Control (PLC-Human Machine Interface (HMI and fuzzy logic approach. This project will focus on design and development of flow and level controller for small scale hydro generating units by implementing gate control based on PLC-HMI and Fuzzy Logic Control (FLC. So far there is no other better performing control scheme, with uncomplicated approach, in order to match and satisfy the dynamic changes in load demand. In this project, FLC will be applied to flow and level control for small scale hydro generating units is proposed. A lab scale experimental setup is made-up as prototype model for flow and level control and simulation outputs were achieved, using PLC-HMI based fuzzy controller scheme. The hardware set up is designed with 5 stages in the tank 1 and 2 stages in the tank 2. Based on the outputs of the level sensors from tanks 1 and 2, the ladder logic will perform. B&R Industrial Automation PLC inbuilt with 24 digital inputs and provides 16 potential free outputs is used to perform control action. Finally, the performance of the proposed scheme is evaluated by simulation results by comparing with conventional controllers output using the data collected from the hydroelectric power plant. The merits of the proposed Fuzzy scheme over the conventional method are spotlighted.
Optimized and Self-Organized Fuzzy Logic Controller for pH Neutralization Process
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Parikshit Kishor Singh
2013-11-01
Full Text Available To conform to strict environmental safety regulations, pH control is used in many industrial applications. For this purpose modern process industries are increasingly relying on intelligent and adaptive control strategies. On one hand intelligent control strategies try to imitate human way of thinking and decision making using artificial intelligence (AI based techniques such as fuzzy logic whereas on the other hand adaptive mechanism ensures adjusting of the controller parameters. A self-organized fuzzy logic controller (SOFLC is intelligent in nature and adapts its performance to meet the figure of merit. This paper presents an optimized SOFLC for pH control using performance correction table. The fuzzy adaptation mechanism basically involves a penalty for the output membership functions if the controller performance is poor. The evolutionary genetic algorithm (GA is used for optimization of input-output scaling factors of the conventional fuzzy logic controller (FLC as well as elements of the fuzzy performance correction table. The resulting optimized SOFLC is compared with optimized FLC for servo and regulatory control. Comparison indicate superior performance of SOFLC over FLC in terms of much reduced integral of squared error (ISE, maximum overshoot and undershoot, and increased speed of response.
Design and implementation of the tree-based fuzzy logic controller.
Liu, B D; Huang, C Y
1997-01-01
In this paper, a tree-based approach is proposed to design the fuzzy logic controller. Based on the proposed methodology, the fuzzy logic controller has the following merits: the fuzzy control rule can be extracted automatically from the input-output data of the system and the extraction process can be done in one-pass; owing to the fuzzy tree inference structure, the search spaces of the fuzzy inference process are largely reduced; the operation of the inference process can be simplified as a one-dimensional matrix operation because of the fuzzy tree approach; and the controller has regular and modular properties, so it is easy to be implemented by hardware. Furthermore, the proposed fuzzy tree approach has been applied to design the color reproduction system for verifying the proposed methodology. The color reproduction system is mainly used to obtain a color image through the printer that is identical to the original one. In addition to the software simulation, an FPGA is used to implement the prototype hardware system for real-time application. Experimental results show that the effect of color correction is quite good and that the prototype hardware system can operate correctly under the condition of 30 MHz clock rate.
Institute of Scientific and Technical Information of China (English)
HuangMiao-hua; JinGuo-dong
2003-01-01
The Hierarchical Structure Fuzzy Logic Control(HSFLC) strategies of torque distribute for Parallel Hybrid Electric Vehicle (PHEV) in the mocle of operation of the vehicle i. e. , acceleration, cruise, deceleration etc. have been studied. Using secondly developed the hybrid vehicle simulation tool ADVISOR, the dynamic model of PHEV has been set up by MATLAB/SIMULINK. The engine, motor as well as the battery characteristics have been studied. Simulation results show that the proposed hierarchical structured fuzzy logic control strategy is effective over the entire operating range of the vehicle in terms of fuel economy. Based on the analyses of the simulation results and driver's experiences, a fuzzy controller is designed and developed to control the torque distribution. The controller is evaluated via hardware-in-the-loop simulator (HILS). The results show that controller verify its value.
Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control
Itik, Mehmet; Sabetghadam, Mohammadreza; Alici, Gursel
2014-12-01
Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which the magnitude of the force applied to the target is of crucial importance, the force generated by CPAs needs to be accurately controlled. In this paper, a fuzzy logic (FL) controller with a Mamdani inference system is designed to control the blocking force of a trilayer CPA with polypyrrole electrodes, which operates in air. The particle swarm optimization (PSO) method is employed to optimize the controller’s membership function parameters and therefore enhance the performance of the FL controller. An adaptive neuro-fuzzy inference system model, which can capture the nonlinear dynamics of the actuator, is utilized in the optimization process. The optimized Mamdani FL controller is then implemented on the CPA experimentally, and its performance is compared with a non-optimized fuzzy controller as well as with those obtained from a conventional PID controller. The results presented indicate that the blocking force at the tip of the CPA can be effectively controlled by the optimized FL controller, which shows excellent transient and steady state characteristics but increases the control voltage compared to the non-optimized fuzzy controllers.
FUZZY LOGIC CONTROLLER AS MODELING TOOL FOR THE BURNING PROCESS OF A CEMENT PRODUCTION PLANT
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P.B. Osofisan
2012-01-01
Full Text Available
ENGLISH ABSTRACT: A comprehensive optimisation of the cement production process presents a problem since the input variables as well as the output variables are non-linear, interdependent and contain uncertainties. To arrive at a solution, a Fuzzy Logic controller has been designed to achieve a well-defined relationship between the main and vital variables through the instrumentality of a Fuzzy Model. The Fuzzy Logic controller has been simulated on a digital computer using MATLAB 5.0 Fuzzy Logic Tool Box, using data from a local cement production plant.
AFRIKAANSE OPSOMMING: Die omvattende optimisering van 'n proses wat sement vervaardig, word beskryf deur nie-linieêre inset- en uitsetveranderlikes wat onderling afhanklik is, en ook van onsekere aard is. Om 'n optimum oplossing te verkry, word 'n Wasigheidsmodel gebruik. Die model word getoets deur gebruik te maak van die MATLAB 5.0 Fuzzy Logic Tool Box en data vanaf 'n lokale sementvervaardigingsaanleg.
Design and Implementation of a Water Level Controller using Fuzzy Logic
Directory of Open Access Journals (Sweden)
Namrata Dey
2013-06-01
Full Text Available This paper analyzes the effectiveness of water level control using fuzzy logic. The water level in the tank is sensed using transistor switching principle. The level sensed is fed to the PIC16 microcontroller. The user provides the set point to the microcontroller through serial communication using the COM development port software, Terminal. It computes the error as the difference between the set point and the process variable. The fuzzy logic programmed in the microcontroller is applied which controls the water level in the tank using the drain and the feed pumps. Once the set point has been reached, the message along with the present level is sent back through serial communication to the user interface on a PC. Thus, the water level in the tank is controlled according to the set point given by the user. The implementation of a fuzzy level controller has many applications such as boiler drum level control, reverse osmosis plant, demineralisation plant etc.
Indirect Vector Control of an Induction Motor with Fuzzy-Logic based Speed Controller
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BIROU, I.
2010-02-01
Full Text Available The aim of this paper is to present a new speed control structure for induction motors (IM by using fuzzy-logic based speed controllers. A fuzzy controller is designed to achieve fast dynamic response and robustness for low and high speeds. Different types of membership functions of the linguistic variables and output/input characteristics are analyzed. A simple but robust structure enables a wide range speed control of the driving system. The rotor flux field oriented control (FOC is realized by using a flux observer based on the IM model with nonlinear parameters. The control is extended to operate also in the field weakening region with an optimal rotor flux regulation. The control structure was implemented on a computer system, based on a fixed point digital signal processor (DSP. To verify the performances of the proposed driving system, simulated and experimental results are presented.
ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
An artificial neural network(ANN) and a self-adjusting fuzzy logic controller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented. The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and the intelligent control for weld seam tracking with FLC. The proposed neural network can produce highly complex nonlinear multi-variable model of the GTAW process that offers the accurate prediction of welding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts the control parameters on-line automatically according to the tracking errors so that the torch position can be controlled accurately.
A Practical Fast Acting Control Scheme For Fuzzy Logic-Based Voltage Stabilization Control
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E. E. EL-Kholy
2005-03-01
Full Text Available This paper presents a simplified control model for stabilizing a load voltage using a switched reactor in parallel with a fixed capacitor of static VAR compensator. Two IGBT’s are used to control the reactance of the switched reactor. A uniform pulse width modulation is used for controlling the two switches. The compensator has a simple control circuit and structure. A complete modeling and numerical simulation for the proposed systems is presented. A high speed Digital Signal Processor is used for implementing proportional-integral (PI and fuzzy load voltage controllers. Experimental results indicate the superiority of fuzzy logic control over the conventional proportional-integral control method. Simulation results are reported and proved to be in good agreement with the relevant experimental results.
DSP Based Vector Control of Five-Phase Induction Using Fuzzy Logic Control
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Zakaria Mohamed Salem
2012-03-01
Full Text Available Abstract - This paper proposes an indirect field oriented controller for five-phase induction motor drives. The controller is based on fuzzy logic control technique. Simulation is carried out by using the Matlab/Simulink package. A complete control system experimentally implemented using digital signal processing (DSP board. The performance of the proposed system is investigated at different operating conditions. The proposed controller is robust and suitable to high performance five-phase induction motor drives. Simulation and experimental results validate the proposed approaches.
Zorić, Nemanja D.; Simonović, Aleksandar M.; Mitrović, Zoran S.; Stupar, Slobodan N.; Obradović, Aleksandar M.; Lukić, Nebojša S.
2014-10-01
This paper deals with active free vibrations control of smart composite beams using particle-swarm optimized self-tuning fuzzy logic controller. In order to improve the performance and robustness of the fuzzy logic controller, this paper proposes integration of self-tuning method, where scaling factors of the input variables in the fuzzy logic controller are adjusted via peak observer, with optimization of membership functions using the particle swarm optimization algorithm. The Mamdani and zero-order Takagi-Sugeno-Kang fuzzy inference methods are employed. In order to overcome stability problem, at the same time keeping advantages of the proposed self-tuning fuzzy logic controller, this controller is combined with the LQR making composite controller. Several numerical studies are provided for the cantilever composite beam for both single mode and multimodal cases. In the multimodal case, a large-scale system is decomposed into smaller subsystems in a parallel structure. In order to represent the efficiency of the proposed controller, obtained results are compared with the corresponding results in the cases of the optimized fuzzy logic controllers with constant scaling factors and linear quadratic regulator.
Control of Yaw Disturbance Using Fuzzy Logic Based Yaw Stability Controller
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S. Krishna
2014-01-01
Full Text Available Yaw stability is an important consideration for the vehicle directional stability and handling behavior during emergency maneuvers. In order to maintain the desired path of the vehicle, in presence of disturbances due to cross wind, different road conditions, and tire deflections, a fuzzy logic based yaw stability controller is proposed in this paper. Proposed control system receives yaw rate error, steering angle given by the driver, and side slip angle as inputs, for calculating the additional steering angle as output, for maintaining the yaw stability of the vehicle. As the side slip angle cannot be measured directly in a vehicle, it was estimated using a model based Kalman observer. A two-degrees-of-freedom vehicle model is considered in the present work. The effect of disturbance on yaw rate and yaw rate error of the vehicle is simulated for sinusoidal, step maneuver and compared with the existing fuzzy control system which uses two inputs such as steering angle and yaw rate. The simulation results show better performance of the proposed fuzzy based yaw controller as compared with existing control system. Proposed fuzzy based yaw stability controller can be implemented in steer-by-wire system for an active front steering of a road vehicle.
Controlling the power output of a nuclear reactor with fuzzy logic
Ruan, D.; Wal, A.J. van der
1998-01-01
The application of fuzzy logic control (FLC) in the domain of nuclear industry presents a tremendous challenge. The main reason for this is the public awareness of the risks of nuclear reactors and the very strict safety regulations in force for nuclear power plants. The very same regulations preven
Controlling the Power Output of a Nuclear Reactor with Fuzzy Logic
Ruan, D.; Wal, A.J. van der
1997-01-01
The application of fuzzy logic control (FLC) in the domain of nuclear industry presents a tremendous challenge. The main reason for this is the public awareness of the risks of nuclear reactors and the very strict safety regulations in force for nuclear power plants. The very same regulations preven
Controlling the power output of a nuclear reactor with fuzzy logic
Ruan, D.; Wal, A.J. van der
1998-01-01
The application of fuzzy logic control (FLC) in the domain of nuclear industry presents a tremendous challenge. The main reason for this is the public awareness of the risks of nuclear reactors and the very strict safety regulations in force for nuclear power plants. The very same regulations preven
FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM
The paper describes a variable-speed wind generation system where fuzzy logic principles are used to optimize efficiency and enhance performance control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which either pump...
FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM
The paper describes a variable-speed wind generation system where fuzzy logic principles are used to optimize efficiency and enhance performance control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which either pump...
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Wang, Chengshan;
2015-01-01
Microgrid is an efficient solution to integraterenewable energy sources (RES) into power systems. Inorder to deal with the intermittent characteristics of therenewable energy based distributed generation (DG) units,a fuzzy-logic based coordinated control strategy of thebattery energy storage system...
The Fuzzy Logic of MicroRNA Regulation: A Key to Control Cell Complexity.
Ripoli, Andrea; Rainaldi, Giuseppe; Rizzo, Milena; Mercatanti, Alberto; Pitto, Letizia
2010-08-01
Genomic and clinical evidence suggest a major role of microRNAs (miRNAs) in the regulatory mechanisms of gene expression, with a clear impact on development and physiology; miRNAs are a class of endogenous 22-25 nt single-stranded RNA molecules, that negatively regulate gene expression post-transcriptionally, by imperfect base pairing with the 3' UTR of the corresponding mRNA target. Because of this imperfection, each miRNA can bind multiple targets, and multiple miRNAs can bind the same mRNA target; although digital, the miRNAs control mechanism is characterized by an imprecise action, naturally understandable in the theoretical framework of fuzzy logic.A major practical application of fuzzy logic is represented by the design and the realization of efficient and robust control systems, even when the processes to be controlled show chaotic, deterministic as well unpredictable, behaviours. The vagueness of miRNA action, when considered together with the controlled and chaotic gene expression, is a hint of a cellular fuzzy control system. As a demonstration of the possibility and the effectiveness of miRNA based fuzzy mechanism, a fuzzy cognitive map -a mathematical formalism combining neural network and fuzzy logic- has been developed to study the apoptosis/proliferation control performed by the miRNA-17-92 cluster/E2F1/cMYC circuitry.When experimentally demonstrated, the concept of fuzzy control could modify the way we analyse and model gene expression, with a possible impact on the way we imagine and design therapeutic intervention based on miRNA silencing.
Abdul Kareem; Mohammad Fazle Azeem
2012-01-01
This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness ...
Fuzzy Logic Based Speed Control System for ThreePhase Induction Motor
Directory of Open Access Journals (Sweden)
Marwan A. Badran
2013-05-01
Full Text Available Three-phase induction motors have been used in a wide range of industry applications. Using modern technology, the speed of induction motor can be easily controlled by variable frequency drives (VFDs. These drives use high speed power transistors with various switching techniques, mainly PWM schemes. For several decades, conventional control systems were applied to electric drives to control the speed of induction motor. Although conventional controllers showed good results, but they still need tuning to obtain optimum results. The recent proposed control systems use fuzzy logic controller (FLC to enhance the performance of induction motor drives. In this paper, a fuzzy logic based speed control system is presented. The proposed controller has been designed with MATLAB/SIMULINK software, and it was tested for various operating conditions including load disturbance and sudden change of reference speed. The results showed better performance of the proposed controller compared with the conventional PI controller.
Comparative Study between PI and FUZZY Logic Speed Controller in Vector Controlled PMSM Drive
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Kaushik Jash
2014-04-01
Full Text Available This paper is concerned with vector control of permanent magnet synchronous motor (PMSM using two different type of speed controller, one is PI controller and another is FUZZY logic controller. Although Proportional Integral Controller usually preferred as a speed controller due to its fixed gain and integral time constant but the performance of PI controller is affected by parameter variation, such as load changing, speed variation etc. In PI controller THD of the stator phase current is more and torque ripple also more. To avoid this problem here we used FUZZY logic controller. In this paper the mathematical model of PMSM, using the powerful simulation modeling capabilities of Matlab/Simulink is implemented. The entire PMSM control system is divided into several independent functional modules such as PMSM body module, inverter module and coordinate transformation module and Sinusoidal pulse width modulation (SPWM production module and so on. Here we used two loops, one is outer loop known as speed control loop, another is inner loop called current loop. we can analyzed a variety of simulation waveforms and it provide an effective means for the analysis and design of the PMSM control system.
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S.Swathi,
2014-01-01
Full Text Available This paper deals with the electronic load controller for self exited induction generator using PID plus fuzzy logic controller. The self-excited induction generators (SEIGs are considered to be well suited for generating electricity by means of conventional energy sources and for supplying electrical energy in remote and rural areas. Induction generators have many advantages such as cost, reduced maintenance, rugged, and simple construction, brushless rotor (squirrel cage. A three phase induction generator can be operated on a delta connection for supplying single phase loads. The main disadvantage of SEIG has is that it poor voltage regulation, and its value depends on the prime mover speed, capacitance, load current and power factor of the load. The electronic load controller (ELC can be used for maintaining constant voltage and frequency of SEIG with variable consumer load driven by constant prime mover. This paper presents the simulation design and implementation of ELC using fuzzy logic method for an SEIG feeding single-phase load. The ELC consist of a rectifier, IGBT as a chopper switch, PI controller, voltage sensor, and resistive dump load in which power consumption was varied through the duty cycle of the chopper. However an ELC consist of electronics system, in general, has complex nonlinear model with parameter variation problem, and the control need to be very fast. The fuzzy logic based controller gives nonlinear control with fast response and virtually no overshoot. The simulation of ELC for self exited induction generator is carried out on MATLAB/SIMULINK. By this proposed ELC using FLC for SEIG we can maintain the constant voltage and frequency of SEIG with variable consumer load.
Fuzzy Logic Velocity Control of a Biped Robot Locomotion and Simulation
Directory of Open Access Journals (Sweden)
Arif Ankarali
2012-10-01
Full Text Available In this paper, fuzzy logic velocity control of a biped robot to generate gait is studied. The system considered in this study has six degrees of freedom with hip, knee and ankle joints. The joint angular positions are determined utilizing the Cartesian coordinate information of the joints obtained by using camera captured data of the motion. The first derivatives of the calculated joint angular positions are applied as the reference angular velocity input to the fuzzy controllers of the joint servomotors to generate a gait motion. The assumed motion for the biped robot is horizontal walking on a flat surface. The actuated joints are hip, knee and ankle joints which are driven by DC servomotors. The calculated angular velocities of the joints from camera captured motion data are utilized to get the driving velocity functions of the model as sine functions. These functions are applied to the fuzzy controller as the reference angular velocity inputs. The control signals produced by the fuzzy controllers are applied to the servomotors and then the response of the servomotor block is introduced as an input to the SimMechanics model of the biped robot. The simulation results are provided which evaluate the effectiveness of the fuzzy logic controller on joint velocities to generate gait motion.
Directory of Open Access Journals (Sweden)
C. Subba Rami Reddy
2011-07-01
Full Text Available This paper introduces an Integrated fuzzy logic controller (IFLC for brushless dc (BLDC motor drives using advanced simulation model and presents a comparative study of performances of PID controller and IFLC. The dynamic characteristics of speed and torque are effectively monitored and analyzed using the proposed model. The aim of IFLC is to obtain improved performance in terms of disturbance rejection or parameter variation than obtained using PID controller. The IFLC is constructed by using Fuzzy logic controller (FLC and PID controller. A performance comparison of the controllers is also given based on the integral of the absolute value of the error (IAE, the integral of the squared error (ISE, the integral of the time-weighted absolute error (ITAE and the integral of the time-weighted squared error (ITSE. The results show the effectiveness of the proposed controller.
Directory of Open Access Journals (Sweden)
Yuanjiang Huang
2014-01-01
Full Text Available The sensor nodes in the Wireless Sensor Networks (WSNs are prone to failures due to many reasons, for example, running out of battery or harsh environment deployment; therefore, the WSNs are expected to be able to maintain network connectivity and tolerate certain amount of node failures. By applying fuzzy-logic approach to control the network topology, this paper aims at improving the network connectivity and fault-tolerant capability in response to node failures, while taking into account that the control approach has to be localized and energy efficient. Two fuzzy controllers are proposed in this paper: one is Learning-based Fuzzy-logic Topology Control (LFTC, of which the fuzzy controller is learnt from a training data set; another one is Rules-based Fuzzy-logic Topology Control (RFTC, of which the fuzzy controller is obtained through designing if-then rules and membership functions. Both LFTC and RFTC do not rely on location information, and they are localized. Comparing them with other three representative algorithms (LTRT, List-based, and NONE through extensive simulations, our two proposed fuzzy controllers have been proved to be very energy efficient to achieve desired node degree and improve the network connectivity when sensor nodes run out of battery or are subject to random attacks.
Institute of Scientific and Technical Information of China (English)
Wu Kaiyuan; Huang Shisheng; Meng Yongmin
2005-01-01
According to the feature of arc voltage control in welding steel using pulsed MIG welding, a correction factor based double model fuzzy logic controller (FLC) was developed to realize the arc voltage control by means of arc voltage feedback.When the error of peak arc voltage was great, a coarse adjusting fuzzy logic control rules with correction factor was designed,in the controller, the peak arc voltage was controlled by the wire feeding speed by means of arc voltage feedback. When the error of peak arc voltage was small, a fine adjusting fuzzy logic control rules with correction factor was designed, in this controller, the peak arc voltage was controlled by the background time by means of arc voltage feedback. The FLC was realized in a Look-Up Table ( LUT) method. Experiments had been carried out aiming at implementing the control strategy to control the arc length change in welding process. Experimental results show that the controller proposed enables the consistency of arc length and the stabolity of arc voltage and welding process to be achieved in pulsed MIG welding process.
Directory of Open Access Journals (Sweden)
Fatih Korkmaz
2013-11-01
Full Text Available The induction motors are indispensable motor types for industrial applications due to its wellknown advantages. Therefore, many kind of control scheme are proposed for induction motors over the past years and direct torque control has gained great importance inside of them due to fast dynamic torque response behavior and simple control structure. This paper suggests a new approach on the direct torque controlled induction motors, Fuzzy logic based space vector modulation, to overcome disadvantages of conventional direct torque control like high torque ripple. In the proposed approach, optimum switching states are calculated by fuzzy logic controller and applied by space vector pulse width modulator to voltage source inverter. In order to test and compare the proposed DTC scheme with conventional DTC scheme simulations, in Matlab/Simulink, have been carried out in different speed and load conditions. The simulation results showed that a significant improvement in the dynamic torque and speed responses when compared to the conventional DTC scheme.
Voltage Source Inverter/Converter for the Improvement of Power Quality Using Fuzzy Logic Controller
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T Jagan Mohan Rao
2014-05-01
Full Text Available In recent years, the applications of power electronics have grown tremendously. These power electronic systems offer highly nonlinear characteristics. To overcome those non linearities active power filters are preferred. This paper presents and compares the performance of two controllers namely Fuzzy Logic and Proportional Integral (PI applied to a voltage source inverter / converter which operates as an active power filter. The active power filter is operated to compensate harmonics generated by the non-linear load . This work is done to make an accurate comparison of the performance of fuzzy logic controller and classical control technique such as PI controller in compensating harmonics in the ac mains current. Fuzzy control rule design is based on the general dynamic behavior of the process. A novel control method is implemented for suppressing the harmonics. The compensation process is instantaneous, which is achieved without employing any complicated control logic. The control scheme is based on sensing line currents only; an approach different from convention ones, which are based on sensing harmonics of the nonlinear load. In the control scheme a hysteresis controller based on current control is employed to generate switching signals to the PWM converter.
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Prechanon Kumkratug
2011-01-01
Full Text Available Problem statement: Modern power system consists of the complicated network of transmission lines and carries heavy demand. Thus they cause in the stability problem. Approach: Static Synchronous Series Compensator (SSSC is a power electronic based device that has the capability of controlling the power flow through a line. The series voltage injection model of SSSC is modeled into power flow equation and thus it is used to determine its control strategy. This study applies the fuzzy logic applies the SSSC to improve stability of power system. The mathematical model and control strategy of a SSSC are presented. The SSSC is represented by variable voltage injection with associate transformer leakage control to derive control strategy of SSSC. The swing curves of the three phase faulted power system without and with a SSSC is tested and compared in various cases. Results: The swing curve of the system with SSSC based fuzzy logic control has the less amplitude during the dynamic period. Conclusion: It was found from simulation results that SSSC can improve the power system oscillation after disturbance.
SPEED CONTROL OF BRUSHLESS DC MOTOR ON RESONANT POLE INVERTER USING FUZZY LOGIC CONTROLLER
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S. Sivakotiah
2011-10-01
Full Text Available Brushless dc motor has been widely used in drive system and servo control because of its fast response ,high density ,high efficiency ,low inertia ,high reliability ,maintenance free. It is however driven by a hard switching frequency, high switching losses, high electromagnetic interference, high acoustic noise and low efficiency. The rectifier/inverter with a simple commutation circuit to provide zero voltage turn on for the switches and soft turn off for diodes. The converter is intended for high performance, medium power applications requiring bidirectional power flow .A new soft switching inverter has been developed to overcome over voltages and over current problems existing resonant link inverter .This inverter employs a single auxiliary switches. The introduces fuzzy logic based soft switching resonant pole inverter using transformer, which can generates dc link voltages notches during chopping which an minimized the drawback of soft switching, The operation principle and control scheme of the inverter are analyzed and performance of the fuzzy controller is compared with conventional PI controller .The simulation result show that the fuzzy controller is compared with the conventional PI controller.
Khaled MAMMAR; CHAKER, Abdelkader
2010-01-01
This paper presents a dynamic model of Fuel cell system for residential power generation. The models proposedinclude a fuel cell stack model, reformer model and DC/AC inverter model. More then an analytical details ofhow active and reactive power output of a proton-exchange-membrane (PEM) fuel cell system is controlled.Furthermore a fuzzy logic (FLC) controller is used to control active power of PEM fuel cell system. Thecontroller modifies the hydrogen flow feedback from the terminal load. Si...
Hasanien, Hany M.; Al-Ammar, Essam A.
2012-11-01
Doubly fed induction generator (DFIG) based wind farm is today the most widely used concept. This paper presents dynamic response enhancement of DFIG based wind farm under remote fault conditions using the fuzzy logic controller. The goal of the work is to improve the dynamic response of DFIG based wind farm during and after the clearance of fault using the proposed controller. The stability of wind farm during and after the clearance of fault is investigated. The effectiveness of the fuzzy logic controller is then compared with that of a PI controller. The validity of the controllers in restoring the wind farms normal operation after the clearance of fault is illustrated by the simulation results which are carried out using MATLAB/SIMULINK. Simulation results are analyzed under different fault conditions.
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Sona Padma
2011-01-01
Full Text Available Problem statement: FACTS devices play a major role in the efficient operation of the complex power system. FACTS devices such as STATCOM, SSSC and IPFC are in increasing usage. With energy storage systems they have a good control over the real as well as reactive power compensation and transient stability improvement. The design of controller for the SSSC with SMES system is analyzed in this study. Approach: The main variables to be controlled in the power system for efficient operation are the voltage, phase angle and impedance. A SSSC is a series connected converter based FACTS control which can provide a series reactive power compensation for a transmission system. With the addition of energy storage device, in addition to the reactive power compensation the real power exchange is also accomplished. Fuzzy logic controller is designed for the efficient operation of the power system with SSSC integrated with energy storage device. From the power reference the current reference is calculated and the error and change in error in the current are calculated in the controller. Results: A three phase to ground fault is simulated in the test system. A comparative analysis of the PI and fuzzy logic control of SSSC with energy storage system for the rotor angle oscillation damping following the disturbance is done. Conclusion: The fuzzy logic controller works efficiently compared to the conventional PI controller for the SSSC with SMES system. Also with energy storage system in the FACTS devices, the efficient operation of the power system is possible.
Borni, A.; Abdelkrim, T.; Zaghba, L.; Bouchakour, A.; Lakhdari, A.; Zarour, L.
2017-02-01
In this paper the model of a grid connected hybrid system is presented. The hybrid system includes a variable speed wind turbine controlled by aFuzzy MPPT control, and a photovoltaic generator controlled with PSO Fuzzy MPPT control to compensate the power fluctuations caused by the wind in a short and long term, the inverter currents injected to the grid is controlled by a decoupled PI current control. In the first phase, we start by modeling of the conversion system components; the wind system is consisted of a turbine coupled to a gearless permanent magnet generator (PMG), the AC/DC and DC-DC (Boost) converter are responsible to feed the electric energy produced by the PMG to the DC-link. The solar system consists of a photovoltaic generator (GPV) connected to a DC/DC boost converter controlled by a PSO fuzzy MPPT control to extract at any moment the maximum available power at the GPV terminals, the system is based on maximum utilization of both of sources because of their complementary. At the end. The active power reached to the DC-link is injected to the grid through a DC/AC inverter, this function is achieved by controlling the DC bus voltage to keep it constant and close to its reference value, The simulation studies have been performed using Matlab/Simulink. It can be concluded that a good control system performance can be achieved.
Investigation of the Flutter Suppression by Fuzzy Logic Control for Hypersonic Wing
Li, Dongxu; Luo, Qing; Xu, Rui
This paper presents a fundamental study of flutter characteristics and control performance of an aeroelastic system based on a two-dimensional double wedge wing in the hypersonic regime. Dynamic equations were established based on the modified third order nonlinear piston theory and some nonlinear structural effects are also included. A set of important parameters are observed. And then aeroelastic control law is designed to suppress the amplitude of the LCOs for the system in the sub/supercritical speed range by applying fuzzy logic control on the input of the deflection of the flap. The overall effects of the parameters on the aeroelastic system were outlined. Nonlinear aeroelastic responses in the open- and closed-loop system are obtained through numerical methods. The simulations show fuzzy logic control methods are effective in suppressing flutter and provide a smart approach for this complicated system.
The Medical Microrobot Control System Design via Fuzzy Logic Application
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A. S. Yuschenko
2014-01-01
Full Text Available The aim of the investigation is the development of the instruments and technologies for diagnostics and treatment of tube-like human’s organs such as blood vessels and intestines. The medical microrobots may be applied to move along the tube-like organs by the same way as a worm. Such microrobots had been presented in some works in Russia and abroad among them is a project of BMSTU. The control system of the robot has to adapt the movement process to the peculiarity of the biology environment. The safety of the application of robotic device inside the human body is the main requirement to the construction.An experimental model of microrobot has three segments which contracting successively to ensure progressive movement of the device. The diameter of the robot is smaller than the same of the blood vessel. So it is pressed to the internal cover of the vessel by the special planes to avoid the thrombosis of the vessel. Every segment of robot contain three contact elements, pressure sensors and a regulator to control the pressure of the elements to the internal surface of the vessel. Aboard the robot is a micro-video camera has been mounted to inform the surgeon of the situation inside the vessel and other micro-devices. The supporting plates carry tens metric sensors to control the contact forces. The driver of the robot is of hydraulic type with physiologic solution to avoid the danger of embolism.Microrobot is a part of the robotic system including also a hydro-driver mounted in the stationary part of the system and intelligent interface of the operator. The surgeon-operator has opportunity to observe the inner surface of the vessel by the sensors mounted aboard the robot and to control the robot movement along the vessel. The construction of the microrobot has to guarantee the stable position of the robot in the moving blood flow and its movement inside the vessel without any damage of the inner surface.The peculiarity of the microrobot
Mohit Jha; Shailja Shukla
2014-01-01
During the past several years fuzzy logic control has swell from one of the major active and profitable areas for research in the application of fuzzy set, especially in the zone of industrial process which do not lead themselves to control conventional methods because of lack of quantitative data regarding the input-output relations. Fuzzy control is based on fuzzy logic- a logical system which is much closer in spirit to human thinking and natural language than conventional ...
Qazi, Abroon Jamal; de Silva, Clarence W; Khan, Afzal; Khan, Muhammad Tahir
2014-01-01
This paper uses a quarter model of an automobile having passive and semiactive suspension systems to develop a scheme for an optimal suspension controller. Semi-active suspension is preferred over passive and active suspensions with regard to optimum performance within the constraints of weight and operational cost. A fuzzy logic controller is incorporated into the semi-active suspension system. It is able to handle nonlinearities through the use of heuristic rules. Particle swarm optimization (PSO) is applied to determine the optimal gain parameters for the fuzzy logic controller, while maintaining within the normalized ranges of the controller inputs and output. The performance of resulting optimized system is compared with different systems that use various control algorithms, including a conventional passive system, choice options of feedback signals, and damping coefficient limits. Also, the optimized semi-active suspension system is evaluated for its performance in relation to variation in payload. Furthermore, the systems are compared with respect to the attributes of road handling and ride comfort. In all the simulation studies it is found that the optimized fuzzy logic controller surpasses the other types of control.
Electric Drive Control with Rotor Resistance and Rotor Speed Observers Based on Fuzzy Logic
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C. Ben Regaya
2014-01-01
Full Text Available Many scientific researchers have proposed the control of the induction motor without speed sensor. These methods have the disadvantage that the variation of the rotor resistance causes an error of estimating the motor speed. Thus, simultaneous estimation of the rotor resistance and the motor speed is required. In this paper, a scheme for estimating simultaneously the rotor resistance and the rotor speed of an induction motor using fuzzy logic has been developed. We present a method which is based on two adaptive observers using fuzzy logic without affecting each other and a simple algorithm in order to facilitate the determination of the optimal values of the controller gains. The control algorithm is proved by the simulation tests. The results analysis shows the characteristic robustness of the two observers of the proposed method even in the case of variation of the rotor resistance.
A tunable fuzzy logic controller for the vehicle semi-active suspension system
Institute of Scientific and Technical Information of China (English)
方子帆; DENG; Zhaoxiang; 等
2002-01-01
On the basis of analyzing the system constitution of vehicle semi-active suspension,a 4-DOF(degree of freedom)dynamic model is established.A tunable fuzzy logic controller is designed by using without quantification method and taking into account the uncertainty,nonlinearity and complexity of parameters for a vehicle suspension system.Simulation to test the performance of this controller is performed under random excitations and definite disturbances of a C grade road,and the effects of time delay and changes of system parameters on the vehicle suspension system are researched.The numerical simulation shows that the performance of the designed tunable fuzzy logic controller is effective,stable and reliable.
Elimination & Mitigation of Sag & Swell Using a New UPQC-S Methodology & Fuzzy Logic Controller
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Kanaka Raju Kalla,
2014-05-01
Full Text Available This paper presents the enhancement of voltage sags, harmonic distortion and low power factor using Unified Power Quality Conditioner (UPQC with Fuzzy Logic Controller in distribution system, The series inverter of UPQC is controlled to perform simultaneous 1 voltage sag/swell compensation and 2 load reactive power sharing with the shunt inverter. Since the series inverter simultaneously delivers active and reactive powers, this concept is named as UPQC-S (S for complex power in this paper; a detailed mathematical formulation of PAC for UPQC-S is carried out. In this paper details are carried out on both series inverter & shunt inverter, and fuzzy logic controller is applied to shunt inverter in order to dc fluctuations and to compensate reactive power. The feasibility and effectiveness of the proposed UPQC-S approach are validated by simulation in using MATLAB software.
Design and Lyapunov Stability Analysis of a Fuzzy Logic Controller for Autonomous Road Following
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Yi Fu
2010-01-01
Full Text Available Autonomous road following is one of the major goals in intelligent vehicle applications. The development of an autonomous road following embedded system for intelligent vehicles is the focus of this paper. A fuzzy logic controller (FLC is designed for vision-based autonomous road following. The stability analysis of this control system is addressed. Lyapunov's direct method is utilized to formulate a class of control laws that guarantee the convergence of the steering error. Certain requirements for the control laws are presented for designers to choose a suitable rule base for the fuzzy controller in order to make the system stable. Stability of the proposed fuzzy controller is guaranteed theoretically and also demonstrated by simulation studies and experiments. Simulations using the model of the four degree of freedom nonholonomic robotic vehicle are conducted to investigate the performance of the fuzzy controller. The proposed fuzzy controller can achieve the desired steering angle and make the robotic vehicle follow the road successfully. Experiments show that the developed intelligent vehicle is able to follow a mocked road autonomously.
Flight test results of the fuzzy logic adaptive controller-helicopter (FLAC-H)
Wade, Robert L.; Walker, Gregory W.
1996-05-01
The fuzzy logic adaptive controller for helicopters (FLAC-H) demonstration is a cooperative effort between the US Army Simulation, Training, and Instrumentation Command (STRICOM), the US Army Aviation and Troop Command, and the US Army Missile Command to demonstrate a low-cost drone control system for both full-scale and sub-scale helicopters. FLAC-H was demonstrated on one of STRICOM's fleet of full-scale rotary-winged target drones. FLAC-H exploits fuzzy logic in its flight control system to provide a robust solution to the control of the helicopter's dynamic, nonlinear system. Straight forward, common sense fuzzy rules governing helicopter flight are processed instead of complex mathematical models. This has resulted in a simplified solution to the complexities of helicopter flight. Incorporation of fuzzy logic reduced the cost of development and should also reduce the cost of maintenance of the system. An adaptive algorithm allows the FLAC-H to 'learn' how to fly the helicopter, enabling the control system to adjust to varying helicopter configurations. The adaptive algorithm, based on genetic algorithms, alters the fuzzy rules and their related sets to improve the performance characteristics of the system. This learning allows FLAC-H to automatically be integrated into a new airframe, reducing the development costs associated with altering a control system for a new or heavily modified aircraft. Successful flight tests of the FLAC-H on a UH-1H target drone were completed in September 1994 at the White Sands Missile Range in New Mexico. This paper discuses the objective of the system, its design, and performance.
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E.A. Ramadan
2014-09-01
Full Text Available This paper presents an improved adaptive fuzzy logic speed controller for a DC motor, based on field programmable gate array (FPGA hardware implementation. The developed controller includes an adaptive fuzzy logic control (AFLC algorithm, which is designed and verified with a nonlinear model of DC motor. Then, it has been synthesised, functionally verified and implemented using Xilinx Integrated Software Environment (ISE and Spartan-3E FPGA. The performance of this controller has been successfully validated with good tracking results under different operating conditions.
A Fuzzy Logic Based Controller for the Automated Alignment of a Laser-beam-smoothing Spatial Filter
Krasowski, M. J.; Dickens, D. E.
1992-01-01
A fuzzy logic based controller for a laser-beam-smoothing spatial filter is described. It is demonstrated that a human operator's alignment actions can easily be described by a system of fuzzy rules of inference. The final configuration uses inexpensive, off-the-shelf hardware and allows for a compact, readily implemented embedded control system.
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Saifullah Khalid
2016-09-01
Full Text Available Three conventional control constant instantaneous power control, sinusoidal current control, and synchronous reference frame techniques for extracting reference currents for shunt active power filters have been optimized using Fuzzy Logic control and Adaptive Tabu search Algorithm and their performances have been compared. Critical analysis of Comparison of the compensation ability of different control strategies based on THD and speed will be done, and suggestions will be given for the selection of technique to be used. The simulated results using MATLAB model are presented, and they will clearly prove the value of the proposed control method of aircraft shunt APF. The waveforms observed after the application of filter will be having the harmonics within the limits and the power quality will be improved.
Modelling and Control of the Qball X4 Quadrotor System based on Pid and Fuzzy Logic Structure
Bodrumlu, Tolga; Turan Soylemez, Mehmet; Mutlu, Ilhan
2017-01-01
This work focuses on a quadrocopter model, which was developed by QuanserTM and named as Qball X4. First, mathematical model of the Qball X4 is obtained. Then, a conventional PID control technique is presented. This PID control parameters come from Qball user manual. After the presentation of conventional PID control, as an extension of the conventional PID control theory, a different fuzzy controller structure is given. The proposed fuzzy controller structure is based on fuzzy logic and its name is PID type fuzzy controller. All of the simulations are done in MATLABTM environment.
Optimization of the Fermentation Process in a Brewery with a Fuzzy Logic Controller
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Philip B. OSOFISAN
2007-08-01
Full Text Available In this research work, the fermentation process in a Brewery will be optimized, with the application of Fuzzy Logic Controller (FLC. Fermentation is controlled by regulating the temperature, the oxygen content and the pitch rate; but the temperature plays a dominant role in the optimization of the fermentation process. For our case study (Guinness Nigeria Plc the optimal fermentation temperature is 16ºC, so the FLC has been designed to maintain this temperature. The designed FLC can also be applied to maintain any other optimal fermentation temperature e.g. 20ºC. These two cases have been investigated. The FLC has been stimulated on a digital computer using MATLAB 5.0 Fuzzy Logic Tool Box.
Digital Fuzzy logic and PI control of phase-shifted full-bridge current-doubler converter
DEFF Research Database (Denmark)
Török, Lajos; Munk-Nielsen, Stig
2011-01-01
Simple digital fuzzy logic voltage control of a phaseshifted full-bridge (PSFB) converter is proposed in this article. A comparison of the fuzzy controller and the classical PI voltage controller is presented and their effects on the converter dynamics are analyzed. Simulation model of the conver...... of the converter was built in Matlab/Simulink using PLECS. A 600W PSFB convert was designed and built and the control strategies were implemented in a 16 bit fixed point dsPIC microcontroller. The advantages and disadvantages of using Fuzzy logic control are highlighted....
A fuzzy logic controller for hormone administration using an implantable pump
Coles, L. Stephen; Wells, George H., Jr.
1994-01-01
This paper describes the requirements for a Fuzzy Logic Controller for the physiologic administration of hormones by means of a FDA-approved surgically implantable infusion pump. Results of a LabVIEW computer simulation for the administration of insulin for diabetic adult patients as well as human growth hormone for pediatric patients are presented. A VHS video tape of the simulation in action has been prepared and is available for viewing.
Increase efficiency CNC lathe with the help of fuzzy logic controller (FLC
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Mošorinski Predrag R.
2016-01-01
Full Text Available This paper discusses the process of increasing the effectiveness of CNC lathe for carrying out the appropriate experiments. Experiments are related to the plastics processing machine and programming fuzzy logic controller (FLC for the requirements of machining. Input parameters of the FLCare obtained as a result of previous experimental parameters set by experience and with a great subjective impact of technologists. Expected results of FLC's settings are based on the complete autonomy of the process and eliminating subjective errors.
Benefits and challenges of controlling a LED AFS (Adaptive Front-lighting System) using fuzzy logic
2011-01-01
Texto completo: acesso restrito. p.579−588 The vehicular illumination system has undergone considerable technological advances in recent decades such as the use of a Light Emitting Diode (LED) Adaptive Front-lighting System (AFS), which represents an industry breakthrough in lighting technology and is rapidly becoming one of the most important innovative technologies around the world in the lighting community. This paper presents AFS control alternatives using fuzzy logic (types 1...
Energy Technology Data Exchange (ETDEWEB)
Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira; Brito, Thiago Souza Pereira de; Afonso, Antonio Claudio Marques, E-mail: wagner@unicap.br, E-mail: cabol@ufpe.br, E-mail: afonsofisica@gmail.com, E-mail: thiago.brito86@yahoo.com.br [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Centro de Tecnologia e Geociencias. Departamento de Energia Nuclear; Cruz Filho, Antonio Jose da; Marques, Jose Antonio, E-mail: antonio.jscf@gmail.com, E-mail: jamarkss@uol.com.br [Universidade Catolica de Pernambuco (CCT/PUC-PE), Recife, PE (Brazil). Centro de Ciencias e Tecnologia; Teixeira, Marcello Goulart, E-mail: marcellogt@dcc.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ (Brazil). Instituto de Matematica. Dept. de Matematica
2013-07-01
Nuclear reactors are in nature nonlinear systems and their parameters vary with time as a function of power level. These characteristics must be considered if large power variations occur in power plant operational regimes, such as in load-following conditions. A PWR reactor has a component called pressurizer, whose function is to supply the necessary high pressure for its operation and to contain pressure variations in the primary cooling system. The use of control systems capable of reducing fast variations of the operation variables and to maintain the stability of this system is of fundamental importance. The best-known controllers used in industrial control processes are proportional-integral-derivative (PID) controllers due to their simple structure and robust performance in a wide range of operating conditions. However, designing a fuzzy controller is seen to be a much less difficult task. Once a Fuzzy Logic controller is designed for a particular set of parameters of the nonlinear element, it yields satisfactory performance for a range of these parameters. The objective of this work is to develop fuzzy proportional-integral-derivative (fuzzy-PID) control strategies to control the level of water in the reactor. In the study of the pressurizer, several computer codes are used to simulate its dynamic behavior. At the fuzzy-PID control strategy, the fuzzy logic controller is exploited to extend the finite sets of PID gains to the possible combinations of PID gains in stable region. Thus the fuzzy logic controller tunes the gain of PID controller to adapt the model with changes in the water level of reactor. The simulation results showed a favorable performance with the use to fuzzy-PID controllers. (author)
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Puchalski Bartosz
2015-12-01
Full Text Available In the paper, analysis of multi-region fuzzy logic controller with local PID controllers for steam generator of pressurized water reactor (PWR working in wide range of thermal power changes is presented. The U-tube steam generator has a nonlinear dynamics depending on thermal power transferred from coolant of the primary loop of the PWR plant. Control of water level in the steam generator conducted by a traditional PID controller which is designed for nominal power level of the nuclear reactor operates insufficiently well in wide range of operational conditions, especially at the low thermal power level. Thus the steam generator is often controlled manually by operators. Incorrect water level in the steam generator may lead to accidental shutdown of the nuclear reactor and consequently financial losses. In the paper a comparison of proposed multi region fuzzy logic controller and traditional PID controllers designed only for nominal condition is presented. The gains of the local PID controllers have been derived by solving appropriate optimization tasks with the cost function in a form of integrated squared error (ISE criterion. In both cases, a model of steam generator which is readily available in literature was used for control algorithms synthesis purposes. The proposed multi-region fuzzy logic controller and traditional PID controller were subjected to broad-based simulation tests in rapid prototyping software - Matlab/Simulink. These tests proved the advantage of multi-region fuzzy logic controller with local PID controllers over its traditional counterpart.
FPGA based Fuzzy Logic Controller for plasma position control in ADITYA Tokamak
Energy Technology Data Exchange (ETDEWEB)
Suratia, Pooja, E-mail: poojasuratia@yahoo.com [Electrical Engineering Department, Faculty of Technology and Engineering, The Maharaja Sayajirao University of Baroda, Kalabhavan, Vadodara 390001, Gujarat (India); Patel, Jigneshkumar, E-mail: jjp@ipr.res.in [Institute for Plasma Research, Bhat, Gandhinagar 382428, Gujarat (India); Rajpal, Rachana, E-mail: rachana@ipr.res.in [Institute for Plasma Research, Bhat, Gandhinagar 382428, Gujarat (India); Kotia, Sorum, E-mail: smkotia-eed@msubaroda.ac.in [Electrical Engineering Department, Faculty of Technology and Engineering, The Maharaja Sayajirao University of Baroda, Kalabhavan, Vadodara 390001, Gujarat (India); Govindarajan, J., E-mail: govindarajan@ipr.res.in [Institute for Plasma Research, Bhat, Gandhinagar 382428, Gujarat (India)
2012-11-15
Highlights: Black-Right-Pointing-Pointer Evaluation and comparison of the working performance of FLC is done with that of PID Controller. Black-Right-Pointing-Pointer FLC is designed using MATLAB Fuzzy Logic Toolbox, and validated on ADITYA RZIP model. Black-Right-Pointing-Pointer FLC was implemented on a FPGA. The close-loop testing is done by interfacing FPGA to MATLAB/Simulink. Black-Right-Pointing-Pointer Developed FLC controller is able to maintain the plasma column within required range of {+-}0.05 m and was found to give robust control against various disturbances and faster and smoother response compared to PID Controller. - Abstract: Tokamaks are the most promising devices for obtaining nuclear fusion energy from high-temperature, ionized gas termed as Plasma. The successful operation of tokamak depends on its ability to confine plasma at the geometric center of vacuum vessel with sufficient stability. The quality of plasma discharge in ADITYA Tokamak is strongly related to the radial position of the plasma column in the vacuum vessel. If the plasma column approaches too near to the wall of vacuum vessel, it leads to minor or complete disruption of plasma. Hence the control of plasma position throughout the entire plasma discharge duration is a fundamental requirement. This paper describes Fuzzy Logic Controller (FLC) which is designed for radial plasma position control. This controller is tested and evaluated on the ADITYA RZIP control model. The performance of this FLC was compared with that of Proportional-Integral-Derivative (PID) Controller and the response was found to be faster and smoother. FLC was implemented on a Field Programmable Gate Array (FPGA) chip with the use of a Very High-Speed Integrated-Circuits Hardware Description-Language (VHDL).
Mauseth, Richard; Wang, Youqing; Dassau, Eyal; Kircher, Robert; Matheson, Donald; Zisser, Howard; Jovanovic, Lois; Doyle, Francis J
2010-07-01
Physicians tailor insulin dosing based on blood glucose goals, response to insulin, compliance, lifestyle, eating habits, daily schedule, and fear of and ability to detect hypoglycemia. We introduce a method that allows a physician to tune a fuzzy logic controller (FLC) artificial pancreas (AP) for a particular patient. It utilizes the physician's judgment and weighing of various factors. The personalization factor (PF) is a scaling of the dose produced by the FLC and is used to customize the dosing. The PF has discrete values of 1 through 5. The proposed method was developed using a database of results from 30 University of Virginia/Padova Metabolic Simulator in silico subjects (10 adults, 10 adolescents, and 10 children). Various meal sizes and timing were used to provide the physician information on which to base an initial dosing regimen and PF. Future decisions on dosing aggressiveness using the PF would be based on the patient's data at follow-up. Three examples of a wide variation in diabetes situations are given to illustrate the physician's thought process when initially configuring the AP system for a specific patient. Fuzzy logic controllers are developed by encoding human expertise into the design of the controller. The FLC methodology allows for the real-time scaling of doses without compromising the integrity of the dosing rules matrix. The use of the PF to individualize the AP system is enabled by the fuzzy logic development methodology. 2010 Diabetes Technology Society.
A Position Controller Model on Color-Based Object Tracking using Fuzzy Logic
Cahyo Wibowo, Budi; Much Ibnu Subroto, Imam; Arifin, Bustanul
2017-04-01
Robotics vision is applying technology on the camera to view the environmental conditions as well as the function of the human eye. Colour object tracking system is one application of robotics vision technology with the ability to follow the object being detected. Several methods have been used to generate a good response position control, but most are still using conventional control approach. Fuzzy logic which includes several step of which is to determine the value of crisp input must be fuzzification. The output of fuzzification is forwarded to the process of inference in which there are some fuzzy logic rules. The inference output forwarded to the process of defuzzification to be transformed into outputs (crisp output) to drive the servo motors on the X-axis and Y-axis. Fuzzy logic control is applied to the color-based object tracking system, the system is successful to follow a moving object with average speed of 7.35 cm/s in environments with 117 lux light intensity.
PID self tuning control based on Mamdani fuzzy logic control for quadrotor stabilization
Energy Technology Data Exchange (ETDEWEB)
Priyambodo, Tri Kuntoro, E-mail: mastri@ugm.ac.id; Putra, Agfianto Eko [Aerospace and Aeronautics Electronics Research Group, Universitas Gadjah Mada, Yogyakarta (Indonesia); Department of Computer Science and Electronics, Universitas Gadjah Mada, Yogyakarta (Indonesia); Dharmawan, Andi, E-mail: andi-dharmawan@ugm.ac.id [Department of Computer Science and Electronics, Universitas Gadjah Mada, Yogyakarta (Indonesia)
2016-02-01
Quadrotor as one type of UAV have the ability to perform Vertical Take Off and Landing (VTOL). It allows the Quadrotor to be stationary hovering in the air. PID (Proportional Integral Derivative) control system is one of the control methods that are commonly used. It is usually used to optimize the Quadrotor stabilization at least based on the three Eulerian angles (roll, pitch, and yaw) as input parameters for the control system. The three constants of PID can be obtained in various methods. The simplest method is tuning manually. This method has several weaknesses. For example if the three constants are not exact, the resulting response will deviate from the desired result. By combining the methods of PID with fuzzy logic systems where human expertise is implemented into the machine language is expected to further optimize the control system.
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Hodeiseh Gordan
2012-11-01
Full Text Available This paper proposes a novel inference mechanism for an interval type-2 Takagi-Sugeno-Kang fuzzy logic controlsystem (IT2 TSK FLCS. This paper focuses on control applications for case both plant and controller use A2-C0 TSK models. The defuzzified output of the T2FLS is then obtained by averaging the defuzzified outputs of the resultant four embedded T1FLSs in order to reduce the computational burden of T2 TSK FS. A simplified T2 TSK FS based on a hybrid structure of four type-1 fuzzy systems (T1 TSK FS. A simulation example is presented to show the eectiveness of this method.
Olliver, S; Davis, G M; Hatzakis, G E
2003-01-01
We have previously developed a fuzzy logic controller for weaning adults with chronic obstructive pulmonary disease using pressure support ventilation (PSV). We used the core of our fuzzy logic-based weaning platform and further developed parametrizable components for weaning newborns of differing body size and disease-state. The controller was validated on neonates recovering from congenital heart disease (CHD) while receiving synchronous intermittent mandatory ventilation (SIMV). We wished to compare the efficacy of this controller versus the bedside weaning protocol in children with respiratory syncytial virus pneumonitis/bronchiolitis (RSV) in the pediatric intensive care unit (PICU). The fuzzy controller evaluated the "current" and "trend" weaning status of the newborn to quantitatively determine the change in the SIMV integrated ventilatory setting. For the "current" status it used heart rate (HR), respiratory rate (RR), tidal volume (VT) and oxygen saturation (SaO2), while for the "trend" status the differences of deltaRR/ deltat, deltaHR/ deltat, and deltaSaO2/ deltat recorded between two subsequent time points were utilized. The enumerated vital signs were fuzzified and then probability levels of occurrence were assigned. Individualized "golden" goals for SaO2 were set for each newborn. We retrospectively assessed the charts of 19 newborns, 113+/-128 days old, 5,546+/-2,321 gr body weight, weaning for 99+/-46 days, at 2-hour intervals. The SIMV levels proposed by the fuzzy controller were matched to those levels actually applied. In 60% of the time both values coincided. For the remaining 40%, the controller was more aggressive suggesting lower values of SIMV than the applied ones. The Area under the SIMV curves over time was 1,969+/-1,044 for the applied vs 1,886+/-978 for the suggested levels, respectively. The fuzzy controller adjusted for body size and disease-pattern can approximate the actual weaning course of newborns with RSV.
Application of Fuzzy Logic in Servo Motor
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Shereen F. Abd-Alkarim
2007-01-01
Full Text Available In this work the design and application of a fuzzy logic controller to DC-servomotor is investigated. The proposed strategy is intended to improve the performance of the original control system by use of a fuzzy logic controller (FLC as the motor load changes. Computer simulation demonstrates that FLC is effective in position control of a DC-servomotor comparing with conventional one.
Type-2 fuzzy logic control of a 2-DOF helicopter (TRMS system)
Zeghlache, Samir; Kara, Kamel; Saigaa, Djamel
2014-09-01
The helicopter dynamic includes nonlinearities, parametric uncertainties and is subject to unknown external disturbances. Such complicated dynamics involve designing sophisticated control algorithms that can deal with these difficulties. In this paper, a type 2 fuzzy logic PID controller is proposed for TRMS (twin rotor mimo system) control problem. Using triangular membership functions and based on a human operator experience, two controllers are designed to control the position of the yaw and the pitch angles of the TRMS. Simulation results are given to illustrate the effectiveness of the proposed control scheme.
On the stability of interval type-2 TSK fuzzy logic control systems.
Biglarbegian, Mohammad; Melek, William W; Mendel, Jerry M
2010-06-01
Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainties. This paper proposes a novel inference mechanism for an interval type-2 Takagi-Sugeno-Kang fuzzy logic control system (IT2 TSK FLCS) when antecedents are type-2 fuzzy sets and consequents are crisp numbers (A2-C0). The proposed inference mechanism has a closed form which makes it more feasible to analyze the stability of this FLCS. This paper focuses on control applications for the following cases: 1) Both plant and controller use A2-C0 TSK models, and 2) the plant uses type-1 Takagi-Sugeno (TS) and the controller uses IT2 TS models. In both cases, sufficient stability conditions for the stability of the closed-loop system are derived. Furthermore, novel linear-matrix-inequality-based algorithms are developed for satisfying the stability conditions. Numerical analyses are included which validate the effectiveness of the new inference methods. Case studies reveal that an IT2 TS FLCS using the proposed inference engine clearly outperforms its type-1 TSK counterpart. Moreover, due to the simple nature of the proposed inference engine, it is easy to implement in real-time control systems. The methods presented in this paper lay the mathematical foundations for analyzing the stability and facilitating the design of stabilizing controllers of IT2 TSK FLCSs and IT2 TS FLCSs with significantly improved performance over type-1 approaches.
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Y. K. Bhateshvar
2016-01-01
Full Text Available This paper attempts to develop a linearized model of automatic generation control (AGC for an interconnected two-area reheat type thermal power system in deregulated environment. A comparison between genetic algorithm optimized PID controller (GA-PID, particle swarm optimized PID controller (PSO-PID, and proposed two-stage based PSO optimized fuzzy logic controller (TSO-FLC is presented. The proposed fuzzy based controller is optimized at two stages: one is rule base optimization and other is scaling factor and gain factor optimization. This shows the best dynamic response following a step load change with different cases of bilateral contracts in deregulated environment. In addition, performance of proposed TSO-FLC is also examined for ±30% changes in system parameters with different type of contractual demands between control areas and compared with GA-PID and PSO-PID. MATLAB/Simulink® is used for all simulations.
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Nun Pitalúa-Díaz
2015-05-01
Full Text Available Exposure to hazardous concentrations of volatile organic compounds indoors in small workshops could affect the health of workers, resulting in respirative diseases, severe intoxication or even cancer. Controlling the concentration of volatile organic compounds is required to prevent harmful conditions for workers in indoor environments. In this document, PI and fuzzy PI controllers were used to reduce hazardous indoor air benzene concentrations in small workplaces. The workshop is represented by means of a well-mixed room model. From the knowledge obtained from the model, PI and fuzzy PI controllers were designed and their performances were compared. Both controllers were able to maintain the benzene concentration within secure levels for the workers. The fuzzy PI controller performed more efficiently than the PI controller. Both approaches could be expanded to control multiple extractor fans in order to reduce the air pollution in a shorter time. The results from the comparative analysis showed that implementing a fuzzy logic PI controller is promising for assuring indoor air quality in this kind of hazardous work environment.
Hardware simulation of automatic braking system based on fuzzy logic control
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Noor Cholis Basjaruddin
2016-07-01
Full Text Available In certain situations, a moving or stationary object can be a barrier for a vehicle. People and vehicles crossing could potentially get hit by a vehicle. Objects around roads as sidewalks, road separator, power poles, and railroad gates are also a potential source of danger when the driver is inattentive in driving the vehicle. A device that can help the driver to brake automatically is known as Automatic Braking System (ABS. ABS is a part of the Advanced Driver Assistance Systems (ADAS, which is a device designed to assist the driver in driving the process. This device was developed to reduce human error that is a major cause of traffic accidents. This paper presents the design of ABS based on fuzzy logic which is simulated in hardware by using a remote control car. The inputs of fuzzy logic are the speed and distance of the object in front of the vehicle, while the output of fuzzy logic is the intensity of braking. The test results on the three variations of speed: slow-speed, medium-speed, and high-speed shows that the design of ABS can work according to design.
Minimal sensor count approach to fuzzy logic rotary blood pump flow control.
Casas, Fernando; Ahmed, Nisar; Reeves, Andrew
2007-01-01
A rotary blood pump fuzzy logic flow controller without flow sensors was developed and tested in vitro. The controller, implemented in LabView, was set to maintain a flow set point in the presence of external pressure disturbances. Flow was estimated as a function of measured pump's delta P and speed, using a steady-state, nonlinear approximation. The fuzzy controller used the pump's flow estimate and delta P as feedback variables. The defuzzified control output manipulated the pump speed. Membership functions included flow error, delta P, and pump speed. Experimental runs in a mock loop (water/glycerin 3.5 cPs, 37 degrees C), using the estimated flow, were compared with those using a Transonic flow meter for nine conditions of flow and delta P (4 to 6 L/min, 150 to 350 mm Hg). Pressure disturbances generated by a servo pinch valve ranged from +/-23 to +/-47 mm Hg. Results indicated that the fuzzy controller ably regulated the flow set point to within +/-10% of the baseline even under large swings in pressure. There was no difference in controller performance between the ultrasonic flow measurement and the estimated flow calculation scenarios. These tests demonstrated that the fuzzy controller is capable of rejecting disturbances and regulating flow to acceptable limits while using a flow estimate.
Perancangan Coupled Fuzzy Logic Controller pada Prototipe Mesin Computer Numerical Control (CNC
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Nabilla Gustiviana
2012-09-01
Full Text Available Tingkat ketelitian mesin CNC dalam membuat suatu kontur merupakan hal yang penting. Adanya gesekan antara mata pahat dengan benda kerja saat melakukan gerakan feeding dalam membentuk suatu kontur dapat berakibat pada kesalahan bentuk kontur yang akan dihasilkan apabila di tiap sumbunya dikontrol secara individu. Untuk mengatasi permasalahan tersebut, maka dirancang kombinasi antara Fuzzy Logic Controller sebagai kontroler individu yang mengatasi permasalahan di tiap sumbu, dengan kontroler koordinasi, yaitu Cross-Coupled Controller. Algoritma dari kontroler ini dibuat dengan menggunakan software LabView 8.6. Hasil simulasi menunjukkan bahwa dengan menambahkan kontroler koordinasi, dapat memperbaiki nilai indeks performansi sebesar 37,5% untuk kontur linier dan 2,78% untuk kontur lingkaran
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Pritha Agrawal
2014-02-01
Full Text Available This paper presents a comparative analysis of speed control of brushless DC motor (BLDC drive fed with conventional two-level, three and five level diode clamped multilevel inverter (DC-MLI. The performance of the drive system is successfully evaluated using Fuzzy Logic (FL based speed controller. The control structure of the proposed drive system is described. The speed and torque characteristic of conventional two-level inverter is compared with the three and five-level multilevel inverter (MLI for various operating conditions. The three and five level diode clamped multilevel inverters are simulated using IGBT’s and the mathematical model of BLDC motor has been developed in MATLAB/SIMULINK environment. The simulation results show that the Fuzzy based speed controller eliminate torque ripples and provides fast speed response. The developed Fuzzy Logic model has the ability to learn instantaneously and adapt its own controller parameters based on disturbances with minimum steady state error, overshoot and rise time of the output voltage.
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Chandra Babu Paduchuri
2014-01-01
Full Text Available A design of multiconverter unified power quality conditioner to improve the power quality issues is presents in this paper. Modified SRF theory and fuzzy logic controller technique are incorporated in this modelling. This newly designed controller is connected to a source in order to compensate voltage and current in the two feeders. The expanded concept of UPQC is multi converter-UPQC; this system has two series voltage source converter (VSC and one shunt VSC connected back to back. In the proposed system, the power can be conveyed from one feeder to another in order to mitigate the voltage sag, swell, interruption and transient response of the system. The control strategies of multi converter-UPQC are designed based on the modified synchronous reference frame theory with fuzzy logic controller. The transient response of the fuzzy logic controller in dc-link voltage controller will be very fast. The relevant simulation and compensation performance analysis of multi converter-UPQC with fuzzy logic controller is performed using MATLAB/Simulink software.
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Abdul Kareem
2012-07-01
Full Text Available This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness of the proposed controller over the first order Sliding Mode Fuzzy Logic controller is illustrated by Matlab based simulations performed on a DC-DC Buck converter. Based on this comparison, the proposed controller is shown to obtain the desired transient response without causing chattering and error under steady-state conditions. The proposed controller is able to give robust performance in terms of rejection to input voltage variations and load variations.
Automatic control with fuzzy logic of home-made beer production in maceration and cooking stages
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Mariano Luján Corro
2010-06-01
Full Text Available The process of home-made beer production in the malt maceration and cooking stages was controlled automatically with fuzzy logic, across different performers considering the time and temperature of the process, using 2009LabVIEW. The equipment was mainly composed of three 20 L capacity stainless steel containers (water supply, maceration and cooking, an additional hops container, a data acquisition card (PIC 16F877a micro controller, three LM35 temperature sensors and 11 on/off type performers, which were governed by a total of 47 Mandani type fuzzy rules with trapezoidal membership functions, using the method of center area for the defuzzification. The performers: electrovalves (5, pumps (2, heaters (3 and a stirrer, in approximately 4 hours, were adequately controlled in their early maceration and cooking stages. The beer obtained by automatic control with fuzzy logic in the maceration and cooking stages, had the following characteristics: 0.98 g/cm3 of density, 3.9 of pH, total acidity expressed as 0.87% of lactic acid, 6.2ºGL of alcoholic degree and 0.91% w/v of CO2 percentage.
Scheduling By Using Fuzzy Logic in Manufacturing
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Miss. Ashwini. A. Mate
2014-07-01
Full Text Available This paper represents the scheduling process in furniture manufacturing unit. It gives the fuzzy logic application in flexible manufacturing system. Flexible manufacturing systems are production system in furniture manufacturing unit. FMS consist of same multipurpose numerically controlled machines. Here in this project the scheduling has been done in FMS by using fuzzy logic tool in Matlab software. The fuzzy logic based scheduling model in this paper will deals with the job and best alternative route selection with multi-criteria of machine. Here two criteria for job and sequencing and routing with rules. This model is applicable to the scheduling of any manufacturing industry.
Network Based Building Lighting Design and Fuzzy Logic via Remote Control
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Cemal YILMAZ
2009-02-01
Full Text Available In this paper, a network based building lighting system is implemented. Profibus-DP network structure is used in the design and Fuzzy Logic Controller (FLC is used on control of the building lighting. Informations received from sensors which measures level of the building illumination is used on FLC and they are transferred to the system by Profibus-DP network. Control of lighting luminaries are made via Profibus-DP network. The illuminance inside the bulding is fitted required level. Energy saving and healthy lighting facilities have been obtained by the design.
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Abdul Kareem
2012-08-01
Full Text Available This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for thecontrol of dynamic uncertain systems. The proposed controller combines the advantages of Second orderSliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability androbustness of the system with the proposed controller are guaranteed. In addition, the proposed controlleris well suited for simple design and implementation. The effectiveness of the proposed controller over thefirst order Sliding Mode Fuzzy Logic controller is illustrated by Matlab based simulations performed on aDC-DC Buck converter. Based on this comparison, the proposed controller is shown to obtain the desiredtransient response without causing chattering and error under steady-state conditions. The proposedcontroller is able to give robust performance in terms of rejection to input voltage variations and loadvariations
Fuzzy logic mode switching in helicopters
Sherman, Porter D.; Warburton, Frank W.
1993-01-01
The application of fuzzy logic to a wide range of control problems has been gaining momentum internationally, fueled by a concentrated Japanese effort. Advanced Research & Development within the Engineering Department at Sikorsky Aircraft undertook a fuzzy logic research effort designed to evaluate how effective fuzzy logic control might be in relation to helicopter operations. The mode switching module in the advanced flight control portion of Sikorsky's motion based simulator was identified as a good candidate problem because it was simple to understand and contained imprecise (fuzzy) decision criteria. The purpose of the switching module is to aid a helicopter pilot in entering and leaving coordinated turns while in flight. The criteria that determine the transitions between modes are imprecise and depend on the varied ranges of three flight conditions (i.e., simulated parameters): Commanded Rate, Duration, and Roll Attitude. The parameters were given fuzzy ranges and used as input variables to a fuzzy rulebase containing the knowledge of mode switching. The fuzzy control program was integrated into a real time interactive helicopter simulation tool. Optimization of the heading hold and turn coordination was accomplished by interactive pilot simulation testing of the handling quality performance of the helicopter dynamic model. The fuzzy logic code satisfied all the requirements of this candidate control problem.
Hierarchical rule-based monitoring and fuzzy logic control for neuromuscular block.
Shieh, J S; Fan, S Z; Chang, L W; Liu, C C
2000-01-01
The important task for anaesthetists is to provide an adequate degree of neuromuscular block during surgical operations, so that it should not be difficult to antagonize at the end of surgery. Therefore, this study examined the application of a simple technique (i.e., fuzzy logic) to an almost ideal muscle relaxant (i.e., rocuronium) at general anaesthesia in order to control the system more easily, efficiently, intelligently and safely during an operation. The characteristics of neuromuscular blockade induced by rocuronium were studied in 10 ASA I or II adult patients anaesthetized with inhalational (i.e., isoflurane) anaesthesia. A Datex Relaxograph was used to monitor neuromuscular block. And, ulnar nerve was stimulated supramaximally with repeated train-of-four via surface electrodes at the wrist. Initially a notebook personal computer was linked to a Datex Relaxograph to monitor electromyogram (EMG) signals which had been pruned by a three-level hierarchical structure of filters in order to design a controller for administering muscle relaxants. Furthermore, a four-level hierarchical fuzzy logic controller using the fuzzy logic and rule of thumb concept has been incorporated into the system. The Student's test was used to compare the variance between the groups. p control of muscle relaxation with a mean T1% error of -0.19 (SD 0.66) % accommodating a range in mean infusion rate (MIR) of 0.21-0.49 mg x kg(-1) x h(-1). When these results were compared with our previous ones using the same hierarchical structure applied to mivacurium, less variation in the T1% error (p controller activity of these two drugs showed no significant difference (p > 0.5). However, the consistent medium coefficient variance (CV) of the MIR of both rocuronium (i.e., 36.13 (SD 9.35) %) and mivacurium (i.e., 34.03 (SD 10.76) %) indicated a good controller activity. The results showed that a hierarchical rule-based monitoring and fuzzy logic control architecture can provide stable control
Intelligent control aspects of fuzzy logic and neural nets
Harris, C J; Brown, M
1993-01-01
With increasing demands for high precision autonomous control over wide operating envelopes, conventional control engineering approaches are unable to adequately deal with system complexity, nonlinearities, spatial and temporal parameter variations, and with uncertainty. Intelligent Control or self-organising/learning control is a new emerging discipline that is designed to deal with problems. Rather than being model based, it is experiential based. Intelligent Control is the amalgam of the disciplines of Artificial Intelligence, Systems Theory and Operations Research. It uses most recent expe
Shukla, Shailja
2010-01-01
... This paper is to describe exploratory research on the design of a modular autonomous mobile robot controller. The controller incorporates a fuzzy logic [8] [9] approach for steering and speed control [37], a FL approach for ultrasound sensing and an overall expert system for guidance. The advantages of a modular system are related to portability and transportability, i.e. any vehicle can become autonomous with minimal modifications. A mobile robot test bed has been constructed in university of Cincinnati using a golf cart base. This cart has full speed control with guidance provided by a vision system and obstacle avoidance using ultrasonic sensors. The speed and steering fuzzy logic controller is supervised through a multi-axis motion controller. The obstacle avoidance system is based on a microcontroller interfaced with ultrasonic transducers. This micro-controller independently handles all timing and distance calculations and sends distance information back to the fuzzy logic controller via the serial ...
2005-01-01
A new all-electronic Particle Image Velocimetry technique that can efficiently map high speed gas flows has been developed in-house at the NASA Lewis Research Center. Particle Image Velocimetry is an optical technique for measuring the instantaneous two component velocity field across a planar region of a seeded flow field. A pulsed laser light sheet is used to illuminate the seed particles entrained in the flow field at two instances in time. One or more charged coupled device (CCD) cameras can be used to record the instantaneous positions of particles. Using the time between light sheet pulses and determining either the individual particle displacements or the average displacement of particles over a small subregion of the recorded image enables the calculation of the fluid velocity. Fuzzy logic minimizes the required operator intervention in identifying particles and computing velocity. Using two cameras that have the same view of the illumination plane yields two single exposure image frames. Two competing techniques that yield unambiguous velocity vector direction information have been widely used for reducing the single-exposure, multiple image frame data: (1) cross-correlation and (2) particle tracking. Correlation techniques yield averaged velocity estimates over subregions of the flow, whereas particle tracking techniques give individual particle velocity estimates. For the correlation technique, the correlation peak corresponding to the average displacement of particles across the subregion must be identified. Noise on the images and particle dropout result in misidentification of the true correlation peak. The subsequent velocity vector maps contain spurious vectors where the displacement peaks have been improperly identified. Typically these spurious vectors are replaced by a weighted average of the neighboring vectors, thereby decreasing the independence of the measurements. In this work, fuzzy logic techniques are used to determine the true
Fuzzy Logic Based MPPT Controller for a Small Wind Turbine System
DEFF Research Database (Denmark)
Petrila, Diana; Blaabjerg, Frede; Muntean, Nicolae
2012-01-01
This paper describes the design of a maximum power point tracking (MPPT) strategy for a variable speed, small scale, wind turbine systems based on a fuzzy logic controller (FLC). The FLC has as input variables the change in mechanical power (ΔPm), the change in rotor speed (Δω), and the sign of ΔPm...... operation. Therefore, the mechanical power (Pm) is composed of the generator mechanical (input) power (Pg) plus the dynamic power, resulting in the dynamic power versus rotating speed curve. The controller is able to track the maximum power point for changing wind conditions, and is robust with respect...
Chaotic queue-based genetic algorithm for design of a self-tuning fuzzy logic controller
Saini, Sanju; Saini, J. S.
2012-11-01
This paper employs a chaotic queue-based method using logistic equation in a non-canonical genetic algorithm for optimizing the performance of a self-tuning Fuzzy Logic Controller, used for controlling a nonlinear double-coupled system. A comparison has been made with a standard canonical genetic algorithm implemented on the same plant. It has been shown that chaotic queue-method brings an improvement in the performance of the FLC for wide range of set point changes by a more profound initial population spread in the search space.
Motion Control with Fuzzy Logic in an High Speed PLC System
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Ovidiu Neamtu
2008-05-01
Full Text Available The paper presents a new strategy of makingsoftware modules with fuzzy control. It is the best solutionfor implementing complex applications. Dynamic controltoday takes place in discrete time and discrete values.Concurrently, it is desirable that the discrete values are asclose as possible to the continuous values. This needs A/Dand D/A converters with high resolutions (up to 16-bitand support of floating point operations in controllers.This approach forced slow migration from MCU(Microcontroller unit, to DSP (Digital Signal Processor,to CPLD (Complex Programmable Logic Device andFPGA (Field Programmable Gate Array.
Fuzzy logic control of air-conditioning system in residential buildings
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Abdel-Hamid Attia
2015-09-01
Full Text Available There has been a rising concern in reducing the energy consumption in building. Heating ventilation and air condition system is the biggest consumer of energy in building. In this study, fuzzy logic control of the air conditioning system of building for efficient energy operation and comfortable environment is investigated. A theoretical model of the fan coil unit (FCU and the heat transfer between air and coolant fluid is derived. The controlled variables are the room temperature and relative humidity and control consequents are the percentage of chilled and hot water flow rates at summer and the percentage of hot water and steam injected flow rates at winter. A computer simulation has been conducted and fuzzy control results are compared with that of conventional Proportional-Integral-Derivative control. It was found that the proposed control strategy satisfies the space load and at the same time to achieve the comfort zone, as defined by the ASHRAE code. Meanwhile PID control fails to adjust the room temperature at part-load operations. It has been demonstrated that fuzzy controller operation is more efficient and consumes less energy than PID control.
An experiment-based comparative study of fuzzy logic control
Berenji, Hamid R.; Chen, Yung-Yaw; Lee, Chuen-Chein; Murugesan, S.; Jang, Jyh-Shing
1989-01-01
An approach is presented to the control of a dynamic physical system through the use of approximate reasoning. The approach has been implemented in a program named POLE, and the authors have successfully built a prototype hardware system to solve the cartpole balancing problem in real-time. The approach provides a complementary alternative to the conventional analytical control methodology and is of substantial use when a precise mathematical model of the process being controlled is not available. A set of criteria for comparing controllers based on approximate reasoning and those based on conventional control schemes is furnished.
FPA Tuned Fuzzy Logic Controlled Synchronous Buck Converter for a Wave/SC Energy System
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SAHIN, E.
2017-02-01
Full Text Available This paper presents a flower pollination algorithm (FPA tuned fuzzy logic controlled (FLC synchronous buck converter (SBC for an integrated wave/ supercapacitor (SC hybrid energy system. In order to compensate the irregular wave effects on electrical side of the wave energy converter (WEC, a SC unit charged by solar panels is connected in parallel to the WEC system and a SBC is controlled to provide more reliable and stable voltage to the DC load. In order to test the performance of the designed FLC, a classical proportional-integral-derivative (PID controller is also employed. Both of the controllers are optimized by FPA which is a pretty new optimization algorithm and a well-known optimization algorithm of which particle swarm optimization (PSO to minimize the integral of time weighted absolute error (ITAE performance index. Also, the other error-based objective functions are considered. The entire energy system and controllers are developed in Matlab/Simulink and realized experimentally. Real time applications are done through DS1104 Controller Board. The simulation and experimental results show that FPA tuned fuzzy logic controller provides lower value performance indices than conventional PID controller by reducing output voltage sags and swells of the wave/SC energy system.
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Mohit Jha,
2014-06-01
Full Text Available During the past several years fuzzy logic control has swell from one of the major active and profitable areas for research in the application of fuzzy set, especially in the zone of industrial process which do not lead themselves to control conventional methods because of lack of quantitative data regarding the input-output relations. Fuzzy control is based on fuzzy logic- a logical system which is much closer in spirit to human thinking and natural language than conventional logical systems. The fuzzy logic controller based on fuzzy logic provides a means of converting a linguistic control strategy based on expert knowledge into an automatic control strategy. As in Fuzzy logic traffic controller, the need arises for simulating and optimizing traffic control algorithms to better accommodate this increasing demand. Fuzzy optimization deals with finding the values of input parameters of a complex simulated system which result in desired output. This paper presents a MATLAB simulation of fuzzy logic traffic interval type II controller for controlling flow of traffic in multilane paths. This controller is based on the waiting time and queue length of vehicles at present green phase and vehicles queue lengths at the other lanes. The controller controls the traffic light timings and phase difference to ascertain sebaceous flow of traffic with least waiting time and queue length. In this paper, the multilane model used consists of two alleyways in each approach.
Fuzzy-Logic Subsumption Controller for Home Energy Management Systems
Energy Technology Data Exchange (ETDEWEB)
Ainsworth, Nathan; Johnson, Brian; Lundstrom, Blake
2015-10-06
Home Energy Management Systems (HEMS) are controllers that manage and coordinate the generation, storage, and loads in a home. These controllers are increasingly necessary to ensure that increasing penetrations of distributed energy resources are used effectively and do not disrupt the operation of the grid. In this paper, we propose a novel approach to HEMS design based on behavioral control methods, which do not require accurate models or predictions and are very responsive to changing conditions. We develop a proof-of-concept behavioral HEMS controller and show by simulation on an example home energy system that it capable of making context-dependent tradeoffs between goals under challenging conditions.
A fuzzy logic approach to control anaerobic digestion
Domnanovich, A.M.; Strik, D.P.B.T.B.; Pfeiffer, B.; Karlovits, M.; Zani, L.; Braun, R.; Holubar, P.
2003-01-01
One of the goals of the EU-Project AMONCO (Advanced Prediction, Monitoring and Controlling of Anaerobic Digestion Process Behaviour towards Biogas Usage in Fuel Cells) is to create a control tool for the anaerobic digestion process, which predicts the volumetric organic loading rate (Bv) for the nex
A fuzzy logic approach to control anaerobic digestion
Domnanovich, A.M.; Strik, D.P.B.T.B.; Pfeiffer, B.; Karlovits, M.; Zani, L.; Braun, R.; Holubar, P.
2003-01-01
One of the goals of the EU-Project AMONCO (Advanced Prediction, Monitoring and Controlling of Anaerobic Digestion Process Behaviour towards Biogas Usage in Fuel Cells) is to create a control tool for the anaerobic digestion process, which predicts the volumetric organic loading rate (Bv) for the nex
A fuzzy logic approach to control anaerobic digestion
Domnanovich, A.M.; Strik, D.P.B.T.B.; Pfeiffer, B.; Karlovits, M.; Zani, L.; Braun, R.; Holubar, P.
2003-01-01
One of the goals of the EU-Project AMONCO (Advanced Prediction, Monitoring and Controlling of Anaerobic Digestion Process Behaviour towards Biogas Usage in Fuel Cells) is to create a control tool for the anaerobic digestion process, which predicts the volumetric organic loading rate (Bv) for the
STATCOM Stabilizer based on Fuzzy Logic Control for Damping Power Oscillation
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Prechanon Kumkratug
2011-01-01
Full Text Available Problem statement: In power systems, there exists a continuous challenge to improve dynamic performance of power system. Approach: Static Synchronous Compensator (STATCOM is a power electronic based device that has the capability of controlling the power flow through a line. This study applies the Static Synchronous Compensator (STATCOM to control the power flow during dynamic period. To verify the effect of the STATCOM on dynamic performance, the mathematical model and control strategy of a STATCOM was needed to be presented. The converters of STATCOM were represented by variable voltage source with associate transformer leakage reactance and the voltage source and the reactance were transformed into current injection. The current injection model of STATCOM was modeled into power flow equation and thus it was used to determine control strategy. This study applies the fuzzy logic control to determine the control strategy of STATCOM. The swing curves of the three phase faulted power system without and with a STATCOM was tested and compared in various cases. Results: The swing curve of the system with STATCOM based fuzzy logic control had the less amplitude during the dynamic period. Conclusion: STATCOM can improve the dynamic performance of the system after disturbance.
Buck DC DC converter using fuzzy logic control for no linear load
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Rubén Darío Bonilla Isaza
2016-06-01
Method: Through Simulink MATLAB was built a DC-DC converter of closed loop, which is placed in series with a controller based on fuzzy logic. The control inputs are the voltage signal and its derivative, and the output is a constant value, which tunes the duty cycle of a pulse modulator (PWM. This adjust the output of voltage of the controller according to a desired reference. The fuzzy controller was built with membership functions in which linguistic variables that explain when a value of output of voltage must be corrected and when the voltage variation is out of the established ranges between -1 and 1 percent of allowable variation were integrated. Results: To evaluate the performance of this type of control compared to a DC-DC converter with control of closed loop of unity gain, obtaining a 40% improvement in the integral of area regarding the fuzzy controller, with a stabilization time of 0.01s. In non-linear loads, there are random phenomena or own unwanted effects of resonance circuit, then was emulated by interrupting cycles of a time-controlled switch.
Priority-based queuing and transmission rate management using a fuzzy logic controller in WSNs
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Imen Bouazzi
2017-06-01
Full Text Available Wireless sensor networks (WSNs operate under challenging conditions, such as maintaining message latency and the reliability of data transmission and maximizing the battery life of sensor nodes. The aim of this study is to propose a fuzzy logic algorithm for solving these issues, which are difficult to address with traditional techniques. The idea, in this study, is to employ a fuzzy logic scheme to optimize energy consumption and minimize packet drops. We demonstrated how fuzzy logic can be used to tackle this specific communication problem with minimal computational complexity. In this context, the implementation of a fuzzy logic in the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA mechanism is achieved through filling the queue length and the traffic rate at each node. Through simulations, we show that our proposed technique has a better performance in terms of energy consumption compared to the basic implementation of CSMA/CA.
Directory of Open Access Journals (Sweden)
C. Boldisor
2009-12-01
Full Text Available A self-learning based methodology for building the rule-base of a fuzzy logic controller (FLC is presented and verified, aiming to engage intelligent characteristics to a fuzzy logic control systems. The methodology is a simplified version of those presented in today literature. Some aspects are intentionally ignored since it rarely appears in control system engineering and a SISO process is considered here. The fuzzy inference system obtained is a table-based Sugeno-Takagi type. System’s desired performance is defined by a reference model and rules are extracted from recorded data, after the correct control actions are learned. The presented algorithm is tested in constructing the rule-base of a fuzzy controller for a DC drive application. System’s performances and method’s viability are analyzed.
Adaptive Interval Type-2 Fuzzy Logic Control for PMSM Drives with a Modified Reference Frame
Chaoui, Hicham
2017-01-10
In this paper, an adaptive interval type-2 fuzzy logic control scheme is proposed for high-performance permanent magnet synchronous machine drives. This strategy combines the power of type-2 fuzzy logic systems with the adaptive control theory to achieve accurate tracking and robustness to higher uncertainties. Unlike other controllers, the proposed strategy does not require electrical transducers and hence, no explicit currents loop regulation is needed, which yields a simplified control scheme. But, this limits the machine\\'s operation range since it results in a higher energy consumption. Therefore, a modified reference frame is also proposed in this paper to decrease the machine\\'s consumption. To better assess the performance of the new reference frame, comparison against its original counterpart is carried-out under the same conditions. Moreover, the stability of the closed-loop control scheme is guaranteed by a Lyapunov theorem. Simulation and experimental results for numerous situations highlight the effectiveness of the proposed controller in standstill, transient, and steady-state conditions.
Expert system for fault diagnosis in process control valves using fuzzy-logic
Energy Technology Data Exchange (ETDEWEB)
Carneiro, Alvaro L.G., E-mail: carneiro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Porto Junior, Almir C.S., E-mail: almir@ctmsp.mar.mil.br [Centro Tecnologico da Marinha em Sao Paulo (CIANA/CTMSP), Ipero, SP (Brazil). Centro de Instrucao e Adestramento Nuclear de ARAMAR
2013-07-01
The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a
Fuzzy logic based feedback control system for laser beam pointing stabilization.
Singh, Ranjeet; Patel, Kiran; Govindarajan, J; Kumar, Ajai
2010-09-20
This paper reports a fuzzy logic based feedback control system for beam pointing stabilization of a high-power nanosecond Nd:YAG laser operating at 30 Hz. This is achieved by generating the correcting signal for each consequent pulse from the error in the pointing position of the previous laser pulse. We have successfully achieved a reduction of beam position fluctuation from ±60 to ±5.0 μrad without the focusing optics and ±0.9 μrad with focusing optics.
Power-Constrained Fuzzy Logic Control of Video Streaming over a Wireless Interconnect
Directory of Open Access Journals (Sweden)
Mohammed Ghanbari
2008-06-01
Full Text Available Wireless communication of video, with Bluetooth as an example, represents a compromise between channel conditions, display and decode deadlines, and energy constraints. This paper proposes fuzzy logic control (FLC of automatic repeat request (ARQ as a way of reconciling these factors, with a 40% saving in power in the worst channel conditions from economizing on transmissions when channel errors occur. Whatever the channel conditions are, FLC is shown to outperform the default Bluetooth scheme and an alternative Bluetooth-adaptive ARQ scheme in terms of reduced packet loss and delay, as well as improved video quality.
Assessment of Benefits and Drawbacks of Using Fuzzy Logic, Especially in Fire Control Systems
1994-03-01
Netherlands, June 1991 [2] ’Technologieverkenning Vage Logica ’ (Dutch), Stam Tijdschriften, The Netherlands, April 1992 [3] ’Fuzzy Logic; vage logica voor...1991 [14] ’An autopilot for ships designed with fuzzy sets’,Proceedings of 5th IFAC/IFIP Int. Conf. on Digital Computer Applications to Process
Robust fuzzy logic stabilization with disturbance elimination.
Danapalasingam, Kumeresan A
2014-01-01
A robust fuzzy logic controller is proposed for stabilization and disturbance rejection in nonlinear control systems of a particular type. The dynamic feedback controller is designed as a combination of a control law that compensates for nonlinear terms in a control system and a dynamic fuzzy logic controller that addresses unknown model uncertainties and an unmeasured disturbance. Since it is challenging to derive a highly accurate mathematical model, the proposed controller requires only nominal functions of a control system. In this paper, a mathematical derivation is carried out to prove that the controller is able to achieve asymptotic stability by processing state measurements. Robustness here refers to the ability of the controller to asymptotically steer the state vector towards the origin in the presence of model uncertainties and a disturbance input. Simulation results of the robust fuzzy logic controller application in a magnetic levitation system demonstrate the feasibility of the control design.
Fuzzy Logic Controller Stability Analysis Using a Satisfiability Modulo Theories Approach
Arnett, Timothy; Cook, Brandon; Clark, Matthew A.; Rattan, Kuldip
2017-01-01
While many widely accepted methods and techniques exist for validation and verification of traditional controllers, at this time no solutions have been accepted for Fuzzy Logic Controllers (FLCs). Due to the highly nonlinear nature of such systems, and the fact that developing a valid FLC does not require a mathematical model of the system, it is quite difficult to use conventional techniques to prove controller stability. Since safety-critical systems must be tested and verified to work as expected for all possible circumstances, the fact that FLC controllers cannot be tested to achieve such requirements poses limitations on the applications for such technology. Therefore, alternative methods for verification and validation of FLCs needs to be explored. In this study, a novel approach using formal verification methods to ensure the stability of a FLC is proposed. Main research challenges include specification of requirements for a complex system, conversion of a traditional FLC to a piecewise polynomial representation, and using a formal verification tool in a nonlinear solution space. Using the proposed architecture, the Fuzzy Logic Controller was found to always generate negative feedback, but inconclusive for Lyapunov stability.
Design and Implementation of an Optimal Fuzzy Logic Controller Using Genetic Algorithm
Directory of Open Access Journals (Sweden)
S. Khan
2008-01-01
Full Text Available All control systems suffer from problems related to undesirable overshoot, longer settling times and vibrations while going form one state to another state. Most of relevant techniques had been in the form of suggesting modification and improvement in the instrumentation or interfacing part of the control system and the results reported, remain suffering from shortcomings related to hardware parameter dependence and maintenance and operational complexities. Present study was based on a software approach which was focusing on an algorithmic approach for programming a PIC16F877A microcontroller, for eliminating altogether the parametric dependence issues while adding the benefits of easier modification to suit a given control system to changing operational conditions. Said approach was first simulated using MATLAB/SIMULINK using the techniques of Proportional Derivative Fuzzy Logic Controller (PD-FLC whose membership function, fuzzy logic rules and scaling gains were optimized by the genetic algorithm technique. Simulated results were verified by programming the PIC16F877A microcontroller with the algorithm and using it on a temperature control system where a fan was regulated in response to variations in the ambient system temperature. Resulting tabulated performance indices showed a considerable improvement in rising and settling time besides reducing overshoot and steady state error.
Directory of Open Access Journals (Sweden)
Dian Pancawati
2016-07-01
Full Text Available One solution to solve limited agricultural land is applying hydroponics Nutrient Film Technique (NFT. The advantage of NFT is using water circulated as a growing medium in order to obtain water, nutrients and oxygen to accelerate the growth of plants with good results. The most important parameter is the pH of nutrients. This article discusses how to design an automatic nutritional pH control system by implementing the method of Fuzzy Logic Controller. The control system use Arduino Mega2560, Analog pH Meter Kit as input, and the solenoid valve as actuators. The best response of the implementation of Fuzzy Logic Controller with the system which has 25 rules. The response shows that the system has in 1200 millisecond rise time and the steady state in 5530 milliseconds to increase the pH. While to decrease the pH system has response of rise time at 2000 milliseconds and steady state at the time of 3000 milliseconds. The system is able to maintain the pH at 5.5, with the result of the growth of lettuce as high as 20 cm and seven leaves for 54 days.
Directory of Open Access Journals (Sweden)
K.Ramalingeswara Rao
2014-07-01
Full Text Available In this paper, the design of combined operation of UPQC and PV-ARRAY is designed. The proposed system is composed of series and shunt inverters connected back to back by a dc-link to which pv-array is connected. This system is able to compensate voltage and current related problems both in inter-connected mode and islanding mode by injecting active power to grid. The fundamental aspect is that the power electronic devices (PE and sensitive equipments (SE are normally designed to work in non-polluted power system, so they would suffer from malfunctions when supply voltage is not pure sinusoidal. Thus this proposed operating strategy with flexible operation mode improves the power quality of the grid system combining photovoltaic array with a control of unified power quality conditioner. Pulse Width Modulation (PWM is used in both three phase four leg inverters. A Proportional Integral (PI and Fuzzy Logic Controllers are used for power quality improvement by reducing the distortions in the output power. The simulated results were compared among the two controller’s strategies With pi controller and fuzzy logic controller
Fuzzy logic and neural network technologies
Villarreal, James A.; Lea, Robert N.; Savely, Robert T.
1992-01-01
Applications of fuzzy logic technologies in NASA projects are reviewed to examine their advantages in the development of neural networks for aerospace and commercial expert systems and control. Examples of fuzzy-logic applications include a 6-DOF spacecraft controller, collision-avoidance systems, and reinforcement-learning techniques. The commercial applications examined include a fuzzy autofocusing system, an air conditioning system, and an automobile transmission application. The practical use of fuzzy logic is set in the theoretical context of artificial neural systems (ANSs) to give the background for an overview of ANS research programs at NASA. The research and application programs include the Network Execution and Training Simulator and faster training algorithms such as the Difference Optimized Training Scheme. The networks are well suited for pattern-recognition applications such as predicting sunspots, controlling posture maintenance, and conducting adaptive diagnoses.
Self-tuning fuzzy logic control of a switched reluctance generator for wind energy applications
DEFF Research Database (Denmark)
Park, Kiwoo; Chen, Zhe
2012-01-01
This paper presents a new self-tuning fuzzy logic control (FLC) based speed controller of a switched reluctance generator (SRG) for wind power applications. Due to its doubly salient structure and magnetic saturation, the SRG possesses an inherent characteristic of strong nonlinearity. In addition...... has better adaptability than a traditional controller so that it provides better performance over a wide range of operating conditions. The current controller is basically a hysteresis controller which controls the phase current in accordance with the turn-on and turn-off angles. Simulation results......, its flux linkage, inductance, and torque are highly coupled with the rotor position and phase current. All these features make the application of traditional controllers to the SRG difficult and unsatisfactory. The proposed controller consists of three main parts: turn-on and turn-off angle...
Fuzzy Logic Control Based QoS Management in Wireless Sensor/Actuator Networks
Xia, Feng; Sun, Youxian; Tian, Yu-Chu
2008-01-01
Wireless sensor/actuator networks (WSANs) are emerging rapidly as a new generation of sensor networks. Despite intensive research in wireless sensor networks (WSNs), limited work has been found in the open literature in the field of WSANs. In particular, quality-of-service (QoS) management in WSANs remains an important issue yet to be investigated. As an attempt in this direction, this paper develops a fuzzy logic control based QoS management (FLC-QM) scheme for WSANs with constrained resources and in dynamic and unpredictable environments. Taking advantage of the feedback control technology, this scheme deals with the impact of unpredictable changes in traffic load on the QoS of WSANs. It utilizes a fuzzy logic controller inside each source sensor node to adapt sampling period to the deadline miss ratio associated with data transmission from the sensor to the actuator. The deadline miss ratio is maintained at a pre-determined desired level so that the required QoS can be achieved. The FLC-QM has the advantag...
A Fuzzy Logic Based Power Control for Wideband Code Division Multiple Access Wireless Networks
Directory of Open Access Journals (Sweden)
T. Ravichandran
2012-01-01
Full Text Available Problem statement: Resource management is one of the most important engineering issues in 3G systems where multiple traffic classes are supported each being characterized by its required Quality of Service (QoS parameters. Call Admission Control (CAC is one of the resource management functions, which regulates network access to ensure QoS provisioning. Efficient CAC is necessary for the QoS provisioning in WCDMA environment. The effective functioning of WCDMA systems is influenced by the power control utility. Approach: In this study, we propose to design a fuzzy logic based power control for Wideband Code Division Multiple Access Wireless Networks. This proposed technique is aimed at multiple services like voice, video and data for multiclass users. The fuzzy logic technique is used to estimate the optimal admissible users group inclusive of optimum transmitting power level. This technique reduces the interference level and call rejection rate. Results: By simulation results, we demonstrate that the proposed technique achieve reduced energy consumption for a cell with increased throughput. Conclusion: The proposed technique minimizes the power consumption and call rejection rate.
Gas Turbine Engine Control Design Using Fuzzy Logic and Neural Networks
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M. Bazazzadeh
2011-01-01
Full Text Available This paper presents a successful approach in designing a Fuzzy Logic Controller (FLC for a specific Jet Engine. At first, a suitable mathematical model for the jet engine is presented by the aid of SIMULINK. Then by applying different reasonable fuel flow functions via the engine model, some important engine-transient operation parameters (such as thrust, compressor surge margin, turbine inlet temperature, etc. are obtained. These parameters provide a precious database, which train a neural network. At the second step, by designing and training a feedforward multilayer perceptron neural network according to this available database; a number of different reasonable fuel flow functions for various engine acceleration operations are determined. These functions are used to define the desired fuzzy fuel functions. Indeed, the neural networks are used as an effective method to define the optimum fuzzy fuel functions. At the next step, we propose a FLC by using the engine simulation model and the neural network results. The proposed control scheme is proved by computer simulation using the designed engine model. The simulation results of engine model with FLC illustrate that the proposed controller achieves the desired performance and stability.
DEFF Research Database (Denmark)
Mauricio Iglesias, Miguel; Vangsgaard, Anna Katrine; Gernaey, Krist
2013-01-01
This contribution explores the use of diagnosis and control modules based on fuzzy set theory and logic for bioreactor monitoring and control. With this aim, two independent modules were used jointly to carry out first the diagnosis of the state of the system and then use transfer this information...... to control the reactor. The separation in diagnosis and control allowed a more intuitive design of the membership functions and the production rules. Hence, the resulting diagnosis-control module is simple to tune, update and maintain while providing a good control performance. In particular the diagnosis-control...... system was designed for a complete autotrophic nitrogen removal process. The whole module is evaluated by dynamic simulation. Additionally, the diagnosis tool was demonstrated by analysis 100 days of experimental data....
A Fuzzy-Logic-Based Controller for Three-Phase PWM Rectifier With Unity Power Factor Operation
Directory of Open Access Journals (Sweden)
A. Bouafia
2008-03-01
Full Text Available In this paper, direct power control (DPC of three-phase PWM rectifiers based on fuzzy logic controller is presented, without line voltage sensors. The control technique is built upon the ideas of the well known direct torque control (DTC for induction motors. The instantaneous active and reactive powers, directly controlled by selecting the optimum state of the converter, are used as the PWM control variables instead of the phase line currents being used. The proposed fuzzy logic controller presents the advantage to be based on linguistic description and does not require a mathematical model of the system. The controller ensures a good regulation of the output voltage, and guarantees the power factor close to one. The simulation results show that the designed fuzzy controller has a good dynamic behavior, a good rejection of impact load disturbance, and is very robust.
DEFF Research Database (Denmark)
Dotoli, M.; Jantzen, Jan
1999-01-01
The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control......, and to show how to apply fuzzy logic in automatic control. The tutorial is distance learning, where students interact one-to-one with the teacher using e-mail....
DEFF Research Database (Denmark)
Dotoli, M.; Jantzen, Jan
1999-01-01
The tutorial concerns automatic control of an inverted pendulum, especially rule based control by means of fuzzy logic. A ball balancer, implemented in a software simulator in Matlab, is used as a practical case study. The objectives of the tutorial are to teach the basics of fuzzy control, and t......, and to show how to apply fuzzy logic in automatic control. The tutorial is distance learning, where students interact one-to-one with the teacher using e-mail....
Fuzzy logic control of stand-alone photovoltaic system with battery storage
Lalouni, S.; Rekioua, D.; Rekioua, T.; Matagne, E.
Photovoltaic energy has nowadays an increased importance in electrical power applications, since it is considered as an essentially inexhaustible and broadly available energy resource. However, the output power provided via the photovoltaic conversion process depends on solar irradiation and temperature. Therefore, to maximize the efficiency of the photovoltaic energy system, it is necessary to track the maximum power point of the PV array. The present paper proposes a maximum power point tracker (MPPT) method, based on fuzzy logic controller (FLC), applied to a stand-alone photovoltaic system. It uses a sampling measure of the PV array power and voltage then determines an optimal increment required to have the optimal operating voltage which permits maximum power tracking. This method carries high accuracy around the optimum point when compared to the conventional one. The stand-alone photovoltaic system used in this paper includes two bi-directional DC/DC converters and a lead-acid battery bank to overcome the scare periods. One converter works as an MPP tracker, while the other regulates the batteries state of charge and compensates the power deficit to provide a continuous delivery of energy to the load. The Obtained simulation results show the effectiveness of the proposed fuzzy logic controller.
Zhang, Xian-Xia; Jiang, Ye; Li, Han-Xiong; Li, Shao-Yuan
2013-10-01
A data-driven 3-D fuzzy-logic controller (3-D FLC) design methodology based on support vector regression (SVR) learning is developed for nonlinear spatially distributed dynamic systems. Initially, the spatial information expression and processing as well as the fuzzy linguistic expression and rule inference of a 3-D FLC are integrated into spatial fuzzy basis functions (SFBFs), and then the 3-D FLC can be depicted by a three-layer network structure. By relating SFBFs of the 3-D FLC directly to spatial kernel functions of an SVR, an equivalence relationship of the 3-D FLC and the SVR is established, which means that the 3-D FLC can be designed with the help of the SVR learning. Subsequently, for an easy implementation, a systematic SVR learning-based 3-D FLC design scheme is formulated. In addition, the universal approximation capability of the proposed 3-D FLC is presented. Finally, the control of a nonlinear catalytic packed-bed reactor is considered as an application to demonstrate the effectiveness of the proposed 3-D FLC.
Application of fuzzy logic to the control of wind tunnel settling chamber temperature
Gwaltney, David A.; Humphreys, Gregory L.
1994-01-01
The application of Fuzzy Logic Controllers (FLC's) to the control of nonlinear processes, typically controlled by a human operator, is a topic of much study. Recent application of a microprocessor-based FLC to the control of temperature processes in several wind tunnels has proven to be very successful. The control of temperature processes in the wind tunnels requires the ability to monitor temperature feedback from several points and to accommodate varying operating conditions in the wind tunnels. The FLC has an intuitive and easily configurable structure which incorporates the flexibility required to have such an ability. The design and implementation of the FLC is presented along with process data from the wind tunnels under automatic control.
A fuzzy-logic-based controller for methane production in anaerobic fixed-film reactors.
Robles, A; Latrille, E; Ruano, M V; Steyer, J P
2017-01-01
The main objective of this work was to develop a controller for biogas production in continuous anaerobic fixed-bed reactors, which used effluent total volatile fatty acids (VFA) concentration as control input in order to prevent process acidification at closed loop. To this aim, a fuzzy-logic-based control system was developed, tuned and validated in an anaerobic fixed-bed reactor at pilot scale that treated industrial winery wastewater. The proposed controller varied the flow rate of wastewater entering the system as a function of the gaseous outflow rate of methane and VFA concentration. Simulation results show that the proposed controller is capable to achieve great process stability even when operating at high VFA concentrations. Pilot results showed the potential of this control approach to maintain the process working properly under similar conditions to the ones expected at full-scale plants.
Design of a fuzzy logic controller for a jet engine fuel system
Energy Technology Data Exchange (ETDEWEB)
Zilouchian, A. [Florida Atlantic Univ., Dept. of Electrical Engineering, Boca Raton, FL (United States); Juliano, M.; Healy, T.; Davis, J. [Florida Atlantic Univ., Dept. of Mechanical Engineering, Boca Raton, FL (United States)
2000-08-01
The design, implementation and evaluation of two types of fuzzy logic controllers (FLC) are presented. The system under consideration is the control of fuel delivery in a jet engine test bench. Two methods of designing FLCs were experimented with. The first method included the development of a tool that inputs the rules, membership functions, and outputs the appropriate consequences. The second method was based on bivariate curve development and scaling. The evaluations of the proposed controllers were performed with an existing proportional-integral (PI) controller. Both of the design methodologies were proven to be superior in comparison with the conventional controller currently utilised for the control of combustion pressure on jet engines. (Author)
Fuzzy logic membership implementation using optical hardware components
Moniem, T. A.; Saleh, M. H.
2012-10-01
Intelligent control techniques consist of knowledge-based expert or fuzzy logic control. One obvious drawback in many such applications is that fuzzy logic memberships are implemented at the lowest level. In high-bandwidth processes, this form of fuzzy logic membership implementation would require high speed and accuracy in the presence of strong nonlinearities and dynamic coupling. This paper presents a novel methodology called the Opto-fuzzy method to design a fuzzy logic membership using an optical hardware component. The proposed scheme is applied to triangular-shaped and half trapezoidal-shaped membership functions.
Corbett, Dan; Zwaag, van der Berend Jan; Antoniou, Grigoris; Slaney, John
1998-01-01
We have designed a fuzzy logic wheelchair controller to minimise the effect of Multiple Sclerosis hand tremors on a wheelchair joystick controller. The aim is to give people with Multiple Sclerosis better control of an electric wheelchair by removing tremors from the joystick signal. This has been a
PERFORMANCE EVALUATION OF HYBRID FUZZY LOGIC CONTROLLER FOR BRUSHLESS DC MOTOR DRIVE
Directory of Open Access Journals (Sweden)
C. SUBBA RAMI REDDY
2011-06-01
Full Text Available This paper presents Hybrid fuzzy logic controller (HFLC for the well developed and sophisticated simulation model of Brush less DC (BLDC motor drive using MATLAB. The developed simulation model has been examined by the PID controller and HFLC. The performance of the controllers is evaluated more precisely from various simulation studies for variations in the load torque and speed of BLDC motor drive. A performance comparison of two controllers is also carried out by taking various performance measures such as settling time, steady state error, peak overshoot, the integral of the absolute value of the error (IAE and the integral of the time-weighted squared error (ITSE. The results confirm that the developed simulation model is very convenient for the precise evaluation of performance and the HFLC shows improved performance over the PID controller in terms of disturbance rejection or parameter variation.
Fuzzy Logic Control Based QoS Management in Wireless Sensor/Actuator Networks
Directory of Open Access Journals (Sweden)
Yu-Chu Tian
2007-12-01
Full Text Available Wireless sensor/actuator networks (WSANs are emerging rapidly as a newgeneration of sensor networks. Despite intensive research in wireless sensor networks(WSNs, limited work has been found in the open literature in the field of WSANs. Inparticular, quality-of-service (QoS management in WSANs remains an important issue yetto be investigated. As an attempt in this direction, this paper develops a fuzzy logic controlbased QoS management (FLC-QM scheme for WSANs with constrained resources and indynamic and unpredictable environments. Taking advantage of the feedback controltechnology, this scheme deals with the impact of unpredictable changes in traffic load on theQoS of WSANs. It utilizes a fuzzy logic controller inside each source sensor node to adaptsampling period to the deadline miss ratio associated with data transmission from the sensorto the actuator. The deadline miss ratio is maintained at a pre-determined desired level sothat the required QoS can be achieved. The FLC-QM has the advantages of generality,scalability, and simplicity. Simulation results show that the FLC-QM can provide WSANswith QoS support.
Fuzzy Logic Control of Adaptive ARQ for Video Distribution over a Bluetooth Wireless Link
Directory of Open Access Journals (Sweden)
R. Razavi
2007-01-01
Full Text Available Bluetooth's default automatic repeat request (ARQ scheme is not suited to video distribution resulting in missed display and decoded deadlines. Adaptive ARQ with active discard of expired packets from the send buffer is an alternative approach. However, even with the addition of cross-layer adaptation to picture-type packet importance, ARQ is not ideal in conditions of a deteriorating RF channel. The paper presents fuzzy logic control of ARQ, based on send buffer fullness and the head-of-line packet's deadline. The advantage of the fuzzy logic approach, which also scales its output according to picture type importance, is that the impact of delay can be directly introduced to the model, causing retransmissions to be reduced compared to all other schemes. The scheme considers both the delay constraints of the video stream and at the same time avoids send buffer overflow. Tests explore a variety of Bluetooth send buffer sizes and channel conditions. For adverse channel conditions and buffer size, the tests show an improvement of at least 4 dB in video quality compared to nonfuzzy schemes. The scheme can be applied to any codec with I-, P-, and (possibly B-slices by inspection of packet headers without the need for encoder intervention.
A novel fuzzy-logic control strategy minimizing N2O emissions
DEFF Research Database (Denmark)
Boiocchi, Riccardo; Gernaey, Krist; Sin, Gürkan
2017-01-01
A novel control strategy for achieving low N2O emissions and low effluent NH4+ concentration is here proposed. The control strategy uses the measurements of ammonium and nitrate concentrations in inlet and outlet of the aerobic zone of a wastewater treatment plant to calculate a ratio indicating...... was implemented using the fuzzy logic approach. It was comprehensively tested for different model structures and different sets of model parameters with regards to its ability of mitigating N2O emissions for future applications in real wastewater treatment plants. It is concluded that the control strategy...... is useful for those plants having AOB denitrification as the main N2O producing process. However, in treatment plants having incomplete NH2OH oxidation as the main N2O producing pathway, a cascade controller configuration adapting the oxygen supply to respect only the effluent ammonium concentration limits...
Design and Construction of Intelligent Traffic Light Control System Using Fuzzy Logic
Lin, Htin; Aye, Khin Muyar; Tun, Hla Myo; Theingi, Naing, Zaw Min
2008-10-01
Vehicular travel is increasing throughout the world, particularly in large urban areas. Therefore the need arises for simulation and optimizing traffic control algorithms to better accommodate this increasing demand. This paper presents a microcontroller simulation of intelligent traffic light controller using fuzzy logic that is used to change the traffic signal cycles adaptively at a two-way intersection. This paper is an attempt to design an intelligent traffic light control systems using microcontrollers such as PIC 16F84A and PIC 16F877A. And then traffic signal can be controlled depending upon the densities of cars behind green and red lights of the two-way intersection by using sensors and detectors circuits.
Integration of Wind Energy and Solar Energy in a DC Microgrid Using Fuzzy Logic Control
Jajula, Harshavardhan
The significance of wind and solar energy as renewable sources for electric power generation has been rapidly increasing. The current project presents a model subsystem that integrates wind and solar energy sources to power a Direct Current (DC) microgrid, along with a backup Battery Energy Storage System (BESS) and a supercapacitor. The microgrid is used for the charging of electric vehicles locally, to supply power to the main grid, and to meet other local demands. The model compares the effectiveness of two control methods: Fuzzy Logic Control (FLC) and Proportional plus Integral control (PI). Simulation results show that the FLC is more efficient in regulating the grid power and DC bus voltage, and at the same time, it is simpler to implement, as compared to the PI controller.
Directory of Open Access Journals (Sweden)
Yeh-Hsiang Ho
2013-07-01
Full Text Available Lithium ion (Li-ion batteries have been widely used in various kinds of applications, including consumer electronics, green energy systems and electrical vehicles. Since the charging method has a significant influence on the performance and lifetime of Li-ion batteries, an intelligent charging algorithm which can properly determine the charging current is essential. In this study, a fuzzy-logic-control-based (FLC-based five-stage Li-ion battery charger is proposed. The proposed charger takes the temperature rise and the gradient of temperature rise of battery into account, and adjusts the charging current accordingly. To further improve the performance of the proposed FLC, the fuzzy-based Taguchi method is utilized to determine the optimal output membership functions (MFs. Comparing with the conventional constant current-constant voltage (CC-CV method, the charging time, charging efficiency, average temperature rise and the obtained cycle life of the Li-ion battery are improved by about 58.3%, 1.65%, 26.7% and 59.3%, respectively.
DEFF Research Database (Denmark)
Boiocchi, Riccardo; Gernaey, Krist; Sin, Gürkan
2016-01-01
In this work, a fuzzy-logic controller for minimization of the nitrous oxide emission from wastewater treatment plants is developed and tested in a simulation environment. The controller is designed in order to maintain a balance between production and consumption of nitrite by AOB and NOB...
MPPT Based on Fuzzy Logic Controller (FLC for Photovoltaic (PV System in Solar Car
Directory of Open Access Journals (Sweden)
Seno Aji
2013-12-01
Full Text Available This paper presents a control called Maximum Power Point Tracking (MPPT for photovoltaic (PV system in a solar car. The main purpose of this system is to extracts PV power maximally while keeping small losses using a simple design of converter. Working principle of MPPT based fuzzy logic controller (MPPT-FLC is to get desirable values of reference current and voltage. MPPT-FLC compares them with the values of the PV's actual current and voltage to control duty cycle value. Then the duty cycle value is used to adjust the angle of ignition switch (MOSFET gate on the Boost converter. The proposed method was shown through simulation performed using PSIM and MATLAB software. Simulation results show that the system is able to improve the PV power extraction efficiency significantly by approximately 98% of PV’s power.
Shunt hybrid active power filter under nonideal voltage based on fuzzy logic controller
Dey, Papan; Mekhilef, Saad
2016-09-01
In this paper, a synchronous reference frame (SRF) method based on a modified phase lock loop (PLL) circuit is developed for a three-phase four-wire shunt hybrid active power filter (APF). Its performance is analysed under unbalanced grid conditions. The dominant lower order harmonics as well as reactive power can be compensated by the passive elements, whereas the active part mitigates the remaining distortions and improves the power quality. As different control methods show contradictory performance, fuzzy logic controller is considered here for DC-link voltage regulation of the inverter. Extensive simulations of the proposed technique are carried out in a MATLAB-SIMULINK environment. A laboratory prototype has been built on dSPACE1104 platform to verify the feasibility of the suggested SHAPF controller. The simulation and experimental results validate the effectiveness of the proposed technique.
Burn control of an ITER-like fusion reactor using fuzzy logic
Garcia-Amador, A. Sair; Martinell, Julio J.
2016-10-01
The fuel burn in a fusion reactor has to be kept at a nearly constant rate in order to have a steady power exhaust. Here, we develop a control system based on a fuzzy logic controller in order that adjusts external parameters to keep the plasma temperature and density at the design values of a reactor of the characteristics of ITER. The control parameters chosen are the D-T refueling rate, the auxiliary heating power and a neutral helium beam. We use a fuzzy controller of the Mamdani type that uses a number of membership functions appropriate to produce a response to parameter deviations that minimizes the response time. The inference rules are determined in a way to provide stabilization to all perturbations of the temperature, density and alpha particle fraction. The dynamical response of the reactor is simulated with a 0D model that uses confinement times provided by the ITER scaling. We show that the system is feedback stabilized for a large range of parameters around the nominal values. The recovery time after a departure from the steady values is of the order of one second. We compare the results with another control system based on neural networks that was developed previously. Funded by projects PAPIIT IN109115 and Conacyt 152905.
FUZZY LOGIC IN LEGAL EDUCATION
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Z. Gonul BALKIR
2011-04-01
Full Text Available The necessity of examination of every case within its peculiar conditions in social sciences requires different approaches complying with the spirit and nature of social sciences. Multiple realities require different and various perceptual interpretations. In modern world and social sciences, interpretation of perception of valued and multi-valued have been started to be understood by the principles of fuzziness and fuzzy logic. Having the verbally expressible degrees of truthness such as true, very true, rather true, etc. fuzzy logic provides the opportunity for the interpretation of especially complex and rather vague set of information by flexibility or equivalence of the variables’ of fuzzy limitations. The methods and principles of fuzzy logic can be benefited in examination of the methodological problems of law, especially in the applications of filling the legal loopholes arising from the ambiguities and interpretation problems in order to understand the legal rules in a more comprehensible and applicable way and the efficiency of legal implications. On the other hand, fuzzy logic can be used as a technical legal method in legal education and especially in legal case studies and legal practice applications in order to provide the perception of law as a value and the more comprehensive and more quality perception and interpretation of value of justice, which is the core value of law. In the perception of what happened as it has happened in legal relationships and formations, the understanding of social reality and sociological legal rules with multi valued sense perspective and the their applications in accordance with the fuzzy logic’s methods could create more equivalent and just results. It can be useful for the young lawyers and law students as a facilitating legal method especially in the materialization of the perception and interpretation of multi valued and variables. Using methods and principles of fuzzy logic in legal
Competencies assessment using fuzzy logic
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Matej Jevšček
2016-06-01
Full Text Available Research Question: Competencies evaluation is complex. The question is how to evaluate a competency which was assessed with 360° feedback, in one result using fuzzy logic tools so the result represents an actual competency development in an individual. Purpose: The purpose and goal of the study is to determine a possible process of competency evaluation that would enable creating a single competency assessment using fuzzy logic methods. Method: The theoretical part examines the current state and terminology of competencies and fuzzy logic. The empirical part consists of a quantitative research study. Data from the survey questionnaire was used for model testing. Results: An example of an »Initiative« competency evaluation model is created and tested in the research study. Testing confirmed that evaluation using fuzzy logic is efficient. Organization: The study directly affects the development of the HR function in organizations. It enables an easier and more oriented competency evaluation. Society: The study enables easier orientation in competencies development that can improve the social order as well as social responsibility and the environment indirectly. Originality: The study presents a new competency evaluation model using fuzzy logic. Limitations/Future Research: The study is restricted to one competency and certain assessors. Further research could explore the model with several assessors of the same rank.
Fuzzy logic of Aristotelian forms
Energy Technology Data Exchange (ETDEWEB)
Perlovsky, L.I. [Nichols Research Corp., Lexington, MA (United States)
1996-12-31
Model-based approaches to pattern recognition and machine vision have been proposed to overcome the exorbitant training requirements of earlier computational paradigms. However, uncertainties in data were found to lead to a combinatorial explosion of the computational complexity. This issue is related here to the roles of a priori knowledge vs. adaptive learning. What is the a-priori knowledge representation that supports learning? I introduce Modeling Field Theory (MFT), a model-based neural network whose adaptive learning is based on a priori models. These models combine deterministic, fuzzy, and statistical aspects to account for a priori knowledge, its fuzzy nature, and data uncertainties. In the process of learning, a priori fuzzy concepts converge to crisp or probabilistic concepts. The MFT is a convergent dynamical system of only linear computational complexity. Fuzzy logic turns out to be essential for reducing the combinatorial complexity to linear one. I will discuss the relationship of the new computational paradigm to two theories due to Aristotle: theory of Forms and logic. While theory of Forms argued that the mind cannot be based on ready-made a priori concepts, Aristotelian logic operated with just such concepts. I discuss an interpretation of MFT suggesting that its fuzzy logic, combining a-priority and adaptivity, implements Aristotelian theory of Forms (theory of mind). Thus, 2300 years after Aristotle, a logic is developed suitable for his theory of mind.
Coelho, Antonio Augusto Rodrigues
2016-01-01
This paper introduces the Fuzzy Logic Hypercube Interpolator (FLHI) and demonstrates applications in control of multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) processes with Hammerstein nonlinearities. FLHI consists of a Takagi-Sugeno fuzzy inference system where membership functions act as kernel functions of an interpolator. Conjunction of membership functions in an unitary hypercube space enables multivariable interpolation of N-dimensions. Membership functions act as interpolation kernels, such that choice of membership functions determines interpolation characteristics, allowing FLHI to behave as a nearest-neighbor, linear, cubic, spline or Lanczos interpolator, to name a few. The proposed interpolator is presented as a solution to the modeling problem of static nonlinearities since it is capable of modeling both a function and its inverse function. Three study cases from literature are presented, a single-input single-output (SISO) system, a MISO and a MIMO system. Good results are obtained regarding performance metrics such as set-point tracking, control variation and robustness. Results demonstrate applicability of the proposed method in modeling Hammerstein nonlinearities and their inverse functions for implementation of an output compensator with Model Based Predictive Control (MBPC), in particular Dynamic Matrix Control (DMC). PMID:27657723
FC/PV Fed SAF with Fuzzy Logic Control for Power Quality Enhancement
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R. Balamurugan
2015-02-01
Full Text Available In this paper, a Fuel cell (FC / Photovoltaic cell (PV/ Battery operated three phase Shunt Active power Filter (SAF is proposed for improving the power quality at the utility side. Fuzzy based instantaneous p-q theory control is proposed for SAF. This SAF consists of Voltage Source PWM Converter (VSC and a DC link capacitor supplied by a FC/PV/Battery. The filter provides harmonic mitigation with reactive power compensation and neutral compensation for loads at the Point of Common Coupling (PCC. A Single switch boost DC-DC converter connects the FC/PV/Battery with the VSC to maintain the load. The performance of the proposed SAF is tested in MATLAB / SIMULINK environment with Fuzzy logic controller (FLC. The controller maintains the DC link voltage based on the current reference generated by the p-q theory. The Hysteresis PWM current controller is employed to generate the gating pulses to the switches in VSC. The simulation results of the proposed SAF validate the effectiveness of FLC in power quality enhancement.
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Woonki Na
2017-03-01
Full Text Available This paper presents an improved maximum power point tracking (MPPT algorithm using a fuzzy logic controller (FLC in order to extract potential maximum power from photovoltaic cells. The objectives of the proposed algorithm are to improve the tracking speed, and to simultaneously solve the inherent drawbacks such as slow tracking in the conventional perturb and observe (P and O algorithm. The performances of the conventional P and O algorithm and the proposed algorithm are compared by using MATLAB/Simulink in terms of the tracking speed and steady-state oscillations. Additionally, both algorithms were experimentally validated through a digital signal processor (DSP-based controlled-boost DC-DC converter. The experimental results show that the proposed algorithm performs with a shorter tracking time, smaller output power oscillation, and higher efficiency, compared with the conventional P and O algorithm.
FUZZY LOGIC CONTROLLER OF DFIG TO RIDE THROUGH RECURRING GRID FAULTS
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Mani Kumar Gutti
2016-09-01
Full Text Available The penetration of Wind Turbine Systems (WTS is increasing in recent years. The new grid codes saying that the WTS must remain connected to utility grid at voltages below rated and also under recurring grid faults. The rotor side crowbar with vector control can ride through single grid fault. The rotor side crowbar fails to Ride Through recurring grid faults due to large electromagnetic torque fluctuations. This may affect mechanical system which leads to damage the gear box of WTS. This paper presents fuzzy logic control to investigate Doubly Fed Induction Generator (DFIG WTS to fault ride through (FRT recurring symmetrical grid faults. A rotor natural current is injected into the rotor circuit during voltage recovery under grid faults. By this the decay time of stator natural flux can be minimized. This will suppress the electromagnetic torque fluctuations and improves the mechanical system. The system is modeled by using MATLAB software.
Static Var Compensator based on Fuzzy Logic Control for Damping Power System Oscillation
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Prechanon Kumkratug
2011-01-01
Full Text Available Problem statement: The disturbance in power system is unavoidable situation. It causes in power system oscillation. Approach: This study applied the Static Var Compensator (SVC to damp power system oscillation. The fuzzy logic control is applied to determine the control strategy of SVC. The simulation results are tested on a Single Machine Infinite bus. The proposed method is equipped in sample system with disturbance. The generator rotor angle curve of the system without and with a SVC is plotted and compared. Results: It was found that the system without a SVC has high variation whereas that of the system with a SVC has much smaller variation. Conclusion: From the simulation results, the SVC can damp power system oscillation.
A Fuzzy Logic Based Supervisory Hierarchical Control Scheme for Real Time Pressure Control
Institute of Scientific and Technical Information of China (English)
N.Kanagaraj; P.Sivashanmugam; S.Paramasivam
2009-01-01
This paper describes a supervisory hierarchical fuzzy controller (SHFC) for regulating pressure in a real-time pilot pressure control system.The input scaling factor tuning of a direct expert controller is made using the error and process input parameters in a closed loop system in order to obtain better controller performance for set-point change and load disturbances.This on-line tuning method reduces operator involvement and enhances the controller performance to a wide operating range.The hierarchical control scheme consists of an intelligent upper level supervisory fuzzy controller and a lower level direct fuzzy controller.The upper level controller provides a mechanism to the main goal of the system and the lower level controller delivers the solutions to a particular situation. The control algorithm for the proposed scheme has been developed and tested using an ARM7 microcontroller-based embedded target board for a nonlinear pressure process having dead time.To demonstrate the effectiveness,the results of the proposed hierarchical controller,fuzzy controller and conventional proportional-integral (PI) controller are analyzed.The results prove that the SHFC performance is better in terms of stability and robustness than the conventional control methods.
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Marwan Rosyadi
2012-11-01
Full Text Available In this paper, a design fuzzy logic controller for a variable speed permanent magnet wind generator connected to a grid system through a LC-filter is proposed. A new current control method of grid side conversion is developed by integrating the fuzzy controller, in which both active and reactive power, delivered to a power grid system, is controlled effectively. The fuzzy logic controller is designed to adjust the gain parameters of the PI controllers under any operating conditions, so that the dynamic stability is enhanced. A new simple method, based on frequency response of the bode diagram, is proposed in the design of the fuzzy logic controller. To evaluate the controller system capabilities, simulation analyses are performed on a small wind farm model system including an induction wind generator connected to an infinite bus. The simulations have been performed using PSCAD/EMTDC. Simulation results show that the proposed control scheme is more effective for enhancing the stability of wind farms during temporary and permanent network disturbances and randomly fluctuating wind speed, compared with that of a conventional PI controller.
Fuzzy logic program at SGS-Thomson
Pagni, Andrea; Poluzzi, Rinaldo; Rizzotto, GianGuido
1993-12-01
From its conception by Professor Lotfi A. Zadeh in the early '60s, Fuzzy Logic has slowly won acceptance, first in the academic world, then in industry. Its success is mainly due to the different perspective with which problems are tackled. Thanks to Fuzzy Logic we have moved from a numerical/analytical description to a quantitative/qualitative one. It is important to stress that this different perspective not only allows us to solve analysis/control problems at lower costs but can also allow otherwise insoluble problems to be solved at acceptable costs. Of course, it must be stressed that Fuzzy Systems cannot match the computational precision of traditional techniques but seek, instead, to find acceptable solutions in shorter times. Recognizing the enormous importance of fuzzy logic in the markets of the future, SGS-THOMSON intends to produce devices belonging to a new class of machines: Fuzzy Computational Machines. For this purpose a major research project has been established considering the architectural aspects and system implications of fuzzy logic, the development of dedicated VLSI components and supporting software.
Craft, Michael J.; Buckner, Gregory D.; Anderson, Richard D.
2003-07-01
Automotive ride quality and handling performance remain challenging design tradeoffs for modern, passive automobile suspension systems. Despite extensive published research outlining the benefits of active vehicle suspensions in addressing this tradeoff, the cost and complexity of these systems frequently prohibit commercial adoption. Semi-active suspensions can provide performance benefits over passive suspensions without the cost and complexity associated with fully active systems. This paper outlines the development and experimental evaluation of a fuzzy logic control algorithm for a commercial semi-active suspension component, Carrera's MagneShockTM shock absorber. The MagneShockTM utilizes an electromagnet to change the viscosity of magnetorheological (MR) fluid, which changes the damping characteristics of the shock. Damping for each shock is controlled by manipulating the coil current using real-time algorithms. The performance capabilities of fuzzy logic control (FLC) algorithms are demonstrated through experimental evaluations on a passenger vehicle. Results show reductions of 25% or more in sprung mass absorbed power (U.S. Army 6 Watt Absorbed Power Criterion) as compared to typical passive shock absorbers over urban terrains in both simulation and experimentation. Average sprung-mass RMS accelerations were also reduced by as much as 9%, but usually with an increase in total suspension travel over the passive systems. Additionally, a negligible decrease in RMS tire normal force was documented through computer simulations. And although the FLC absorbed power was comparable to that of the fixed-current MagneShockTM the FLC revealed reduced average RMS sprung-mass accelerations over the fixed-current MagneShocks by 2-9%. Possible means for improvement of this system include reducing the suspension spring stiffness and increasing the dynamic damping range of the MagneShockTM.
Bakri, F. A.; Mashor, M. Y.; Sharun, S. M.; Bibi Sarpinah, S. N.; Abu Bakar, Z.
2016-10-01
This study proposes an adaptive fuzzy controller for attitude control system (ACS) of Innovative Satellite (InnoSAT) based on direct action type structure. In order to study new methods used in satellite attitude control, this paper presents three structures of controllers: Fuzzy PI, Fuzzy PD and conventional Fuzzy PID. The objective of this work is to compare the time response and tracking performance among the three different structures of controllers. The parameters of controller were tuned on-line by adjustment mechanism, which was an approach similar to a PID error that could minimize errors between actual and model reference output. This paper also presents a Model References Adaptive Control (MRAC) as a control scheme to control time varying systems where the performance specifications were given in terms of the reference model. All the controllers were tested using InnoSAT system under some operating conditions such as disturbance, varying gain, measurement noise and time delay. In conclusion, among all considered DA-type structures, AFPID controller was observed as the best structure since it outperformed other controllers in most conditions.
Using fuzzy logic analysis for siting decisions of infiltration trenches for highway runoff control.
Ki, Seo Jin; Ray, Chittaranjan
2014-09-15
Determining optimal locations for best management practices (BMPs), including their field considerations and limitations, plays an important role for effective stormwater management. However, these issues have been often overlooked in modeling studies that focused on downstream water quality benefits. This study illustrates the methodology of locating infiltration trenches at suitable locations from spatial overlay analyses which combine multiple layers that address different aspects of field application into a composite map. Using seven thematic layers for each analysis, fuzzy logic was employed to develop a site suitability map for infiltration trenches, whereas the DRASTIC method was used to produce a groundwater vulnerability map on the island of Oahu, Hawaii, USA. In addition, the analytic hierarchy process (AHP), one of the most popular overlay analyses, was used for comparison to fuzzy logic. The results showed that the AHP and fuzzy logic methods developed significantly different index maps in terms of best locations and suitability scores. Specifically, the AHP method provided a maximum level of site suitability due to its inherent aggregation approach of all input layers in a linear equation. The most eligible areas in locating infiltration trenches were determined from the superposition of the site suitability and groundwater vulnerability maps using the fuzzy AND operator. The resulting map successfully balanced qualification criteria for a low risk of groundwater contamination and the best BMP site selection. The results of the sensitivity analysis showed that the suitability scores were strongly affected by the algorithms embedded in fuzzy logic; therefore, caution is recommended with their use in overlay analysis. Accordingly, this study demonstrates that the fuzzy logic analysis can not only be used to improve spatial decision quality along with other overlay approaches, but also is combined with general water quality models for initial and refined
Feedback Control of Transmission Line by Static VAR Compensators (TSC & TCR Using Fuzzy Logic
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Arushi Jaiswal
2013-07-01
Full Text Available Voltage profile maintenance of a transmission system can be done by using feedback control methodology and the compensation technique used is Static VAR compensation. This thesis describes a MATLAB based SIMULINK model that can be implemented in real time systems to maintain a constant voltage profile during load changes and fault conditions. In any power system the basic requirement is to keep the voltage of the system constant so that the load functions properly. Whenever there is a fault or any load is disconnected, the active and reactive power requirements of the system changes. As a result, the voltage of the system changes. Therefore to maintain a constant voltage profile shunt compensators are used near the load end, in the model presented in this project. Fuzzy logic is also implemented to set the proper compensation required
Project Scheduling Using Hybrid Genetic Algorithm with Fuzzy Logic Controller in SCM Environment
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
In supply chain management (SCM) environment, we consider a resource-constrained project scheduling problem (rcPSP) model as one of advanced scheduling problems considered by a constraint programming technique. We develop a hybrid genetic algorithm (hGA) with a fuzzy logic controller (FLC) to solve the rcPSP which is the well known NP-hard problem. This new approach is based on the design of genetic operators with FLC through initializing the serial method which is superior for a large rcPSP scale. For solving these rcPSP problems, we first demonstrate that our hGA with FLC (flc-hGA) yields better results than several heuristic procedures presented in the literature. We have revealed a fact that flc-hGA has the evolutionary behaviors of average fitness better than hGA without FLC.
Set Theory and Arithmetic in Fuzzy Logic
Běhounek, L. (Libor); Haniková, Z. (Zuzana)
2015-01-01
This chapter offers a review of Petr Hájek’s contributions to first-order axiomatic theories in fuzzy logic (in particular, ZF-style fuzzy set theories, arithmetic with a fuzzy truth predicate, and fuzzy set theory with unrestricted comprehension schema). Generalizations of Hájek’s results in these areas to MTL as the background logic are presented and discussed.
Ruspini, Enrique H.
1991-01-01
Summarized here are the results of recent research on the conceptual foundations of fuzzy logic. The focus is primarily on the principle characteristics of a model that quantifies resemblance between possible worlds by means of a similarity function that assigns a number between 0 and 1 to every pair of possible worlds. Introduction of such a function permits one to interpret the major constructs and methods of fuzzy logic: conditional and unconditional possibility and necessity distributions and the generalized modus ponens of Zadeh on the basis of related metric relationships between subsets of possible worlds.
Fuzzy Logic Based Controller for Maintaining Human Comfort within Intelligent Building System
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Nasrodin .T. Mustapha, Momoh J. E. Salami, Nazim and M. Nasiri
2012-10-01
Full Text Available This paper presents an intelligent control approach for air handling unit (AHU which is an integral part of heat, ventilation, and air conditioning (HVAC system. In the past years various control design for HVAC have been proposed as this system remarkably consumes very high energy. But most of the proposed designs were focused on the control flow of heat-transfer medium such as chilled or heated water while the importance of the efficient mixture of outdoor and indoor enthalpies is sometimes ignored. These enthalpies invariably determine the best strategy to overcome thermal load in a controlled environment to satisfy human comfort, hence a control design strategy must be able to efficiently regulate the flow and mixture of outdoor and indoor enthalpies by a proper control of AHU dampers and fans. This approach requires sensors to measure temperature and relative humidity of both outdoor and indoor environments. However, unpredictable level of disturbances coming from many sources including heat generated by occupants, electrical items and air leaking and the continuous changes of outdoor enthalpy makes it difficult to model the process. Consequently, conventional controllers are not suitable, hence the use of fuzzy logic controller (FLC is proposed in this paper. This proposed controller operates in a master and slave control loop so as to control the AHU dampers and fans with adjustable output membership function whilst at the same time a scaling-factor method is used to drive the master operation. To implement the proposed system, a small scale prototype has been designed and fabricated. This prototype is an AHU model which consists of ductwork, temperature and humidity sensors, dampers, air cooling and heating systems. A small box is used as a conditioning space in which a room temperature is measured. The control algorithm is programmed using National Instrument (NI LabVIEW and executed using NI FieldPoint. Experimental results reveal that
Extended Fuzzy Logic Programs with Fuzzy Answer Set Semantics
Saad, Emad
This paper extends fuzzy logic programs [12, 24] to allow the explicit representation of classical negation as well as non-monotonic negation, by introducing the notion of extended fuzzy logic programs. We present the fuzzy answer set semantics for the extended fuzzy logic programs, which is based on the classical answer set semantics of classical extended logic programs [7]. We show that the proposed semantics is a natural extension to the classical answer set semantics of classical extended logic programs [7]. Furthermore, we define fixpoint semantics for extended fuzzy logic programs with and without non-monotonic negation, and study their relationship to the fuzzy answer set semantics. In addition, we show that the fuzzy answer set semantics is reduced to the stable fuzzy model semantics for normal fuzzy logic programs introduced in [42]. The importance of that is computational methods developed for normal fuzzy logic programs can be applied to the extended fuzzy logic programs. Moreover, we show that extended fuzzy logic programs can be intuitively used for representing and reasoning about actions in fuzzy environment.
Fuzzy Logic-Based Audio Pattern Recognition
Malcangi, M.
2008-11-01
Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.
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Márcio Mendonça
2015-10-01
Full Text Available In this work, it is analyzed a multivariate system control of an alcoholic fermentation process with no minimum phase. The control is made with PID classic controllers associated with a supervisory system based on Fuzzy Systems. The Fuzzy system, a priori, send set-points to PID controllers, but also adds protection functions, such as if the biomass valued is at zero or very close. The Fuzzy controller changes the campaign to prevent or mitigate the paralyzation of the process. Three control architectures based on Fuzzy Control Systems are presented and compared in performance with classic control in different campaigns. The third architecture, in particular, adds an adaptive function. A brief summary of Fuzzy theory and correlated works will be presented. And, finally simulations results, conclusions and future works end the article.
Modeling and Fuzzy Logic Control of an Active Reaction Compensating Platform System
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Y.J. Lin
1995-01-01
Full Text Available This article presents the application of the fuzzy logic (FL concept to the active control of a multiple degree of freedom reaction compensating platform system that is designed and used for isolating vibratory disturbances of space-based devices. The physical model used is a scaled down two-plate platform system. In this work, simulation is performed and presented. According to the desired performance specifications, a full range of investigation regarding the development of an FL stabilization controller for the system is conducted. Specifically, the study includes four stages: comprehensive dynamic modeling of the reaction compensating system; analysis of the dynamic responses of the platform system when it is subjected to various disturbances; design of an FL controller capable of filtering the vibratory disturbances transmitted to the bottom plate of the platform system; performance evaluation of the developed FL controller through computer simulations. To simplify the simulation work, the system model is linearized and the system component parameter variations are not considered. The performance of the FL controller is tested by exciting the system with an impulsive force applied at an arbitrarily chosen point on the top plate. It is shown that the proposed FL controller is robust in that the resultant active system is well stabilized when subjected to a random external disturbance. The comparative study of the performances of the FL controlled active reaction and passive reaction compensating systems also reveals that the FL controlled system achieves significant improvements in reducing vibratory accelerations over passive systems.
Fuzzy Logic Indoor Positioning System
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Roberto García Sánz
2008-12-01
Full Text Available The GPS system is not valid for positioning indoors, thus positioning systems are designed using Wi-Fi technology that allows location of a device inside buildings. The use of fuzzy logic is argued by the failure to find positioning systems based on this technology, which seeks toobserve how their use in this field
IMPLEMENTATION OF FUZZY LOGIC MAXIMUM POWER POINT TRACKING CONTROLLER FOR PHOTOVOLTAIC SYSTEM
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Rasoul Rahmani
2013-01-01
Full Text Available In this study, simulation and hardware implementation of Fuzzy Logic (FL Maximum Power Point Tracking (MPPT used in photovoltaic system with a direct control method are presented. In this control system, no proportional or integral control loop exists and an adaptive FL controller generates the control signals. The designed and integrated system is a contribution of different aspects which includes simulation, design and programming and experimental setup. The resultant system is capable and satisfactory in terms of fastness and dynamic performance. The results also indicate that the control system works without steady-state error and has the ability of tracking MPPs rapid and accurate which is useful for the sudden changes in the atmospheric condition. MATLAB/Simulink software is utilized for simulation and also programming the TMS320F2812 Digital Signal Processor (DSP. The whole system designed and implemented to hardware was tested successfully on a laboratory PV array. The obtained experimental results show the functionality and feasibility of the proposed controller.
Anaesthesia monitoring using fuzzy logic.
Baig, Mirza Mansoor; Gholamhosseini, Hamid; Kouzani, Abbas; Harrison, Michael J
2011-10-01
Humans have a limited ability to accurately and continuously analyse large amount of data. In recent times, there has been a rapid growth in patient monitoring and medical data analysis using smart monitoring systems. Fuzzy logic-based expert systems, which can mimic human thought processes in complex circumstances, have indicated potential to improve clinicians' performance and accurately execute repetitive tasks to which humans are ill-suited. The main goal of this study is to develop a clinically useful diagnostic alarm system based on fuzzy logic for detecting critical events during anaesthesia administration. The proposed diagnostic alarm system called fuzzy logic monitoring system (FLMS) is presented. New diagnostic rules and membership functions (MFs) are developed. In addition, fuzzy inference system (FIS), adaptive neuro fuzzy inference system (ANFIS), and clustering techniques are explored for developing the FLMS' diagnostic modules. The performance of FLMS which is based on fuzzy logic expert diagnostic systems is validated through a series of off-line tests. The training and testing data set are selected randomly from 30 sets of patients' data. The accuracy of diagnoses generated by the FLMS was validated by comparing the diagnostic information with the one provided by an anaesthetist for each patient. Kappa-analysis was used for measuring the level of agreement between the anaesthetist's and FLMS's diagnoses. When detecting hypovolaemia, a substantial level of agreement was observed between FLMS and the human expert (the anaesthetist) during surgical procedures. The diagnostic alarm system FLMS demonstrated that evidence-based expert diagnostic systems can diagnose hypovolaemia, with a substantial degree of accuracy, in anaesthetized patients and could be useful in delivering decision support to anaesthetists.
DEFF Research Database (Denmark)
Boiocchi, Riccardo; Gernaey, Krist; Sin, Gürkan
2016-01-01
A methodology is developed to systematically design the membership functions of fuzzy-logic controllers for multivariable systems. The methodology consists of a systematic derivation of the critical points of the membership functions as a function of predefined control objectives. Several...... rules, determine the long term reachability of the control objectives by the fuzzy logic controller. The methodology is highlighted using a single-stage side-stream partial nitritation/Anammox reactor as a case study. As a result, a new fuzzy-logic controller for high and stable total nitrogen removal......, the controller was tested, and showed robustness, against measurement noise levels typical for wastewater sensors. A feedforward-feedback configuration using the present controller would give even better performance. In comparison, a previously developed fuzzy-logic controller using merely expert and intuitive...
Introduction to fuzzy logic using Matlab
Sivanandam, SN; Deepa, S N
2006-01-01
Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference.
Fayek, H M; Elamvazuthi, I; Perumal, N; Venkatesh, B
2014-09-01
A computationally-efficient systematic procedure to design an Optimal Type-2 Fuzzy Logic Controller (OT2FLC) is proposed. The main scheme is to optimize the gains of the controller using Particle Swarm Optimization (PSO), then optimize only two parameters per type-2 membership function using Genetic Algorithm (GA). The proposed OT2FLC was implemented in real-time to control the position of a DC servomotor, which is part of a robotic arm. The performance judgments were carried out based on the Integral Absolute Error (IAE), as well as the computational cost. Various type-2 defuzzification methods were investigated in real-time. A comparative analysis with an Optimal Type-1 Fuzzy Logic Controller (OT1FLC) and a PI controller, demonstrated OT2FLC׳s superiority; which is evident in handling uncertainty and imprecision induced in the system by means of noise and disturbances. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
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Prema Kannan
2013-01-01
Full Text Available This paper describes design, modeling, simulation, control, and implementation of teleoperated agricultural vehicle using intelligent technique. This vehicle can be used for ploughing, sowing, and soil moisture sensing. Online computer controlled steering system for a vehicle utilizing two independent drive wheels can be used to avoid obstacles and to improve the ability to resist external side forces. To control the steer angles of the nondriven wheels, the mathematical relationships between the drive wheel speeds and the steer angles of the nondriven wheels are used. A fuzzy logic controller is designed to change the drive wheel speeds and to achieve the desired steer angles. Online control of the agricultural vehicle is achieved from a remote place by means of Web Publishing Tool in LabVIEW. IR sensors in the vehicle are used to detect and to avoid the obstacles around. The developed steering angle control algorithm and fuzzy logic controller have been implemented in an agricultural vehicle which depicts that the vehicle performs its operation efficiently and reduces the manpower and becomes advantageous.
Wang, Yin-He; Luo, Liang; Fan, Yong-Qing; Zhang, Yun; Liu, Xiao-Ping; Zhang, Si-Ying
2014-03-01
Many practical engineering applications require various types of fuzzy logic systems (FLSs) to design adaptive controllers for nonlinear systems with uncertainties. In this article, we will consider a fundamental theoretical question: is it possible to find a unified adaptive control design method suited to various types of FLSs? In order to solve this problem, we will introduce scalers and saturators at the input and output terminals of FLSs to form the extended FLSs (EFLS). The scalers and saturators have adjustable parameters. By designing the updated laws of these parameters and the estimate values of the fuzzy approximate accuracies, stable adaptive fuzzy controllers can be realised for a class of nonlinear systems with unknown homogeneous drift functions and gains. The proposed design method is only dependent on the outputs of EFLS and the above updated laws, thus increasing its adaptability. The fuzzy control scheme introduced in this article is suitable for all fuzzy systems with or without fuzzy rules. Simulations will also be used to show the validity of the method proposed in this article.
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Siva GanaVara Prasad P., Amrutha Veena Chandrapati, Navyata Yesodha Rao K., Lakshmi Prasanth K.
2014-05-01
Full Text Available This paper proposes fuzzy logic controller based a single-phase seven-level inverter for grid-connected photovoltaic systems, with a novel pulse width-modulation (PWM control scheme. Three reference signals produces from fuzzy logic controller which are identical to each other are going to compare with the amplitude of the triangular carrier signal. The inverter is capable of producing seven levels( Vab = Vdc Vab = 2Vdc/3 Vab = Vdc/3 Vab = 0 Vab = −V dc/3 Vab= − 2Vdc/3 Vab = −V dc of output-voltage levels from the dc supply voltage. The total harmonic distortion is reduces by this control strategy. The proposed system was verified through simulation.
Energy Technology Data Exchange (ETDEWEB)
Gounden, N. Ammasai; Ann Peter, Sabitha; Nallandula, Himaja; Krithiga, S. [Department of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu (India)
2009-03-15
A fuzzy logic controller has been developed for interfacing PV array with utility grid through a three-phase line-commutated inverter for the first time. The controller tracks and feeds maximum power to the utility grid. The linguistic variables have been selected appropriately to modulate the firing angle of the inverter for tracking the maximum power. The simulink model of the proposed scheme employing fuzzy logic controller has been built using MATLAB/PSB. A PIC microcontroller has been programmed for generation of firing pulses to the thyristors in the inverter. Experimental setup of the proposed scheme has been built and the results obtained on a PV array of 54 V, 12 A rating are presented. The comparison of experimental and simulation results shows very close agreement between the two thus validating the controller proposed. (author)
MODELLING OF AIR CONDITIONING SYSTEM BY FUZZY LOGIC APPROACH
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Ahmet ÖZEK
2004-03-01
Full Text Available One of the main problems in control systems is the difficulty to form the mathematical model associated with the control mechanism. Even though this model can be formed, to realize the application with conventional logic may cause very complex problems. The fuzzy logic without using mathematical model of control system can create control mechanism only with the help of linguistic variables. In this article the modeling has been realized by fuzzy logic.
Fuzzy logic based DSP controlled servo position control for ultrasonic motor
Energy Technology Data Exchange (ETDEWEB)
Bal, G.; Demirbas, S.; Colak, I. [Gazi University, Ankara (Turkey). Electrical Dept.; Bekiroglu, E. [Abant Izzet Baysal University, Bolu (Turkey). Dept. of Electrical and Electronics Engineering
2004-12-01
In this paper, position control of an ultrasonic motor was implemented on the basis of fuzzy reasoning. A digitally controllable two phase serial resonant inverter was developed to drive the ultrasonic motor by using a TMS320F243 digital signal processor. The driving frequency was used as a control input in the position control loop. The position characteristics obtained from the proposed drive and control system were demonstrated and evaluated by experiments. The experimental results verify that the developed position control scheme is highly effective, reliable and applicable for the ultrasonic motor. (author)
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Светлана Николаевна Дворяткина
2014-12-01
Full Text Available This article focuses on the actual problem of designing information systems of automated control of mathematical knowledge of students using fuzzy logic, which take into account the shortcomings of modern systems of evaluation and control. These include a limited number of forms of response and two-point scoring system, inflexible procedures calculating the final assessment, the lack of consideration of estimating the depth and breadth of knowledge, adaptation of the estimation procedure to the individual characteristics of the students.
Fuzzy Logic for Incidence Geometry.
Tserkovny, Alex
The paper presents a mathematical framework for approximate geometric reasoning with extended objects in the context of Geography, in which all entities and their relationships are described by human language. These entities could be labelled by commonly used names of landmarks, water areas, and so forth. Unlike single points that are given in Cartesian coordinates, these geographic entities are extended in space and often loosely defined, but people easily perform spatial reasoning with extended geographic objects "as if they were points." Unfortunately, up to date, geographic information systems (GIS) miss the capability of geometric reasoning with extended objects. The aim of the paper is to present a mathematical apparatus for approximate geometric reasoning with extended objects that is usable in GIS. In the paper we discuss the fuzzy logic (Aliev and Tserkovny, 2011) as a reasoning system for geometry of extended objects, as well as a basis for fuzzification of the axioms of incidence geometry. The same fuzzy logic was used for fuzzification of Euclid's first postulate. Fuzzy equivalence relation "extended lines sameness" is introduced. For its approximation we also utilize a fuzzy conditional inference, which is based on proposed fuzzy "degree of indiscernibility" and "discernibility measure" of extended points.
Fuzzy Logic for Incidence Geometry
2016-01-01
The paper presents a mathematical framework for approximate geometric reasoning with extended objects in the context of Geography, in which all entities and their relationships are described by human language. These entities could be labelled by commonly used names of landmarks, water areas, and so forth. Unlike single points that are given in Cartesian coordinates, these geographic entities are extended in space and often loosely defined, but people easily perform spatial reasoning with extended geographic objects “as if they were points.” Unfortunately, up to date, geographic information systems (GIS) miss the capability of geometric reasoning with extended objects. The aim of the paper is to present a mathematical apparatus for approximate geometric reasoning with extended objects that is usable in GIS. In the paper we discuss the fuzzy logic (Aliev and Tserkovny, 2011) as a reasoning system for geometry of extended objects, as well as a basis for fuzzification of the axioms of incidence geometry. The same fuzzy logic was used for fuzzification of Euclid's first postulate. Fuzzy equivalence relation “extended lines sameness” is introduced. For its approximation we also utilize a fuzzy conditional inference, which is based on proposed fuzzy “degree of indiscernibility” and “discernibility measure” of extended points. PMID:27689133
Fuzzy forecasting based on fuzzy-trend logical relationship groups.
Chen, Shyi-Ming; Wang, Nai-Yi
2010-10-01
In this paper, we present a new method to predict the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy-trend logical relationship groups (FTLRGs). The proposed method divides fuzzy logical relationships into FTLRGs based on the trend of adjacent fuzzy sets appearing in the antecedents of fuzzy logical relationships. First, we apply an automatic clustering algorithm to cluster the historical data into intervals of different lengths. Then, we define fuzzy sets based on these intervals of different lengths. Then, the historical data are fuzzified into fuzzy sets to derive fuzzy logical relationships. Then, we divide the fuzzy logical relationships into FTLRGs for forecasting the TAIEX. Moreover, we also apply the proposed method to forecast the enrollments and the inventory demand, respectively. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.
Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot
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Nitin Afzulpurkar
2008-11-01
Full Text Available This paper describes position control of autonomous mobile robot using combination of Kalman filter and Fuzzy logic techniques. Both techniques have been used to fuse information from internal and external sensors to navigate a typical mobile robot in an unknown environment. An obstacle avoidance algorithm utilizing stereo vision technique has been implemented for obstacle detection. The odometry errors due to systematic-errors (such as unequal wheel diameter, the effect of the encoder resolution etc. and/or non-systematic errors (ground plane, wheel-slip etc. contribute to various motion control problems of the robot. During the robot moves, whether straight-line and/or arc, create the position and orientation errors which depend on systematic and/or non-systematic odometry errors. The main concern in most of the navigating systems is to achieve the real-time and robustness performances to precisely control the robot movements. The objective of this research is to improve the position and the orientation of robot motion. From the simulation and experiments, we prove that the proposed mobile robot moves from start position to goal position with greater accuracy avoiding obstacles.
National Research Council Canada - National Science Library
Prema Kannan; Senthil Kumar Natarajan; Subhransu Sekar Dash
2013-01-01
.... A fuzzy logic controller is designed to change the pulse width of switching signal applied to the converter and thereby the voltage fed to the armature of the separately excited DC motor to regulate the speed...
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Zhu Qi-dan
2013-04-01
Full Text Available The path planning and obstacle avoidance are the most important tasks for an autonomous mobile robot moving in an unknown environment. This paper presents a simple fuzzy logic controller which involves searching target and path planning with obstacle avoidance. In this contest, fuzzy logic controllers are constructed for target searching behavior and obstacle avoidance behavior based on the distance and angle between the robot and the target as inputs for the first behavior and the distance between the robot and the nearest obstacle for the second behavior; then a third fusion behavior is developed to combine the outputs of the two behaviors to compute the speed of the mobile robot in order to fulfill its task properly. Simulation results show that the proposed approach is efficient and can be applied to the mobile robots moving in unknown environments.
Fuzzy logic speed control for the engine of an air-powered vehicle
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Qihui Yu
2016-03-01
Full Text Available To improve the condition of air and eliminate exhaust gas pollution, this article proposes a compressed air power system. Instead of an internal combustion engine, the automobile is equipped with a compressed air engine, which transforms the energy of compressed air into mechanical motion energy. A prototype was built, and the compressed air engine was tested on an experimental platform. The output torque and energy efficiency were obtained from experimental results. When the supply pressure was set at 2 MPa and the speed was 420 r min−1, the output torque, the output power, and the energy efficiency were 56 N m, 1.93 kW, and 25%, respectively. To improve the efficiency of the system, a fuzzy logic speed control strategy is proposed and simulated. The experimental study verified that the theoretical evaluation of the system was reasonable, and this research can be referred to as the design and control of air-powered vehicles.
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Ammar Hussein Mutlag
2014-01-01
Full Text Available 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.
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G. Venu Madhav
2014-12-01
Full Text Available In this paper, decouple PI control for output active and reactive powers which is the common control technique for power converter of Doubly Fed Induction Generator (DFIG is presented. But there are some disadvantages with this control method like uncertainty about the exact model, behavior of some parameters or unpredictable wind speed and tuning of PI parameters. To overcome the mentioned disadvantages a fuzzy logic control of DFIG wind turbine is presented and is compared with PI controller. To validate the proposed scheme, simulation results are presented, these results showed that the performance of fuzzy control of DFIG is excellent and it improves power quality and stability of wind turbine compared to PI controller. The Fuzzy logic controller is applied to rotor side converter for active power control and voltage regulation of wind turbine. The entire work is carried out in MATLab/Simulink. Different faulty operating conditions are considered to prove the effective implementation of the proposed control scheme.
Hybrid Genetic Algorithm with Fuzzy Logic Controller for Obstacle Location-Allocation Problem
Taniguchi, Jyunichi; Wang, Xiaodong; Gen, Mitsuo; Yokota, Takao
Location-allocation problem is known as one of the important problems faced in Industrial Engineering/Operations Research fields. One of important logistic tasks is transfer of manufactured products from plants to customers. If there is a need to supply products to large number of customers in a wide area, it is disadvantageous to deliver products from the only central distribution center or direct from plants. It is suitable to build up local distribution centers. In literature, different location models have been used according to characteristics of a distribution area. However, most of them related the location problem without obstacle. In this paper, an extended location-allocation problem with obstacles is considered. Since this problem is very complex and with many infeasible solutions, no direct method is effective to solve it, we propose a hybrid Genetic Algorithm (hGA) for effectively solving this problem. The proposed hGA combines two efficient methods based on Lagrangian relaxation and Dijkstra’s shortest path algorithm. To improve the performance of the proposed hGA, a Fuzzy Logic Controller (FLC) approach is also adopted to auto-tune the GA parameters.
Fuzzy logic controller approach in quality and productivity improvement program (PPKP)
Ruza, Nadiah; Mustafa, Zainol; Rika Fatimah, P. L.; Hussain, Saiful Izzuan
2013-04-01
The education sector plays a major role in building the stability and strength of a country and also the main channel in shaping the quality of nation. Each generation have different educational level. Therefore, improvements should be made on an on-going basis to ensure that quality of education is at high level all the time. In general, this study aimed to determine the effectiveness of the education system for Quality and Productivity Improvement Program (PPKP), Universiti Kebangsaan Malaysia (UKM) from the perspective of alumni as well as their satisfaction and importance level on how PPKP be able to meet the needs of their students. This study discusses the application of Fuzzy Logic Control analysis, which is flexible and adjustable. This analysis also identifies the program's quality of education system through alumni point of view. Overall, it was found that 93.4 percent of respondents felt that all four dimensions of students' needs have high level of importance. The rest felt that the importance level of all four dimensions is modest. Next, in term of satisfaction level with PPKP, only one percent was very satisfied with PPKP's role in meeting the needs of students and the rest felt that their needs are met only at moderate level. Results of this study could be used to improve the quality of education system for PPKP.
Fuzzy logic modeling and control of steel rod quenching after hot rolling
Giorleo, G.; Memola Capece Minutolo, F.; Sergi, V.
1997-10-01
Reinforced concrete rod produced by European Community countries must comply with standards that establish minimum strength and tensile properties along with other technological and geometrical characteristics; however, possible variability within the assigned limits is not specified. Consequently, a number of manufacturing methods are now used, with the result that over time the mechanical properties of these products vary widely. Increased competition has led to the development of new procedures incorporating both process and quality control. One example is a process based on the heat treatment undergone by the metal bars leaving the final stand of the rolling mill train. In this way, the mechanical and technological properties can be graduated, thereby enhancing strength (particularly yield point) without altering the deformability of the material. This procedure does away with the need to alter the chemical composition of the steel used to manufacture the rods. Process adjustment still relies on the experience of the production manager, however. This paper examines the possibility of applying fuzzy logic computer techniques to the heat treatment process in order to render it more rational and independent of operator unreliability.
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Po-Chen Cheng
2015-06-01
Full Text Available In this paper, an asymmetrical fuzzy-logic-control (FLC-based maximum power point tracking (MPPT algorithm for photovoltaic (PV systems is presented. Two membership function (MF design methodologies that can improve the effectiveness of the proposed asymmetrical FLC-based MPPT methods are then proposed. The first method can quickly determine the input MF setting values via the power–voltage (P–V curve of solar cells under standard test conditions (STC. The second method uses the particle swarm optimization (PSO technique to optimize the input MF setting values. Because the PSO approach must target and optimize a cost function, a cost function design methodology that meets the performance requirements of practical photovoltaic generation systems (PGSs is also proposed. According to the simulated and experimental results, the proposed asymmetrical FLC-based MPPT method has the highest fitness value, therefore, it can successfully address the tracking speed/tracking accuracy dilemma compared with the traditional perturb and observe (P&O and symmetrical FLC-based MPPT algorithms. Compared to the conventional FLC-based MPPT method, the obtained optimal asymmetrical FLC-based MPPT can improve the transient time and the MPPT tracking accuracy by 25.8% and 0.98% under STC, respectively.
Ullah, Muhammed Zafar
Neural Network and Fuzzy Logic are the two key technologies that have recently received growing attention in solving real world, nonlinear, time variant problems. Because of their learning and/or reasoning capabilities, these techniques do not need a mathematical model of the system, which may be difficult, if not impossible, to obtain for complex systems. One of the major problems in portable or electric vehicle world is secondary cell charging, which shows non-linear characteristics. Portable-electronic equipment, such as notebook computers, cordless and cellular telephones and cordless-electric lawn tools use batteries in increasing numbers. These consumers demand fast charging times, increased battery lifetime and fuel gauge capabilities. All of these demands require that the state-of-charge within a battery be known. Charging secondary cells Fast is a problem, which is difficult to solve using conventional techniques. Charge control is important in fast charging, preventing overcharging and improving battery life. This research work provides a quick and reliable approach to charger design using Neural-Fuzzy technology, which learns the exact battery charging characteristics. Neural-Fuzzy technology is an intelligent combination of neural net with fuzzy logic that learns system behavior by using system input-output data rather than mathematical modeling. The primary objective of this research is to improve the secondary cell charging algorithm and to have faster charging time based on neural network and fuzzy logic technique. Also a new architecture of a controller will be developed for implementing the charging algorithm for the secondary battery.
Farhoud, Aidin; Erfanian, Abbas
2014-05-01
In this paper, a fully automatic robust control strategy is proposed for control of paraplegic pedaling using functional electrical stimulation (FES). The method is based on higher-order sliding mode (HOSM) control and fuzzy logic control. In FES, the strength of muscle contraction can be altered either by varying the pulse width (PW) or by the pulse amplitude (PA) of the stimulation signal. The proposed control strategy regulates simultaneously both PA and PW (i.e., PA/PW modulation). A HOSM controller is designed for regulating the PW and a fuzzy logic controller for the PA. The proposed control scheme is free-model and does not require any offline training phase and subject-specific information. Simulation studies on a virtual patient and experiments on three paraplegic subjects demonstrate good tracking performance and robustness of the proposed control strategy against muscle fatigue and external disturbances during FES-induced pedaling. The results of simulation studies show that the power and cadence tracking errors are 5.4% and 4.8%, respectively. The experimental results indicate that the proposed controller can improve pedaling system efficacy and increase the endurance of FES pedaling. The average of power tracking error over three paraplegic subjects is 7.4±1.4% using PA/PW modulation, while the tracking error is 10.2±1.2% when PW modulation is used. The subjects could pedal for 15 min with about 4.1% power loss at the end of experiment using proposed control strategy, while the power loss is 14.3% using PW modulation. The controller could adjust the stimulation intensity to compensate the muscle fatigue during long period of FES pedaling.
DEFF Research Database (Denmark)
Jantzen, Jan
as any PID controller. In the nonlinear domain, the stability of four standard control surfaces is analysed by means of describing functions and Nyquist plots. The self-organizing controller (SOC) is shown to be a model reference adaptive controller. There is a possibility that a nonlinear fuzzy PID......The objective of this textbook is to acquire an understanding of the behaviour of fuzzy logic controllers. Under certain conditions a fuzzy controller is equivalent to a proportional-integral-derivative (PID) controller. Using that equivalence as a link, the book applies analysis methods from...... linear and nonlinear control theory. In the linear domain, PID tuning methods and stability analyses are transferred to linear fuzzy controllers. The Nyquist plot shows the robustness of different settings of the fuzzy gain parameters. As a result, a fuzzy controller is guaranteed to perform as well...
DEFF Research Database (Denmark)
Jantzen, Jan
linear and nonlinear control theory. In the linear domain, PID tuning methods and stability analyses are transferred to linear fuzzy controllers. The Nyquist plot shows the robustness of different settings of the fuzzy gain parameters. As a result, a fuzzy controller is guaranteed to perform as well......The objective of this textbook is to acquire an understanding of the behaviour of fuzzy logic controllers. Under certain conditions a fuzzy controller is equivalent to a proportional-integral-derivative (PID) controller. Using that equivalence as a link, the book applies analysis methods from...... as any PID controller. In the nonlinear domain, the stability of four standard control surfaces is analysed by means of describing functions and Nyquist plots. The self-organizing controller (SOC) is shown to be a model reference adaptive controller. There is a possibility that a nonlinear fuzzy PID...
ROBUST STABILIZATION AND OPTIMIZATION OF FLIGHT CONTROL SYSTEM WITH STATE FEEDBACK AND FUZZY LOGICS
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Marta M. Komnatska
2009-04-01
Full Text Available This paper deals with combination of two powerful and modern control tools as linear matrix inequality that is used for synthesis a ‘crisp’ controller and a fuzzy control approach for designing a soft controller. The control design consists of two stages. The first stage investigates the problem of a robust an controller design with parameters uncertainties of the handled plant in the presence of external disturbances. Stability conditions are obtained via a quadratic Lyapunov function and represented in the form of linear matrix inequalities. The second stage consists of the outer loop controller construction based on fuzzy inference system that utilizes for altitude hold mode. The parameters of the fuzzy controller are adjusted with a gradient descent method in order to improve the performance of the overall system. The case study illustrates the efficiency of the proposed approach to the flight control of small Unmanned Aerial Vehicle
Robust nonlinear PID-like fuzzy logic control of a planar parallel (2PRP-PPR) manipulator.
Londhe, P S; Singh, Yogesh; Santhakumar, M; Patre, B M; Waghmare, L M
2016-07-01
In this paper, a robust nonlinear proportional-integral-derivative (PID)-like fuzzy control scheme is presented and applied to complex trajectory tracking control of a 2PRP-PPR (P-prismatic, R-revolute) planar parallel manipulator (motion platform) with three degrees-of-freedom (DOF) in the presence of parameter uncertainties and external disturbances. The proposed control law consists of mainly two parts: first part uses a feed forward term to enhance the control activity and estimated perturbed term to compensate for the unknown effects namely external disturbances and unmodeled dynamics, and the second part uses a PID-like fuzzy logic control as a feedback portion to enhance the overall closed-loop stability of the system. Experimental results are presented to show the effectiveness of the proposed control scheme.
Modeling of Kefir Production with Fuzzy Logic
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Hüseyin Nail Akgül
2014-06-01
Full Text Available The fermentation is ended with pH 4.6 values in industrial production of kefir. In this study, the incubation temperature, the incubation time and inoculums of culture were chose as variable parameters of kefir. In conventional control systems, the value of pH can be found by trial method. In these systems, if the number of input parameters is greater, the method of trial and error creates a system dependent on the person as well as troublesome. Fuzzy logic can be used in such cases. Modeling studies with this fuzzy logic control are examined in two portions. The first part consists of fuzzy rules and membership functions, while the second part consists of clarify. Kefir incubation temperature between 20 and 25°C, the incubation period between 18 to 22 hours and the inoculum ratio of culture between 1-5% are selected for optimum production conditions. Three separate fuzzy sets (triangular membership function are used to blur the incubation temperature, the incubation time and the inoculum ratio of culture. Because the membership function numbers belonging to the the input parameters are 3 units, 3x3x3=27 line rule is obtained by multiplying these numbers. The table of fuzzy rules was obtained using the method of Mamdani. The membership function values were determined by the method of average weight using three trapezoidal area of membership functions created for clarification. The success of the system will be found, comparing the numerical values obtained with pH values that should be. Eventually, to achieve the desired pH value of 4.6 in the production of kefir, with the using of fuzzy logic, the workload of people will be decreased and the productivity of business can be increased. In this case, it can be provided savings in both cost and time.
Achieving of Fuzzy Automata for Processing Fuzzy Logic
Institute of Scientific and Technical Information of China (English)
SHU Lan; WU Qing-e
2005-01-01
At present, there has been an increasing interest in neuron-fuzzy systems, the combinations of artificial neural networks with fuzzy logic. In this paper, a definition of fuzzy finite state automata (FFA) is introduced and fuzzy knowledge equivalence representations between neural networks, fuzzy systems and models of automata are discussed. Once the network has been trained, we develop a method to extract a representation of the FFA encoded in the recurrent neural network that recognizes the training rules.
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Pezhman Mohammadi
2012-04-01
Full Text Available In this work, surge of prevention is a critical problem in oil and gas industries, particularly when return gas flow or gas flow reduces in transportation of gas pipelines. This paper is illustrated new results about surge control of centrifugal compressors .surge phenomenon is flow unsteady state in compressors which causes damages seriously in compressor construction. Furthermore, it also demonstrates in comparison with anti surge control ،active surge control expands stability range.Active surge control which based on fuzzy logic،is the main idea that used in this investigation. Using fuzzy controller causes an improvement in compressor's condition and increase performance range of the compressor, in addition to prevention of any instability in compressor. The simulation results is also satisfactory.
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K. Venkata Subbaiah
2010-01-01
Full Text Available The nodes in the mobile ad hoc networks act as router and host, the routing protocol is the primary issue and has to be supported before any applications can be deployed for mobile ad hoc networks. In recent many research protocols are proposed for finding an efficient route between the nodes. But most of the protocol’s that uses conventional techniques in routing; CBRP is a routing protocol that has a hierarchical-based design. This protocol divides the network area into several smaller areas called cluster. We propose a fuzzy logic based cluster head election using energy concept forcluster head routing protocol in MANET’S. Selecting an appropriate cluster head can save power for the whole mobile ad hoc network. Generally, Cluster Head election for mobile ad hoc network is based on the distance to the centroid of a cluster, and the closest one is elected as the cluster head'; or pick a node with the maximum battery capacity as the cluster head. In this paper, we present a cluster head election scheme using fuzzy logic system (FLS for mobile ad hoc networks. Three descriptors are used: distance of a node to the cluster centroid, its remaining battery capacity, and its degree of mobility. The linguistic knowledge of cluster head election based on these three descriptors is obtained from a group of network experts. 27 FLS rules are set up based on the linguistic knowledge. The output of the FLS provides a cluster head possibility, and node with the highest possibility is elected as the cluster head. The performance of fuzzy cluster head selection is evaluated using simulation, and is compared to LEACH protocol with out fuzzy cluster head election procedures and showed the proposed work is efficient than the previous one.
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Andrei Aksjonov
2016-11-01
Full Text Available Automotive driving safety systems such as an anti-lock braking system (ABS and an electronic stability program (ESP assist drivers in controlling the vehicle to avoid road accidents. In this paper, ABS and the ESP, based on the fuzzy logic theory, are integrated for vehicle stability control in complex braking maneuvers. The proposed control algorithm is implemented for a sport utility vehicle (SUV and investigated for braking on different surfaces. The results obtained for the vehicle software simulator confirm the robustness of the developed control strategy for a variety of road profiles and surfaces.
Molecular processors: from qubits to fuzzy logic.
Gentili, Pier Luigi
2011-03-14
Single molecules or their assemblies are information processing devices. Herein it is demonstrated how it is possible to process different types of logic through molecules. As long as decoherent effects are maintained far away from a pure quantum mechanical system, quantum logic can be processed. If the collapse of superimposed or entangled wavefunctions is unavoidable, molecules can still be used to process either crisp (binary or multi-valued) or fuzzy logic. The way for implementing fuzzy inference engines is declared and it is supported by the examples of molecular fuzzy logic systems devised so far. Fuzzy logic is drawing attention in the field of artificial intelligence, because it models human reasoning quite well. This ability may be due to some structural analogies between a fuzzy logic system and the human nervous system. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A Research about Greenhouse Robot’s Motion Control Based on Fuzzy Logic
Institute of Scientific and Technical Information of China (English)
Wang Sheng; Wang Shuai; Sun Yanhong
2013-01-01
This article, with greenhouse mobile robot as the investigated subject, planted fuzzy control into greenhouse robot’s route control system in order to develop a route control method that fits in the complicated environment in greenhouses. Such method aims at ensuring the safety of greenhouse mobile robot by actualizing the function of tracking routes and avoiding obstacles.
Probabilistic and fuzzy logic in clinical diagnosis.
Licata, G
2007-06-01
In this study I have compared classic and fuzzy logic and their usefulness in clinical diagnosis. The theory of probability is often considered a device to protect the classical two-valued logic from the evidence of its inadequacy to understand and show the complexity of world [1]. This can be true, but it is not possible to discard the theory of probability. I will argue that the problems and the application fields of the theory of probability are very different from those of fuzzy logic. After the introduction on the theoretical bases of fuzzy approach to logic, I have reported some diagnostic argumentations employing fuzzy logic. The state of normality and the state of disease often fight their battle on scalar quantities of biological values and it is not hard to establish a correspondence between the biological values and the percent values of fuzzy logic. Accordingly, I have suggested some applications of fuzzy logic in clinical diagnosis and in particular I have utilised a fuzzy curve to recognise subjects with diabetes mellitus, renal failure and liver disease. The comparison between classic and fuzzy logic findings seems to indicate that fuzzy logic is more adequate to study the development of biological events. In fact, fuzzy logic is useful when we have a lot of pieces of information and when we dispose to scalar quantities. In conclusion, increasingly the development of technology offers new instruments to measure pathological parameters through scalar quantities, thus it is reasonable to think that in the future fuzzy logic will be employed more in clinical diagnosis.
Recycling troubleshooting experience with fuzzy logic
Lirov, Yuval
1993-12-01
Increasing complexity of systems requires improved support capabilities. Automation controls the support costs while meeting the growing demands at the same time. Proteus is a firm-wide proactive problem management system with automated advisory capabilities. Proteus non-obtrusively accumulates troubleshooting expertise and quickly recycles it by combining case-based reasoning with text retrieval and fuzzy logic pattern matching. It has linear on-line and sub-quadratic preprocessing computational time complexities.
Properties of Measure-based Fuzzy Logic
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Measure-based fuzzy logic, which is constructed on the basis of eight axioms, is a seemingly powerful fuzzy logic. It possesses several remarkable properties. (1) It is an extended Boolean logic, satisfying all the properties of Boolean algebra, including the law of excluded middle and the law of contradiction. (2) It is conditional. Conditional membership functions play an important role in this logic. (3) The negation operator is not independently defined with the conjunction and disjunction operators, but on the contrary, it is derived from them. (4) Zadehs fuzzy logic is included in it as a particular case. (5) It gives more hints to the relationship between fuzzy logic and probability logic.
Decision model on the demographic profile for tuberculosis control using fuzzy logic
Directory of Open Access Journals (Sweden)
Laisa Ribeiro de Sá
2015-06-01
Full Text Available This study aimed to describe the relationship between demographic factors and the involvement of tuberculosis by applying a decision support model based on fuzzy logic to classify the regions as priority and non-priority in the city of João Pessoa, state of Paraíba (PB. As data source, we used the Notifiable Diseases Information System between 2009 and 2011. We chose the descriptive analysis, relative risk (RR, spatial distribution and fuzzy logic. The total of 1,245 cases remained in the study, accounting for 37.02% of cases in 2009. High and low risk clusters were identified, and the RR was higher among men (8.47, with 12 clusters, and among those uneducated (11.65, with 13 clusters. To demonstrate the functionality of the model was elected the year with highest number of cases, and the municipality district with highest population. The methodology identified priority areas, guiding managers to make decisions that respect the local particularities.
Enric Trillas a passion for fuzzy sets : a collection of recent works on fuzzy logic
Verdegay, Jose; Esteva, Francesc
2015-01-01
This book presents a comprehensive collection of the latest and most significant research advances and applications in the field of fuzzy logic. It covers fuzzy structures, rules, operations and mathematical formalisms, as well as important applications of fuzzy logic in a number of fields, like decision-making, environmental prediction and prevention, communication, controls and many others. Dedicated to Enric Trillas in recognition of his pioneering research in the field, the book also includes a foreword by Lotfi A. Zadeh and an outlook on the future of fuzzy logic.
The Fuzzy Logic Method for Simpler Forecasting
Directory of Open Access Journals (Sweden)
Jeffrey E. Jarrett
2011-08-01
Full Text Available Fildes and Makridakis (1998, Makridakis and Hibon (2000, and Fildes (2001 indicate that simple extrapolative forecasting methods that are robust forecast equally as well or better than more complicated methods, i.e. Box-Jenkins and other methods. We study the Direct Set Assignment (DSA extrapolative forecasting method. The DSA method is a non-linear extrapolative forecasting method developed within the Mamdani Development Framework, and designed to mimic the architecture of a fuzzy logic control system. We combine the DSA method Winters' Exponential smoothing. This combination provides the best observed forecast accuracy in seven of nine subcategories of time series, and is the top three in terms of observed accuracy in two subcategories. Hence, fuzzy logic which is the basis of the DSA method often is the best method for forecasting.
Control of PET Based On Fuzzy Logic for Power Quality Improvement
Directory of Open Access Journals (Sweden)
P Sravanthi
2016-06-01
Full Text Available During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the realm of industrial process, which do not lend of quantities data regarding the input-output relations. This paper presents a power electronic transformer with fuzzy controller. In the design process converters and high frequency transformers have been used. One matrix converter operates as AC/AC converter in power electronic transformer. The proposed AC/AC converter can generate desired output voltage from square input voltage. The main point of proposed PET is reduction of the stage and components of the three-part PETs. The reliability and power quality of distribution system can be significantly improved by using proposed PET. To verify the performance of the proposed PET, computer-aided simulations are carried out using MATLAB/SIMULINK
Possible use of fuzzy logic in database
Directory of Open Access Journals (Sweden)
Vaclav Bezdek
2011-04-01
Full Text Available The article deals with fuzzy logic and its possible use in database systems. At first fuzzy thinking style is shown on a simple example. Next the advantages of the fuzzy approach to database searching are considered on the database of used cars in the Czech Republic.
Fuzzy Versions of Epistemic and Deontic Logic
Gounder, Ramasamy S.; Esterline, Albert C.
1998-01-01
Epistemic and deontic logics are modal logics, respectively, of knowledge and of the normative concepts of obligation, permission, and prohibition. Epistemic logic is useful in formalizing systems of communicating processes and knowledge and belief in AI (Artificial Intelligence). Deontic logic is useful in computer science wherever we must distinguish between actual and ideal behavior, as in fault tolerance and database integrity constraints. We here discuss fuzzy versions of these logics. In the crisp versions, various axioms correspond to various properties of the structures used in defining the semantics of the logics. Thus, any axiomatic theory will be characterized not only by its axioms but also by the set of properties holding of the corresponding semantic structures. Fuzzy logic does not proceed with axiomatic systems, but fuzzy versions of the semantic properties exist and can be shown to correspond to some of the axioms for the crisp systems in special ways that support dependency networks among assertions in a modal domain. This in turn allows one to implement truth maintenance systems. For the technical development of epistemic logic, and for that of deontic logic. To our knowledge, we are the first to address fuzzy epistemic and fuzzy deontic logic explicitly and to consider the different systems and semantic properties available. We give the syntax and semantics of epistemic logic and discuss the correspondence between axioms of epistemic logic and properties of semantic structures. The same topics are covered for deontic logic. Fuzzy epistemic and fuzzy deontic logic discusses the relationship between axioms and semantic properties for these logics. Our results can be exploited in truth maintenance systems.
A FUZZY LOGIC CONTROLLERFORA TWO-LINK FUNCTIONAL MANIPULATOR
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Sherif Kamel Hussein
2014-12-01
Full Text Available This paper presents a new approach for designing a Fuzzy Logic Controller "FLC"for a dynamically multivariable nonlinear coupling system. The conventional controller with constant gains for different operating points may not be sufficient to guarantee satisfactory performance for Robot manipulator. The Fuzzy Logic Controller utilizes the error and the change of error as fuzzy linguistic inputs to regulate the system performance. The proposed controller have been developed to simulate the dynamic behavior of A Two-Link Functional Manipulator. The new controller uses only the available information of the inputoutput for controlling the position and velocity of the robot axes of the motion of the end effectors
Bae, H; Seo, H Y; Kim, S; Kim, Y
2006-01-01
Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.
Fuzzy logic scheme for tip-sample distance control for a low cost near field optical microscope
Directory of Open Access Journals (Sweden)
J.A. Márquez
2013-12-01
Full Text Available The control of the distance between the surface and the tip-sample of a Scanning Near Field Optical Microscope (SNOM is essential for a reliable surface mapping. The control algorithm should be able to maintain the system in a constant distance between the tip and the surface. In this system, nanometric adjustments should be made in order to sense topographies at the same scale with an appropriate resolution. These kinds of devices varies its properties through short periods of time, and it is required a control algorithm capable of handle these changes. In this work a fuzzy logic control scheme is proposed in order to manage the changes the device might have through the time, and to counter the effects of the non-linearity as well. Two inputs are used to program the rules inside the fuzzy logic controller, the difference between the reference signal and the sample signal (error, and the speed in which it decreases or increases. A lock-in amplifier is used as data acquisition hardware to sample the high frequency signals used to produce the tuning fork oscillations. Once these variables are read the control algorithm calculate a voltage output to move the piezoelectric device, approaching or removing the tip-probe from the sample analyzed.
Energy Technology Data Exchange (ETDEWEB)
Velez D, D
2000-07-01
This work presents a fuzzy logic controller design for neutron power control, from its source to its full power level, applied to a nuclear reactor model. First, we present the basic definitions on fuzzy sets as generalized definitions of the crisp (non fuzzy) set theory. Likewise, we define the basic operations on fuzzy sets (complement, union, and intersection), and the operations on fuzzy relations such as projection and cylindrical extension operations. Furthermore, some concepts of the fuzzy control theory, such as the main modules of the typical fuzzy controller structure and its internal variables, are defined. After the knowledge base is obtained by simulation of the reactor behavior, where the controlled system is modeled by a simple nonlinear reactor model, this model is used to infer a set of fuzzy rules for the reactor response to different insertions of reactivity. The reduction of the response time, using fuzzy rule based controllers on this reactor, is possible by adjusting the output membership functions, by selecting fuzzy rule sets, or by increasing the number of crisp inputs to the fuzzy controller. System characteristics, such as number of rules, response times, and safety parameter values, were considered in the evaluation of each controller merits. Different fuzzy controllers are designed to attain the desired power level, to maintain a constant level for long periods of time, and to keep the reactor away from a shutdown condition. The basic differences among the controllers are the number of crisp inputs and the novel implementation of a crisp power level-based selection of different sets of output membership functions. Simulation results highlight, mainly: (1) A decrease of the response variations at low power level, and (2) a decrease in the time required to attain the desired neutron power. Finally, we present a comparative study of different fuzzy control algorithms applied to a nuclear model. (Author)
Tan, Chao; Xu, Rongxin; Wang, Zhongbin; Si, Lei; Liu, Xinhua
2016-01-01
In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement of coal floor deformation is analyzed and a model is built. Then, the framework of proposed approach is built. Moreover, the constituents of GA such as tangent function roulette wheel selection (Tan-RWS) selection, uniform crossover, and nonuniform mutation are employed to enhance the performance of GFLC. Finally, two simulation examples and an industrial application example are carried out and the results indicate that the proposed method is feasible and efficient.
Directory of Open Access Journals (Sweden)
Muhammad Taufiq Ramadhan
2015-03-01
Full Text Available Penggunaan mobil listrik secara umum terkendala pada beban, kecepatan aktual, serta efisiensi energi. Pemanfaatan Fuzzy Logic Controller untuk pengaturan kecepatan motor DC pada mobil listrik diperlukan untuk meraih kecepatan aktual yang lebih presisi sehingga diperoleh efisiensi energi. Selain itu perlu juga menggunakan Bidirectional Buck-Boost Cascade Converter untuk pengaturan motor DC secara bidirectional, yakni pengaturan saat motoring dan saat pengereman regeneratif (regenerative braking. Hal ini berdasar pada energi yang terbuang percuma, baik itu rugi elektris maupun rugi mekanis saat pengereman.
Fuzzy Logic Unmanned Air Vehicle Motion Planning
Directory of Open Access Journals (Sweden)
Chelsea Sabo
2012-01-01
Full Text Available There are a variety of scenarios in which the mission objectives rely on an unmanned aerial vehicle (UAV being capable of maneuvering in an environment containing obstacles in which there is little prior knowledge of the surroundings. With an appropriate dynamic motion planning algorithm, UAVs would be able to maneuver in any unknown environment towards a target in real time. This paper presents a methodology for two-dimensional motion planning of a UAV using fuzzy logic. The fuzzy inference system takes information in real time about obstacles (if within the agent's sensing range and target location and outputs a change in heading angle and speed. The FL controller was validated, and Monte Carlo testing was completed to evaluate the performance. Not only was the path traversed by the UAV often the exact path computed using an optimal method, the low failure rate makes the fuzzy logic controller (FLC feasible for exploration. The FLC showed only a total of 3% failure rate, whereas an artificial potential field (APF solution, a commonly used intelligent control method, had an average of 18% failure rate. These results highlighted one of the advantages of the FLC method: its adaptability to complex scenarios while maintaining low control effort.
Directory of Open Access Journals (Sweden)
Rafik Lasri
2016-12-01
Full Text Available The electrical energy distribution uses a huge network to cover the urbanized areas. The network distribution incorporates an important number of electrical cells that ensure the energy transformation. These cells play a fundamental role to ensure a permanent feeding. Thus, the performance of these cells must be optimized. The main problem that affects these cells is the inside humidity that should be controlled permanently to prevent serious damage and power failure. The presented work proposes the use of a powerful intelligent Fuzzy Logic Controller that can online adapt their internal parameters according to the actually state of the controlled plant and auto-learn from the behavior of the plant how the current humidity level can be decreased. The used controller can stabilize the humidity inside the cells within the recommended range by controlling a set of heating resistances installed inside these cells and in the same time ensuring valuable advantages for the electrical energy distribution company. Unlike the rest of the controllers that are used to stabilize moisture. The intelligent controller used in these papers ensures a very precise control with very low power consumption which trains a very significant energy savings in each electrical cell. Knowing that the distribution network incorporates a very large number of electrical cells, the final savings balance would be a very high amount of energy that can be presented economically with significant savings on the electricity bills.
DEFF Research Database (Denmark)
Mauricio Iglesias, Miguel; Vangsgaard, Anna Katrine; Gernaey, Krist
Diagnosis and control modules based on fuzzy set theory were tested for novel bioreactor monitoring and control. Two independent modules were used jointly to carry out first the diagnosis of the state of the system and then use transfer this information to control the reactor. The separation...... in diagnosis and control allowed a more intuitive design of the membership functions and the production rules. Hence, the resulting diagnosis-control module is simple to tune, update and maintain while providing a good control performance. In particular the diagnosis-control system was designed for a complete...
Controlling mechanical ventilation in acute respiratory distress syndrome with fuzzy logic.
Nguyen, Binh; Bernstein, David B; Bates, Jason H T
2014-08-01
The current ventilatory care goal for acute respiratory distress syndrome (ARDS) and the only evidence-based approach for managing ARDS is to ventilate with a tidal volume (VT) of 6 mL/kg predicted body weight (PBW). However, it is not uncommon for some caregivers to feel inclined to deviate from this strategy for one reason or another. To accommodate this inclination in a rationalized manner, we previously developed an algorithm that allows for VT to depart from 6 mL/kg PBW based on physiological criteria. The goal of the present study was to test the feasibility of this algorithm in a small retrospective study. Current values of peak airway pressure, positive end-expiratory pressure (PEEP), and arterial oxygen saturation are used in a fuzzy logic algorithm to decide how much VT should differ from 6 mL/kg PBW and how much PEEP should change from its current setting. We retrospectively tested the predictions of the algorithm against 26 cases of decision making in 17 patients with ARDS. Differences between algorithm and physician VT decisions were within 2.5 mL/kg PBW, except in 1 of 26 cases, and differences between PEEP decisions were within 2.5 cm H2O, except in 3 of 26 cases. The algorithm was consistently more conservative than physicians in changing VT but was slightly less conservative when changing PEEP. Within the limits imposed by a small retrospective study, we conclude that our fuzzy logic algorithm makes sensible decisions while at the same time keeping practice close to the current ventilatory care goal. Copyright © 2014 Elsevier Inc. All rights reserved.
Maekawa, Koji; Takahara, Kenji; Kajiwara, Toshinori; Watanabe, Masao
This paper proposes a control system to keep hydrogen generation by a reaction between water and activated aluminum particles at desired level. Because the activated aluminum particles are produced shredded aluminum sawdust, the characteristics of hydrogen generation vary depending on its samples. Therefore, the fuzzy control system to determine the quantum of the activated aluminum particles is designed based on the measured characteristics of hydrogen generation. Error form a desired value, error rate and dead time of the reaction are chosen as the labels of the proposed fuzzy membership functions. The reactor vessel that the activated aluminum particles are put into is developed to generate hydrogen continuously. Three types of aluminum particles of the characteristic are used for the experiments. The proposed system is confirmed to be useful for the control of hydrogen generation, coping with the effect of reacting characteristic changes according to the activated aluminum samples.
Fifty years of fuzzy logic and its applications
Rishe, Naphtali; Kandel, Abraham
2015-01-01
This book presents a comprehensive report on the evolution of Fuzzy Logic since its formulation in Lotfi Zadeh’s seminal paper on “fuzzy sets,” published in 1965. In addition, it features a stimulating sampling from the broad field of research and development inspired by Zadeh’s paper. The chapters, written by pioneers and prominent scholars in the field, show how fuzzy sets have been successfully applied to artificial intelligence, control theory, inference, and reasoning. The book also reports on theoretical issues; features recent applications of Fuzzy Logic in the fields of neural networks, clustering, data mining, and software testing; and highlights an important paradigm shift caused by Fuzzy Logic in the area of uncertainty management. Conceived by the editors as an academic celebration of the fifty years’ anniversary of the 1965 paper, this work is a must-have for students and researchers willing to get an inspiring picture of the potentialities, limitations, achievements and accomplishments...
Multi-objective design of fuzzy logic controller in supply chain
Ghane, Mahdi; Tarokh, Mohammad Jafar
2012-08-01
Unlike commonly used methods, in this paper, we have introduced a new approach for designing fuzzy controllers. In this approach, we have simultaneously optimized both objective functions of a supply chain over a two-dimensional space. Then, we have obtained a spectrum of optimized points, each of which represents a set of optimal parameters which can be chosen by the manager according to the importance of objective functions. Our used supply chain model is a member of inventory and order-based production control system family, a generalization of the periodic review which is termed `Order-Up-To policy.' An auto rule maker, based on non-dominated sorting genetic algorithm-II, has been applied to the experimental initial fuzzy rules. According to performance measurement, our results indicate the efficiency of the proposed approach.
A Fuzzy Logic Controller to Increase Fault Ride-Through Capability of Variable Speed Wind Turbines
Directory of Open Access Journals (Sweden)
Geev Mokryani
2012-01-01
Full Text Available A fuzzy controller for improving Fault Ride-Through (FRT capability of Variable Speed Wind Turbines (WTs equipped with Doubly Fed Induction Generator (DFIG is presented. The controller is designed in order to compensate the voltage at the Point of Common Coupling (PCC by regulating the reactive and active power generated by WTs. The performances of the controller are evaluated in some case studies considering a different number of wind farms in different locations. Simulations, carried out on a real 37-bus Italian weak distribution system, confirmed that the proposed controller can enhance the FRT capability in many cases.
A high-speed multiplexer-based fine-grain pipelined architecture for digital fuzzy logic controllers
Rashidi, Bahram; Masoud Sayedi, Sayed
2015-12-01
Design and implementation of a high-speed multiplexer-based fine-grain pipelined architecture for a general digital fuzzy logic controller has been presented. All the operators have been designed at gate level. For the multiplication, a multiplexer-based modified Wallace tree multiplier has been designed, and for the division and addition multiplexer-based non-restoring parallel divider and multiplexer-based Manchester adder have been used, respectively. To further increase the processing speed, fine-grain pipelining technique has been employed. By using this technique, the critical path of the circuit is broken into finer pieces. Based on the proposed architecture, and by using Quartus II 9.1, a sample two-input, one-output digital fuzzy logic controller with eight rules has been successfully synthesised and implemented on Stratix II field programmable gate array. Simulations were carried out using DSP Builder in the MATLAB/Simulink tool at a maximum clock rate of 301.84 MHz.
Energy Technology Data Exchange (ETDEWEB)
Lapolli, Andre L.; Yamagishi, Sueli; Domienikan, Claudio; Schoueri, Roberto M.; Carbonari, Artur W.; Saxena, Rajendra N., E-mail: alapolli@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2009-07-01
The Hyperfine Interaction Laboratory at Instituto de Pesquisas Energeticas e Nucleares (IPEN) has been using Perturbed Angular Correlation (PAC) technique for studying material science for more than 20 years. One of the important aspects of the research involves the study of the behavior of measured properties of samples as a function of temperature. For temperatures higher than room temperature a small resistance furnace is used to heat the sample. The need to carry out the PAC measurement at predefined temperatures steps in a programmed manner is obvious. The present work describes a procedure for the furnace temperature control and automatic data acquisition at different temperatures based on fuzzy logic. The procedure consists in determining the linguistic input (temp, DELTAtemp) and output (pow) variables and their pertinence functions. After defining the variables, an object.oriented program is written in Java language which is an interface between principal data acquisition program and electronic temperature controller of the mini furnace. In addition to the implementation of the class that involves the fuzzy logic and classes with strategic algorithms defined for each temperature range there are classes of communication between systems based on modbus protocol RTU (Remote Terminal Unit) connected to serial interface RS-488. In this manner the applied technology for the development of software permits higher software life requiring only small alterations or implementation of classes in the use with new equipment. (author)
Fuzzy Control Strategies in Human Operator and Sport Modeling
Ivancevic, Tijana T; Markovic, Sasa
2009-01-01
The motivation behind mathematically modeling the human operator is to help explain the response characteristics of the complex dynamical system including the human manual controller. In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal control. As an application of the presented fuzzy strategies, we present a fuzzy-control based tennis simulator.
DEFF Research Database (Denmark)
Aldana, Nelson Leonardo Diaz; Dragicevic, Tomislav; Vasquez, Juan Carlos
2014-01-01
-charge or deep-discharge in one of the energy storage units. Primary control in a microgrid is responsible for power sharing among units; and droop control is typically used in this stage. This paper proposes a modular and decentralized gain-scheduling control strategy based on fuzzy logic that ensures balanced...
Adıgüzel Hydroelectric Power Plant’s Modelling and LoadFrequency Control by Fuzzy Logic Controller
Directory of Open Access Journals (Sweden)
Yüksel Oğuz
2016-08-01
Full Text Available In this study, to realize the load-frequency control according to different loading statuses, modelling of dynamic behaviour of the Adıgüzel Hydroelectric Power Plant (HEPP was made by using the Matlab/Simulink program.By establishing the dynamic model of 36MVA synchronous generator and other components in the system in a manner reflecting its behaviour in the real system, performance of classical controller and self-adjusting fuzzy logic controller in electro-hydraulic governor circuit was examined according to different load statuses. During the simulation works carried out when both control systems closely watched in the fuzzy logic control system according to different loads the frequency of load and the number of frequency have been observed to be stable in short period of time and allowed tolerance limits.
Li, Liang; Ran, Xu; Wu, Kaihui; Song, Jian; Han, Zongqi
2015-06-01
The traction control system (TCS) might prevent excessive skid of the driving wheels so as to enhance the driving performance and direction stability of the vehicle. But if driven on an uneven low-friction road, the vehicle body often vibrates severely due to the drastic fluctuations of driving wheels, and then the vehicle comfort might be reduced greatly. The vibrations could be hardly removed with traditional drive-slip control logic of the TCS. In this paper, a novel fuzzy logic controller has been brought forward, in which the vibration signals of the driving wheels are adopted as new controlled variables, and then the engine torque and the active brake pressure might be coordinately re-adjusted besides the basic logic of a traditional TCS. In the proposed controller, an adjustable engine torque and pressure compensation loop are adopted to constrain the drastic vehicle vibration. Thus, the wheel driving slips and the vibration degrees might be adjusted synchronously and effectively. The simulation results and the real vehicle tests validated that the proposed algorithm is effective and adaptable for a complicated uneven low-friction road.
Puhan, Pratap Sekhar; Ray, Pravat Kumar; Panda, Gayadhar
2016-12-01
This paper presents the effectiveness of 5/5 Fuzzy rule implementation in Fuzzy Logic Controller conjunction with indirect control technique to enhance the power quality in single phase system, An indirect current controller in conjunction with Fuzzy Logic Controller is applied to the proposed shunt active power filter to estimate the peak reference current and capacitor voltage. Current Controller based pulse width modulation (CCPWM) is used to generate the switching signals of voltage source inverter. Various simulation results are presented to verify the good behaviour of the Shunt active Power Filter (SAPF) with proposed two levels Hysteresis Current Controller (HCC). For verification of Shunt Active Power Filter in real time, the proposed control algorithm has been implemented in laboratory developed setup in dSPACE platform.
Emotion Detection from Text using Fuzzy Logic
National Research Council Canada - National Science Library
Saqib Qamar; Parvez Ahmad
2015-01-01
.... Fuzzy logic was developed to deal with concepts that do not have well-defined, sharp boundaries, which theoretically is ideal for emotion as no well-defined boundaries are defined for emotion categories (e. g...
Nursing and fuzzy logic: an integrative review.
Jensen, Rodrigo; Lopes, Maria Helena Baena de Moraes
2011-01-01
This study conducted an integrative review investigating how fuzzy logic has been used in research with the participation of nurses. The article search was carried out in the CINAHL, EMBASE, SCOPUS, PubMed and Medline databases, with no limitation on time of publication. Articles written in Portuguese, English and Spanish with themes related to nursing and fuzzy logic with the authorship or participation of nurses were included. The final sample included 21 articles from eight countries. For the purpose of analysis, the articles were distributed into categories: theory, method and model. In nursing, fuzzy logic has significantly contributed to the understanding of subjects related to: imprecision or the need of an expert; as a research method; and in the development of models or decision support systems and hard technologies. The use of fuzzy logic in nursing has shown great potential and represents a vast field for research.
Fuzzy logic applications in engineering science
Harris, J
2006-01-01
Fuzzy logic is a relatively new concept in science applications. Hitherto, fuzzy logic has been a conceptual process applied in the field of risk management. Its potential applicability is much wider than that, however, and its particular suitability for expanding our understanding of processes and information in science and engineering in our post-modern world is only just beginning to be appreciated. Written as a companion text to the author's earlier volume "An Introduction to Fuzzy Logic Applications", the book is aimed at professional engineers and students and those with an interest in exploring the potential of fuzzy logic as an information processing kit with a wide variety of practical applications in the field of engineering science and develops themes and topics introduced in the author's earlier text.
Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms
Directory of Open Access Journals (Sweden)
L. M. Galantucci
2004-06-01
Full Text Available The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels. The first level of hybridization consists of the development of a Fuzzy controller for the parameters of an assembly or disassembly planner based on GAs. This controller acts on mutation probability and crossover rate in order to adapt their values dynamically while the algorithm runs. The second level consists of the identification of the optimal assembly or disassembly sequence by a Fuzzy function, in order to obtain a closer control of the technological knowledge of the assembly/disassembly process. Two case studies were analyzed in order to test the efficiency of the Fuzzy-GA methodologies.
Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms
Directory of Open Access Journals (Sweden)
L.M. Galantucci
2008-11-01
Full Text Available The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels. The first level of hybridization consists of the development of a Fuzzy controller for the parameters of an assembly or disassembly planner based on GAs. This controller acts on mutation probability and crossover rate in order to adapt their values dynamically while the algorithm runs. The second level consists of the identification of the optimal assembly or disassembly sequence by a Fuzzy function, in order to obtain a closer control of the technological knowledge of the assembly/disassembly process. Two case studies were analyzed in order to test the efficiency of the Fuzzy-GA methodologies.
Directory of Open Access Journals (Sweden)
DR.D. PADMA SUBRAMANIAN
2014-10-01
Full Text Available This paper presents a design of a Single Input Fuzzy Logic Controller (SFLC based Static VAR Compensator (SVC for Dynamic performance enhancement of power systems. The SFLC uses only one input which is the signed distance and has the advantage of reduced number of rules. Improvement of dynamic response by the controller is illustrated in a bifurcation perspective. Bifurcation diagrams of steady state as well as periodic solutions are constructed using continuation method. From the bifurcation diagrams, the existence of various bifurcation points such as, unstable Hopf bifurcation (UHB, stable Hopf bifurcation (SHB, saddle node bifurcation (SNB and period doubling bifurcation (PDB are identified. With the use of tools of nonlinear dynamics, voltage collapse points, and chaotic solutions due to period doublings are unearthed. The effectiveness of the SFL controller over the conventional controller for SVC in delaying the incidence of Hopf bifurcation (HBF, SNB and hence increasing the loadability limit is illustrated for the test system.
Towards the future of fuzzy logic
Trillas, Enric; Kacprzyk, Janusz
2015-01-01
This book provides readers with a snapshot of the state-of-the art in fuzzy logic. Throughout the chapters, key theories developed in the last fifty years as well as important applications to practical problems are presented and discussed from different perspectives, as the authors hail from different disciplines and therefore use fuzzy logic for different purposes. The book aims at showing how fuzzy logic has evolved since the first theory formulation by Lotfi A. Zadeh in his seminal paper on Fuzzy Sets in 1965. Fuzzy theories and implementation grew at an impressive speed and achieved significant results, especially on the applicative side. The study of fuzzy logic and its practice spread all over the world, from Europe to Asia, America and Oceania. The editors believe that, thanks to the drive of young researchers, fuzzy logic will be able to face the challenging goals posed by computing with words. New frontiers of knowledge are waiting to be explored. In order to motivate young people to engage in the ...
Directory of Open Access Journals (Sweden)
S S Patil
2011-04-01
Full Text Available The design and real time implementation of an integrated fuzzy logic controller (IFLC for a multiple-input multiple-output (MIMO system is presented. The design of IFLC for an uncoupled MIMO system has been discussed. This study develops a combination of fuzzy and PID controllers (PIDC to improve the control performance of a two-input-two-output (TITO: angular position, and rotational speed system. These parameters play a vital role in radar-tracking system for military applications. To verify the applicability of proposed controller, two-motor unit plant along with indigenously designed multi-channel analog interface board of 16-bit precision is used. The proposed MIMO control system is interfaced to a PC through its parallel port. The performance of the system is studied by subjecting it to various standard test signals. The IFLC performs better than the other two controllers in tracking the input command for linear as well as nonlinear inputs such as step, square, triangular, and sine waves is observed.Defence Science Journal, 2011, 61(3, pp.219-227, DOI:http://dx.doi.org/10.14429/dsj.61.24
fuzzy control technique fuzzy control technique applied to modified ...
African Journals Online (AJOL)
eobe
ABSTRACT. In this paper, fuzzy control technique is applied to the modified mathematical model for malaria control presented ... be devised for rule-based systems that deals with continuous ... necessary to use fuzzy logic as it is not easy to follow a particular .... point movement and control is realized and designed. (e.g. α1 ...
Boiocchi, Riccardo; Gernaey, Krist V; Sin, Gürkan
2016-10-01
A methodology is developed to systematically design the membership functions of fuzzy-logic controllers for multivariable systems. The methodology consists of a systematic derivation of the critical points of the membership functions as a function of predefined control objectives. Several constrained optimization problems corresponding to different qualitative operation states of the system are defined and solved to identify, in a consistent manner, the critical points of the membership functions for the input variables. The consistently identified critical points, together with the linguistic rules, determine the long term reachability of the control objectives by the fuzzy logic controller. The methodology is highlighted using a single-stage side-stream partial nitritation/Anammox reactor as a case study. As a result, a new fuzzy-logic controller for high and stable total nitrogen removal efficiency is designed. Rigorous simulations are carried out to evaluate and benchmark the performance of the controller. The results demonstrate that the novel control strategy is capable of rejecting the long-term influent disturbances, and can achieve a stable and high TN removal efficiency. Additionally, the controller was tested, and showed robustness, against measurement noise levels typical for wastewater sensors. A feedforward-feedback configuration using the present controller would give even better performance. In comparison, a previously developed fuzzy-logic controller using merely expert and intuitive knowledge performed worse. This proved the importance of using a systematic methodology for the derivation of the membership functions for multivariable systems. These results are promising for future applications of the controller in real full-scale plants. Furthermore, the methodology can be used as a tool to help systematically design fuzzy logic control applications for other biological processes.
Ramesh, Tejavathu; Panda, A. K.; Kumar, S. Shiva
2013-08-01
In this research study, the performance of direct torque and flux control induction motor drive (IMD) is presented using five different speed control techniques. The performance of IMD mainly depends on the design of speed controller. The PI speed controller requires precise mathematical model, continuous and appropriate gain values. Therefore, adaptive control based speed controller is desirable to achieve high-performance drive. The sliding-mode speed controller (SMSC) is developed to achieve continuous control of motor speed and torque. Furthermore, the type-1 fuzzy logic speed controller (T1FLSC), type-1 fuzzy SMSC and a new type-2 fuzzy logic speed controller are designed to obtain high performance, dynamic tracking behaviour, speed accuracy and also robustness to parameter variations. The performance of each control technique has been tested for its robustness to parameter uncertainties and load disturbances. The detailed comparison of different control schemes are carried out in a MATALB/Simulink environment at different speed operating conditions, such as, forward and reversal motoring under no-load, load and sudden change in speed.
Active Force with Fuzzy Logic Control of a Two-Link Arm Driven by Pneumatic Artificial Muscles
Institute of Scientific and Technical Information of China (English)
H. Jahanabadi; M. Mailah; M. Z. Md Zain; H. M. Hooi
2011-01-01
In this paper,the practicality and feasibility of Active Force Control (AFC) integrated with Fuzzy Logic(AFCAFL) appliedto a two link planar arm actuated by a pair of Pneumatic Artificial Muscle (PAM) is investigated.The study emphasizes on the application and control of PAM actuators which may be considered as the new generation of actuators comprising fluidic muscle that has high-tension force,high power to weight ratio and high strength in spite of its drawbacks in the form of high nonlinearity behaviour,high hysteresis and time varying parameters.Fuzzy Logic (FL) is used as a technique to estimate the best value of the inertia matrix of robot arm essential for the AFC mechanism that is complemented with a conventional Proportional-Integral-Derivative (PID) control at the outermost loop.A simulation study was first performed followed by an experimental investigation for validation.The experimental study was based on the independent joint tracking control and coordinated motion control of the arm in Cartesian or task space.In the former,the PAM actuated arm is commanded to track the prescribed trajectories due to harmonic excitations at the joints for a given frequency,whereas for the latter,two sets of trajectories with different loadings were considered.A practical rig utilizing a Hardware-In-The-Loop Simulation (H1LS) configuration was developed and a number of experiments were carried out.The results of the experiment and the simulation works were in good agreement,which verified the effectiveness and robustness of the proposed AFCAFL scheme actuated by PAM.
Energy Technology Data Exchange (ETDEWEB)
Doellen, U.C. von [Lehrstuhl fuer Regelungssysteme und Steuerungstechnik, Bochum Univ. (Germany); Knof, R. [Noack Entsorgung GmbH, Bochum (Germany); Murmann, C. [VEW AG, Dortmund (Germany). Bereich Gastechnik
1994-12-31
Control and supervision of widespread gas distribution networks requires a great deal of planning and decision making. This task, the so-called gas-dispatching, is determined by an enormous set of various not only technical but also economical boundary conditions. This paper presents a new network control system that was realized for VEW AG one of the most important German gas suppliers. The connection and coordination of formerly isolated subprocesses using fuzzy logic is described, the adaptation of this high-level supervision to the existing process control system leads to remarkable improvement of gas-dispatching. (orig.) [Deutsch] Die Fuehrung und Ueberwachung ausgedehnter Gasversorgungsnetze erfordert einen umfangreichen Planungs- und Entscheidungsablauf. Diese als Gas-Dispatching bezeichnete Aufgabe wird durch eine Vielzahl technischer und wirtschaftlicher Randbedingungen beeinflusst. Der Beitrag stellt eine fuer das Leitungs- und Speichersystem eines der groessten regionalen Gasversorgungsunternehmen der Bundesrepublik, der Vereinigten Elektrizitaetswerke Westfalen AG in Dortmund (VEW), entwickelte Netzregelung vor. Er beschreibt die informatorische Verkopplung bestehender Einzelprozesse mit Hilfe der Fuzzy-Logik. Durch die Integration dieser Koordinationsfunktion in das bestehende Leitsystem wird eine uebergeordnete Optimierung des Gasversorgungsprozesses erreicht. (orig.)
Directory of Open Access Journals (Sweden)
Latha. S. C
2014-11-01
Full Text Available The portable devices development of semiconductor manufacturing technology, conversion efficiency, power consumption, and the size of devices have become the most important design criteria of switching power converters. For portable applications better conveniences extension of battery life and improves the conversion efficiency of power converters .It is essential to develop accurate switching power converters, which can reduce more wasted power energy. The proposed topology can achieve faster transient responses when the supply voltages are changed for the converter by making use of the feed forward network .With mode select circuit the conduction & switching losses are reduced the positive buck–boost converter operate in buck, buck–boost, or boost converter. By adding feed-forward techniques, the proposed converter can improve transient response when the supply voltages are changed. The designing, modeling & experimental results were verified in MATLAB/ Simulink. The fuzzy logic controller is used as controller.
Fuzzy logic an introductory course for engineering students
Trillas, Enric
2015-01-01
This book introduces readers to fundamental concepts in fuzzy logic. It describes the necessary theoretical background and a number of basic mathematical models. Moreover, it makes them familiar with fuzzy control, an important topic in the engineering field. The book offers an unconventional introductory textbook on fuzzy logic, presenting theory together with examples and not always following the typical mathematical style of theorem-corollaries. Primarily intended to support engineers during their university studies, and to spark their curiosity about fuzzy logic and its applications, the book is also suitable for self-study, providing a valuable resource for engineers and professionals who deal with imprecision and non-random uncertainty in real-world applications.
Directory of Open Access Journals (Sweden)
Chandra Babu Paduchuri
2014-01-01
Full Text Available This paper proposes the instantaneous p-q theory based fuzzy logic controller (FLC for multi converter unified power quality conditioner (MC-UPQC to mitigate power quality issues in two feeders three-phase four-wire distribution systems. The proposed system is extended system of the existing one feeder three-phase four-wire distribution system, which is operated with UPQC. This system is employed with three voltage source converters, which are connected commonly to two feeder distribution systems. The performance of this proposed system used to compensate voltage sag, neutral current mitigation and compensation of voltage and current harmonics under linear and nonlinear load conditions. The neutral current flowing in series transformers is zero in the implementation of the proposed system. The simulation performance analysis is carried out using MATLAB.
Directory of Open Access Journals (Sweden)
José Raúl Castro
2016-02-01
Full Text Available This paper presents an efficient algorithm to solve the multi-objective (MO voltage control problem in distribution networks. The proposed algorithm minimizes the following three objectives: voltage variation on pilot buses, reactive power production ratio deviation, and generator voltage deviation. This work leverages two optimization techniques: fuzzy logic to find the optimum value of the reactive power of the distributed generation (DG and Pareto optimization to find the optimal value of the pilot bus voltage so that this produces lower losses under the constraints that the voltage remains within established limits. Variable loads and DGs are taken into account in this paper. The algorithm is tested on an IEEE 13-node test feeder and the results show the effectiveness of the proposed model.
The design of thermoelectric footwear heating system via fuzzy logic.
Işik, Hakan; Saraçoğlu, Esra
2007-12-01
In this study, Heat Control of Thermoelectric Footwear System via Fuzzy Logic has been implemented in order to use efficiently in cold weather conditions. Temperature control is very important in domestic as well as in many industrial applications. The final product is seriously affected from the changes in temperature. So it is necessary to reach some desired temperature points quickly and avoid large overshoot. Here, fuzzy logic acts an important role. PIC 16F877 microcontroller has been designed to act as fuzzy logic controller. The designed system provides energy saving and has better performance than proportional control that was implemented in the previous study. The designed system takes into consideration so appropriate parameters that it can also be applied to the people safely who has illnesses like diabetes, etc.
Favieiro, Gabriela W; Balbinot, Alexandre
2011-01-01
The myoelectric signal is a sign of control of the human body that contains the information of the user's intent to contract a muscle and, therefore, make a move. Studies shows that the Amputees are able to generate standardized myoelectric signals repeatedly before of the intention to perform a certain movement. This paper presents a study that investigates the use of forearm surface electromyography (sEMG) signals for classification of five distinguish movements of the arm using just three pairs of surface electrodes located in strategic places. The classification is done by an adaptive neuro-fuzzy inference system (ANFIS) to process signal features to recognize performed movements. The average accuracy reached for the classification of five motion classes was 86-98% for three subjects.
FUZZY-LOGIC BASED CALL ADMISSION CONTROL FOR A HETEROGENEOUS RADIO ENVIRONMENT
DEFF Research Database (Denmark)
Ramkumar, Venkata; Mihovska, Albena D.; Prasad, Neeli R.;
Dette dokument foreslår et nyt opkald Admission Control (CAC) algoritme, der finder forskellige typer af applikationer med forskellige QoS parametre, som en bruger og giver de nødvendige QoS til nyankomne brugere uden en forringelse af de QoS at der allerede er optaget dem. Den foreslåede CAC er...... evalueret for en heterogen radio access-teknologier (rotter) scenario. Den QoS parametre varierer afhængigt af den type af ansøgninger, og aftalen mellem udbyderen og brugeren. Den foreslåede CAC er baseret på en fuzzy logik mekanisme, der består af to etaper, i første omgang den bedste celle i hver RAT er...
Genetic Algorithm Tuned Fuzzy Logic for Gliding Return Trajectories
Burchett, Bradley T.
2003-01-01
The problem of designing and flying a trajectory for successful recovery of a reusable launch vehicle is tackled using fuzzy logic control with genetic algorithm optimization. The plant is approximated by a simplified three degree of freedom non-linear model. A baseline trajectory design and guidance algorithm consisting of several Mamdani type fuzzy controllers is tuned using a simple genetic algorithm. Preliminary results show that the performance of the overall system is shown to improve with genetic algorithm tuning.
A Brief History of Fuzzy Logic
Directory of Open Access Journals (Sweden)
Angel Garrido
2012-04-01
Full Text Available
The problems of uncertainty, imprecision and vagueness have been discussed for many years. These problems have been major topics in philosophical circles with much debate, in particular, about the nature of vagueness and the ability of traditional Boolean logic to cope with concepts and perceptions that are imprecise or vague. The Fuzzy Logic (which is usually translated into Castilian by “Lógica Borrosa”, or “Lógica Difusa”, but also by “Lógica Heurística” can be considered a bypass-valued logics (Multi-valued Logic, MVL, its acronym in English. It is founded on, and is closely related to-Fuzzy Sets Theory, and successfully applied on Fuzzy Systems. You might think that fuzzy logic is quite recent and what has worked for a short time, but its origins date back at least to the Greek philosophers and especially Plato (428-347 B.C.. It even seems plausible
to trace their origins in China and India. Because it seems that they were the first to consider that all things need not be of a certain type or quit, but there are a stopover between. That is, be the pioneers in considering that there may be varying degrees of truth and falsehood. In case of colors, for example, between white and black there is a whole infinite scale: the shades of gray. Some recent theorems show that in principle fuzzy logic can be used to model any continuous system, be it based
in AI, or physics, or biology, or economics, etc. Investigators in many fields may find that fuzzy, commonsense models are more useful, and many more accurate than are standard mathematical ones. We analyze here the history and development of this problem: Fuzziness, or “Borrosidad” (in Castilian, essential to work with Uncertainty.
Ramesh, Tejavathu; Kumar Panda, Anup; Shiva Kumar, S
2015-07-01
In this research study, a model reference adaptive system (MRAS) speed estimator for speed sensorless direct torque and flux control (DTFC) of an induction motor drive (IMD) using two adaptation mechanism schemes are proposed to replace the conventional proportional integral controller (PIC). The first adaptation mechanism scheme is based on Type-1 fuzzy logic controller (T1FLC), which is used to achieve high performance sensorless drive in both transient as well as steady state conditions. However, the Type-1 fuzzy sets are certain and unable to work effectively when higher degree of uncertainties presents in the system which can be caused by sudden change in speed or different load disturbances, process noise etc. Therefore, a new Type-2 fuzzy logic controller (T2FLC) based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties and improves the performance and also robust to various load torque and sudden change in speed conditions, respectively. The detailed performances of various adaptation mechanism schemes are carried out in a MATLAB/Simulink environment with a speed sensor and speed sensorless modes of operation when an IMD is operating under different operating conditions, such as, no-load, load and sudden change in speed, respectively. To validate the different control approaches, the system also implemented on real-time system and adequate results are reported for its validation.
Directory of Open Access Journals (Sweden)
Abdelhak Dida
2015-02-01
Full Text Available This paper proposes a novel variable speed control algorithm for a grid connected doubly-fed induction generator (DFIG system. The main objective is to track the maximum power curve characteristic by using an adaptive fuzzy logic controller, and to compare it with the conventional optimal torque control method for large inertia wind turbines. The role of the FLC is to adapt the transfer function of the harvested mechanical power controller according to the operating point in variable wind speed. The control system has two sub-systems for the rotor side and the grid side converters (RSC, GSC. Active and reactive power control of the back-to-back converters has been achieved indirectly by controlling q-axis and d-axis current components. The main function of the RSC controllers is to track the maximum power through controlling the electromagnetic torque of the wind turbine. The GSC controls the DC-link voltage, and guarantees unity power factor between the GSC and the grid. The proposed system is developed and tested in MATLAB/SimPowerSystem (SPS environment.
Fuzzy logic-based diversity-controlled self-adaptive differential evolution
Amali, S. Miruna Joe; Baskar, S.
2013-08-01
This article presents a novel method using a fuzzy system (FS) to control the population diversity during the various phases of evolution. A local search is applied at regular intervals on an individual selected at random to aid the population in convergence. This diversity control methodology is applied to vary the crossover rate of self-adaptive differential evolution (SaDE). Three variants of the SaDE algorithm are proposed: (1) diversity-controlled SaDE (DCSaDE); (2) SaDE with local search (SaDE-LS); and (3) diversity-controlled SaDE with local search (DCSaDE-LS). The performance of the proposed algorithms is analysed using a set of unconstrained benchmark functions with respect to average function evaluations, success rate and the mean of the objectives of 30 independent trials. The DCSaDE-LS algorithm had a better success rate for high-dimensional multimodal problems and conserved the number of function evaluations required for most of the problems. It is compared with other popular algorithms and the outcome of the proposed DCSaDE-LS algorithm is validated using non-parametric statistical tests. MATLAB codes for the proposed algorithms may be obtained on request.
Energy Technology Data Exchange (ETDEWEB)
Lagunas, J.; Caratozzolo, P.; Ortega, C.; Gonzalez, R.
2004-07-01
This paper presents and validates the use of a fuzzy-logic-based supervisory controller for the management of energy in a hybrid system. The general configuration of the hybrid system is presented as well as the operational objectives of the supervisory controller. The inputs and outputs of the controller are also presented along with the hierarchical structure employed in order to reduce the number of rules in the knowledge base. The results obtained are compared against those of a conventional controller. Simulations were carried out using Matlab. (Author)
Navigating a Mobile Robot Across Terrain Using Fuzzy Logic
Seraji, Homayoun; Howard, Ayanna; Bon, Bruce
2003-01-01
A strategy for autonomous navigation of a robotic vehicle across hazardous terrain involves the use of a measure of traversability of terrain within a fuzzy-logic conceptual framework. This navigation strategy requires no a priori information about the environment. Fuzzy logic was selected as a basic element of this strategy because it provides a formal methodology for representing and implementing a human driver s heuristic knowledge and operational experience. Within a fuzzy-logic framework, the attributes of human reasoning and decision- making can be formulated by simple IF (antecedent), THEN (consequent) rules coupled with easily understandable and natural linguistic representations. The linguistic values in the rule antecedents convey the imprecision associated with measurements taken by sensors onboard a mobile robot, while the linguistic values in the rule consequents represent the vagueness inherent in the reasoning processes to generate the control actions. The operational strategies of the human expert driver can be transferred, via fuzzy logic, to a robot-navigation strategy in the form of a set of simple conditional statements composed of linguistic variables. These linguistic variables are defined by fuzzy sets in accordance with user-defined membership functions. The main advantages of a fuzzy navigation strategy lie in the ability to extract heuristic rules from human experience and to obviate the need for an analytical model of the robot navigation process.
Fault Diagnosis in Deaerator Using Fuzzy Logic
Directory of Open Access Journals (Sweden)
S Srinivasan
2007-01-01
Full Text Available In this paper a fuzzy logic based fault diagnosis system for a deaerator in a power plant unit is presented. The system parameters are obtained using the linearised state space deaerator model. The fuzzy inference system is created and rule base are evaluated relating the parameters to the type and severity of the faults. These rules are fired for specific changes in system parameters and the faults are diagnosed.
Boudjema, Zinelaabidine; Taleb, Rachid; Bounadja, Elhadj
2017-02-01
Traditional filed oriented control strategy including proportional-integral (PI) regulator for the speed drive of the doubly fed induction motor (DFIM) have some drawbacks such as parameter tuning complications, mediocre dynamic performances and reduced robustness. Therefore, based on the analysis of the mathematical model of a DFIM supplied by two five-level SVPWM inverters, this paper proposes a new robust control scheme based on super twisting sliding mode and fuzzy logic. The conventional sliding mode control (SMC) has vast chattering effect on the electromagnetic torque developed by the DFIM. In order to resolve this problem, a second order sliding mode technique based on super twisting algorithm and fuzzy logic functions is employed. The validity of the employed approach was tested by using Matlab/Simulink software. Interesting simulation results were obtained and remarkable advantages of the proposed control scheme were exposed including simple design of the control system, reduced chattering as well as the other advantages.
Fan, Shou-Zen; Shieh, Jiann-Shing
2014-01-01
We compare type-1 and type-2 self-organizing fuzzy logic controller (SOFLC) using expert initialized and pretrained extracted rule-bases applied to automatic control of anaesthesia during surgery. We perform experimental simulations using a nonfixed patient model and signal noise to account for environmental and patient drug interaction uncertainties. The simulations evaluate the performance of the SOFLCs in their ability to control anesthetic delivery rates for maintaining desired physiological set points for muscle relaxation and blood pressure during a multistage surgical procedure. The performances of the SOFLCs are evaluated by measuring the steady state errors and control stabilities which indicate the accuracy and precision of control task. Two sets of comparisons based on using expert derived and extracted rule-bases are implemented as Wilcoxon signed-rank tests. Results indicate that type-2 SOFLCs outperform type-1 SOFLC while handling the various sources of uncertainties. SOFLCs using the extracted rules are also shown to outperform those using expert derived rules in terms of improved control stability. PMID:25587533
Directory of Open Access Journals (Sweden)
Xingguo Lu
2016-05-01
Full Text Available In this work, we propose a new method for the optimal design and tuning of a Proportional-Integral-Derivative type (PID-type interval type-2 fuzzy logic controller (IT2 FLC for Delta parallel robot trajectory tracking control. The presented methodology starts with an optimal design problem of IT2 FLC. A group of IT2 FLCs are obtained by blurring the membership functions using a variable called blurring degree. By comparing the performance of the controllers, the optimal structure of IT2 FLC is obtained. Then, a multi-objective optimization problem is formulated to tune the scaling factors of the PID-type IT2 FLC. The Non-dominated Sorting Genetic Algorithm (NSGA-II is adopted to solve the constrained nonlinear multi-objective optimization problem. Simulation results of the optimized controller are presented and discussed regarding application in the Delta parallel robot. The proposed method provides an effective way to design and tune the PID-type IT2 FLC with a desired control performance.
Directory of Open Access Journals (Sweden)
Xingguo Lu
2016-05-01
Full Text Available In this work, we propose a new method for the optimal design and tuning of a Proportional Integral-Derivative type (PID-type interval type-2 fuzzy logic controller (IT2 FLC for Delta parallel robot trajectory tracking control. The presented methodology starts with an optimal design problem of IT2 FLC. A group of IT2 FLCs are obtained by blurring the membership functions using a variable called blurring degree. By comparing the performance of the controllers, the optimal structure of IT2 FLC is obtained. Then, a multi-objective optimization problem is formulated to tune the scaling factors of the PID-type IT2 FLC. The Non-dominated Sorting Genetic Algorithm (NSGA-II is adopted to solve the constrained nonlinear multi-objective optimization problem. Simulation results of the optimized controller are presented and discussed regarding application in the Delta parallel robot. The proposed method provides an effective way to design and tune the PID-type IT2 FLC with a desired control performance.
Minimising tremor in a joystick using fuzzy logic
van der Zwaag, B.J.; Corbett, Dan; Jain, Lakhmi; Kappen, H.J.; Duin, R.P.W.; Krose, B.J.A.; Segeth, W.
We have designed and built a fuzzy logic controller which minimises the effect of Multiple Sclerosis (MS) hand tremors. The aim of our project has been to give people with Multiple Sclerosis better control of an electronic wheelchair by removing tremors from the joystick signal. The system
Minimising tremor in a joystick using fuzzy logic
Zwaag, van der Berend-Jan; Corbett, Dan; Jain, Lakhmi
1999-01-01
We have designed and built a fuzzy logic controller which minimises the effect of Multiple Sclerosis (MS) hand tremors. The aim of our project has been to give people with Multiple Sclerosis better control of an electronic wheelchair by removing tremors from the joystick signal. The system intercept
Pattern recognition using linguistic fuzzy logic predictors
Habiballa, Hashim
2016-06-01
The problem of pattern recognition has been solved with numerous methods in the Artificial Intelligence field. We present an unconventional method based on Lingustic Fuzzy Logic Forecaster which is primarily used for the task of time series analysis and prediction through logical deduction wtih linguistic variables. This method should be used not only to the time series prediction itself, but also for recognition of patterns in a signal with seasonal component.
CAC Algorithm Based on Fuzzy Logic
Directory of Open Access Journals (Sweden)
Ľubomír DOBOŠ
2009-05-01
Full Text Available Quality of Service (QoS represent one ofmajor parameters that describe mobile wirelesscommunication systems. Thanks growing popularity ofmobile communication in last years, there is anincreasing expansion of connection admission controlschemes (CAC that plays important role in QoSdelivering in terms of connection blocking probability,connection dropping probability, data loss rate andsignal quality.With expansion of services provided by the mobilenetworks growing the requirements to QoS andtogether growing requirements to CAC schemes.Therefore, still more sophisticated CAC schemes arerequired to guarantee the QoS. This paper containsshort introduction into division of connectionadmission control schemes and presents thresholdoriented CAC scheme with fuzzy logic used foradaptation of the threshold value.
Directory of Open Access Journals (Sweden)
Selami KESLER
2009-01-01
Full Text Available The power flow of the rotor circuit is controlled by different methods in induction machines used for producing high torque in applications involved great power and constant output power with constant frequency in wind turbines. The voltage with slip frequency can be applied on rotor windings to produce controlled high torque and obtain optimal power factor and speed control. In this study, firstly, the dynamic effects of the voltage applying on rotor windings through the rings in slip-ring induction machines are researched and undesirable aspects of the method are exposed with simulations supported by experiments. Afterwards, a fuzzy logic based inverter model on rotor side is proposed with a view to improving the dynamic effects, controlling high torque producing and adjusting machine speed in instantaneous forced conditions. For the simulation model of the system in which the stator side is directly connected to the grid in steady state operation, a C/C++ algorithm is developed and the results obtained for different load conditions are discussed.
Fuzzy logic and neural networks basic concepts & application
Alavala, Chennakesava R
2008-01-01
About the Book: The primary purpose of this book is to provide the student with a comprehensive knowledge of basic concepts of fuzzy logic and neural networks. The hybridization of fuzzy logic and neural networks is also included. No previous knowledge of fuzzy logic and neural networks is required. Fuzzy logic and neural networks have been discussed in detail through illustrative examples, methods and generic applications. Extensive and carefully selected references is an invaluable resource for further study of fuzzy logic and neural networks. Each chapter is followed by a question bank
Fuzzy logic systems are equivalent to feedforward neural networks
Institute of Scientific and Technical Information of China (English)
李洪兴
2000-01-01
Fuzzy logic systems and feedforward neural networks are equivalent in essence. First, interpolation representations of fuzzy logic systems are introduced and several important conclusions are given. Then three important kinds of neural networks are defined, i.e. linear neural networks, rectangle wave neural networks and nonlinear neural networks. Then it is proved that nonlinear neural networks can be represented by rectangle wave neural networks. Based on the results mentioned above, the equivalence between fuzzy logic systems and feedforward neural networks is proved, which will be very useful for theoretical research or applications on fuzzy logic systems or neural networks by means of combining fuzzy logic systems with neural networks.
Indeterminacy, linguistic semantics and fuzzy logic
Energy Technology Data Exchange (ETDEWEB)
Novak, V. [Univ. of Ostrava (Czech Republic)
1996-12-31
In this paper, we discuss the indeterminacy phenomenon which has two distinguished faces, namely uncertainty modeled especially by the probability theory and vagueness, modeled by fuzzy logic. Other important mathematical model of vagueness is provided by the Alternative Set Theory. We focus on some of the basic concepts of these theories in connection with mathematical modeling of the linguistic semantics.
Automating Software Development Process using Fuzzy Logic
Marcelloni, Francesco; Aksit, Mehmet; Damiani, Ernesto; Jain, Lakhmi C.; Madravio, Mauro
2004-01-01
In this chapter, we aim to highlight how fuzzy logic can be a valid expressive tool to manage the software development process. We characterize a software development method in terms of two major components: artifact types and methodological rules. Classes, attributes, operations, and inheritance an
Fuzzy Logic System for Slope Stability Prediction
Directory of Open Access Journals (Sweden)
Tarig Mohamed
2012-01-01
Full Text Available The main goal of this research is to predict the stability of slopes using fuzzy logic system. GeoStudio, a commercially available software was used to compute safety factors for various designs of slope. The general formulation of the software could analyze slope stability using various methods of analysis i.e. Morgenstern-Price, Janbu, Bishop and Ordinary to calculate the safety factors. After analyzing, fuzzy logic was used to predict the slope stability. Fuzzy logic is based on natural language and conceptually easy to understand, flexible, tolerant of imprecise data and able to model nonlinear functions of arbitrary complexity. Several important parameters such as height of slope, unit weight of slope material, angle of slope, coefficient of cohesion and internal angle of friction were used as the input parameters, while the factor of safety was the output parameter. A model to test the stability of the slope was generated from the calculated data. This model presented a relationship between input parameters and stability of the slopes. Results showed that the prediction using fuzzy logic was accurate and close to the target data.
Directory of Open Access Journals (Sweden)
VENMATHI, M.
2016-02-01
Full Text Available In this paper, a new four-port DC-DC converter topology is proposed to interface renewable energy sources and the load along with the energy storage device. The proposed four-port SEPIC/ZETA bidirectional converter (FP-SEPIC/ZETA BDC converter comprises an isolated output port with two unidirectional and one bidirectional input ports. This converter topology is obtained by the fusion of SEPIC/ZETA BDC and full-bridge converter. This converter topology ensures the non-reversal of output voltage hence it is preferred mostly for battery charging applications. In this work, photovoltaic (PV source is considered and the power balance in the system is achieved by means of distributed maximum power point tracking (DMPPT in the PV ports. The centralized controller is implemented using fuzzy logic controller (FLC and the performance is compared with conventional proportional integral (PI controller. The results offer useful information to obtain the desired output under line and load regulations. Experimental results are also provided to validate the simulation results.
Neuro-fuzzy Control of Integrating Processes
Directory of Open Access Journals (Sweden)
Anna Vasičkaninová
2011-11-01
Full Text Available Fuzzy technology is adaptive and easily applicable in different areas.Fuzzy logic provides powerful tools to capture the perceptionof natural phenomena. The paper deals with tuning of neuro-fuzzy controllers for integrating plant and for integrating plantswith time delay. The designed approach is verified on three examples by simulations and compared plants with classical PID control.Designed fuzzy controllers lead to better closed-loop control responses then classical PID controllers.
Speech Emotion Recognition Using Fuzzy Logic Classifier
Directory of Open Access Journals (Sweden)
Daniar aghsanavard
2016-01-01
Full Text Available Over the last two decades, emotions, speech recognition and signal processing have been one of the most significant issues in the adoption of techniques to detect them. Each method has advantages and disadvantages. This paper tries to suggest fuzzy speech emotion recognition based on the classification of speech's signals in order to better recognition along with a higher speed. In this system, the use of fuzzy logic system with 5 layers, which is the combination of neural progressive network and algorithm optimization of firefly, first, speech samples have been given to input of fuzzy orbit and then, signals will be investigated and primary classified in a fuzzy framework. In this model, a pattern of signals will be created for each class of signals, which results in reduction of signal data dimension as well as easier speech recognition. The obtained experimental results show that our proposed method (categorized by firefly, improves recognition of utterances.
Automated sensory nerve conduction testing using fuzzy logic.
Gitter, A; Lin, V
1999-01-01
Nerve conduction studies continue to be an important tool in the evaluation of peripheral nerve disorders but have come under increased scrutiny because of heightened cost control in health care service delivery. In selected clinical settings, automated nerve conduction studies may be a useful clinical tool replacing conventional testing, but existing instruments are limited and have not generally been accepted into clinical practice. Further advancements in nerve conduction automation may be possible by incorporating expert system approaches into nerve conduction measurement and control algorithms. Using fuzzy logic techniques to duplicate the reasoning strategies of experienced electrodiagnostic clinicians, a software controller was developed to automatically perform sensory nerve conduction studies. The fuzzy logic system successfully performed 88% of 97 sensory studies in a mixed group of normal and patient populations. Sensory nerve action potential latency and amplitude measures obtained with automated testing were the same as determined by clinicians. Failures were related to design limitations of the controller, noise, and artifact. The high negative predictive value and sensitivity of fuzzy logic based testing suggest that its utility is in minimizing the need for unnecessary conventional electrodiagnostic studies in patients with normal nerve function. Fuzzy logic appears to be a useful approach to nerve conduction automation that can model expert reasoning and judgment.
A STUDY OF FUZZY LOGICAL PETRI NETS AND ITS APPLICATION
Institute of Scientific and Technical Information of China (English)
Jiang Changjun
2001-01-01
In this paper, a fuzzy Petri net approach to modelling fuzzy rule-based reasoning is proposed. Logical Petri net (LPN) and fuzzy logical Petri net (FLPN) are defined. The backward reasoning algorithm based on sub-fuzzy logical Petri net is given. It is simpler than the conventional algorithm of forward reasoning from initial propositions. An application to the partial fault model of a car engine in paper Portinale's(1993) is used as an illustrative example of FLPN.
Directory of Open Access Journals (Sweden)
Xian-Xia Zhang
2013-01-01
Full Text Available This paper presents a reference function based 3D FLC design methodology using support vector regression (SVR learning. The concept of reference function is introduced to 3D FLC for the generation of 3D membership functions (MF, which enhance the capability of the 3D FLC to cope with more kinds of MFs. The nonlinear mathematical expression of the reference function based 3D FLC is derived, and spatial fuzzy basis functions are defined. Via relating spatial fuzzy basis functions of a 3D FLC to kernel functions of an SVR, an equivalence relationship between a 3D FLC and an SVR is established. Therefore, a 3D FLC can be constructed using the learned results of an SVR. Furthermore, the universal approximation capability of the proposed 3D fuzzy system is proven in terms of the finite covering theorem. Finally, the proposed method is applied to a catalytic packed-bed reactor and simulation results have verified its effectiveness.
Hierarchical type-2 fuzzy aggregation of fuzzy controllers
Cervantes, Leticia
2016-01-01
This book focuses on the fields of fuzzy logic, granular computing and also considering the control area. These areas can work together to solve various control problems, the idea is that this combination of areas would enable even more complex problem solving and better results. In this book we test the proposed method using two benchmark problems: the total flight control and the problem of water level control for a 3 tank system. When fuzzy logic is used it make it easy to performed the simulations, these fuzzy systems help to model the behavior of a real systems, using the fuzzy systems fuzzy rules are generated and with this can generate the behavior of any variable depending on the inputs and linguistic value. For this reason this work considers the proposed architecture using fuzzy systems and with this improve the behavior of the complex control problems.
Institute of Scientific and Technical Information of China (English)
LIN; Kuang-Jang; LIN; Chii-Ruey
2010-01-01
The Photovoltaic Array has a best optimal operating point where the array operating can obtain the maximum power.However, the optimal operating point can be compromised by the strength of solar radiation,angle,and by the change of environment and load.Due to the constant changes in these conditions,it has become very difficult to locate the optimal operating point by following a mathematical model.Therefore,this study will focus mostly on the application of Fuzzy Logic Control theory and Three-point Weight Comparison Method in effort to locate the optimal operating point of solar panel and achieve maximum efficiency in power generation. The Three-point Weight Comparison Method is the comparison between the characteristic curves of the voltage of photovoltaic array and output power;it is a rather simple way to track the maximum power.The Fuzzy Logic Control,on the other hand,can be used to solve problems that cannot be effectively dealt with by calculation rules,such as concepts,contemplation, deductive reasoning,and identification.Therefore,this paper uses these two kinds of methods to make simulation successively. The simulation results show that,the Three-point Comparison Method is more effective under the environment with more frequent change of solar radiation;however,the Fuzzy Logic Control has better tacking efficiency under the environment with violent change of solar radiation.
Fuzzy logic based variable speed wind generation system
Energy Technology Data Exchange (ETDEWEB)
Simoes, M.G. [Sao Paulo Univ., SP (Brazil). Escola Politecnica. PMC - Mecatronica; Bose, B.K. [Tennessee Univ., Knoxville, TN (United States). Dept. of Electrical Engineering; Spiegel, Ronal J. [Environmental Protection Agency, Research Triangle Park, NC (United States). Air and Energy Engineering Research Lab.
1996-12-31
This work demonstrates the successful application of fuzzy logic to enhance the performance and control of a variable speed wind generation system. A maximum power point tracker control is performed with three fuzzy controllers, without wind velocity measurement, and robust to wind vortex and turbine torque ripple. A squirrel cage induction generator feeds the power to a double-sided PWM converter system which pumps the power to a utility grid or supplies to an autonomous system. The fuzzy logic controller FLC-1 searches on-line the generator speed so that the aerodynamic efficiency of the wind turbine is optimized. A second fuzzy controller FLC-2 programs the machine flux by on-line search so as to optimize the machine-converter system wind vortex. Detailed analysis and simulation studies were performed for development of the control strategy and fuzzy algorithms, and a DSP TMS320C30 based hardware with C control software was built for the performance evaluation of a laboratory experimental set-up. The theoretical development was fully validated and the system is ready to be reproduced in a higher power installation. (author) 7 refs., 3 figs., 1 tab.
Enhanced Image Segmentation Using Fuzzy Logic
Manpreet singh
2013-01-01
This research work proposed an improved edge detection techniques using fuzzy sets. The problem is to find edges in the image, as a first step in the process of scene reconstruction. Edges are scale-dependent and an edge may comprise other edges, but at a definite scale, an edge still has no width. This paper has presented different edge detection operators and their benefit when they merge with fuzzy logic theory. This paper has achieved the accuracy of edge detection up to 94.89 %. The prop...
Application of fuzzy logic to social choice theory
Mordeson, John N; Clark, Terry D
2015-01-01
Fuzzy social choice theory is useful for modeling the uncertainty and imprecision prevalent in social life yet it has been scarcely applied and studied in the social sciences. Filling this gap, Application of Fuzzy Logic to Social Choice Theory provides a comprehensive study of fuzzy social choice theory.The book explains the concept of a fuzzy maximal subset of a set of alternatives, fuzzy choice functions, the factorization of a fuzzy preference relation into the ""union"" (conorm) of a strict fuzzy relation and an indifference operator, fuzzy non-Arrowian results, fuzzy versions of Arrow's
A fuzzy logic based network intrusion detection system for predicting the TCP SYN flooding attack
CSIR Research Space (South Africa)
Mkuzangwe, Nenekazi NP
2017-04-01
Full Text Available presents a fuzzy logic based network intrusion detection system to predict neptune which is a type of a Transmission Control Protocol Synchronized (TCP SYN) flooding attack. The performance of the proposed fuzzy logic based system is compared to that of a...
Fuzzy Based composition Control of Distillation Column
Directory of Open Access Journals (Sweden)
Guru.R
2013-04-01
Full Text Available This paper proposed a control scheme based on fuzzy logic for a methanol - water system of bubble cap distillation column. Fuzzy rule base and Inference System of fuzzy (FIS is planned to regulatethe reflux ratio (manipulated variable to obtain the preferred product composition (methanol for a distillation column. Comparisons are made with conventional controller and the results confirmed the potentials of the proposed strategy of fuzzy control.
Mauseth, Richard; Lord, Sandra M; Hirsch, Irl B; Kircher, Robert C; Matheson, Don P; Greenbaum, Carla J
2015-09-14
Under controlled conditions, the Dose Safety artificial pancreas (AP) system controller, which utilizes "fuzzy logic" (FL) methodology to calculate and deliver appropriate insulin dosages based on changes in blood glucose, successfully managed glycemic excursions. The aim of this study was to show whether stressing the system with pizza (high carbohydrate/high fat) meals and exercise would reveal deficits in the performance of the Dose Safety FL controller (FLC) and lead to improvements in the dosing matrix. Ten subjects with type 1 diabetes (T1D) were enrolled and participated in 30 studies (17 meal, 13 exercise) using 2 versions of the FLC. After conducting 13 studies with the first version (FLC v2.0), interim results were evaluated and the FLC insulin-dosing matrix was modified to create a new controller version (FLC v2.1) that was validated through regression testing using v2.0 CGM datasets prior to its use in clinical studies. The subsequent 17 studies were performed using FLC v2.1. Use of FLC v2.1 vs FLC v2.0 in the pizza meal tests showed improvements in mean blood glucose (205 mg/dL vs 232 mg/dL, P = .04). FLC v2.1 versus FLC v2.0 in exercise tests showed improvements in mean blood glucose (146 mg/dL vs 201 mg/dL, P = .004), percentage time spent >180 mg/dL (19.3% vs 46.7%, P = .001), and percentage time spent 70-180 mg/dL (80.0% vs 53.3%, P = .002). Stress testing the AP system revealed deficits in the FLC performance, which led to adjustments to the dosing matrix followed by improved FLC performance when retested. © 2015 Diabetes Technology Society.
Fuzzy logic estimator of rotor time constant in induction motors
Energy Technology Data Exchange (ETDEWEB)
Alminoja, J. [Tampere University of Technology (Finland). Control Engineering Laboratory; Koivo, H. [Helsinki University of Technology, Otaniemi (Finland). Control Engineering Laboratory
1997-12-31
Vector control of AC machines is a well-known and widely used technique in induction machine control. It offers an exact method for speed control of induction motors, but it is also sensitive to the changes in machine parameters. E.g. rotor time constant has a strong dependence on temperature. In this paper a fuzzy logic estimator is developed, with which the rotor time constant can be estimated when the machine has a load. It is more simple than the estimators proposed in the literature. The fuzzy estimator is tested by simulation when step-wise abrupt changes and slow drifting occurs. (orig.) 7 refs.
Searching the Arcane Origins of Fuzzy Logic
Directory of Open Access Journals (Sweden)
Angel Garrido
2011-05-01
Full Text Available It is well-known that Artificial Intelligence requires Logic. But its Classical version shows too many insufficiencies. So, it is very necessary to introduce more sophisticated tools, as may be
Fuzzy Logic, Modal Logic, Non-Monotonic Logic, and so on. When you are searching the possible precedent of such new ideas, we may found that they are not totally new, because some ancient thinkers have suggested many centuries ago similar concepts, certainly without adequate mathematical formulation, but in the same line: against the dogmatism and the dualistic vision of
the world: absolutely true vs. absolutely false, black vs. white, good or bad by nature, 0 vs.1, etc. We attempt to analyze here some of these greatly unexplored, and very interesting early origins.
Muniraj, Murali; Arulmozhiyal, Ramaswamy
2015-01-01
A control actuation system has been used extensively in automotive, aerospace, and defense applications. The major challenges in modeling control actuation system are rise time, maximum peak to peak overshoot, and response to nonlinear system with percentage error. This paper addresses the challenges in modeling and real time implementation of control actuation system for missiles glider applications. As an alternative fuzzy-PID controller is proposed in BLDC motor drive followed by linkage mechanism to actuate fins in missiles and gliders. The proposed system will realize better rise time and less overshoot while operating in extreme nonlinear dynamic system conditions. A mathematical model of BLDC motor is derived in state space form. The complete control actuation system is modeled in MATLAB/Simulink environment and verified by performing simulation studies. A real time prototype of the control actuation is developed with dSPACE-1104 hardware controller and a detailed analysis is carried out to confirm the viability of the proposed system.
Directory of Open Access Journals (Sweden)
H. A. Hairik
2008-01-01
Full Text Available This paper presents a new topology for the control of a six-phase series-connectedtwo-motor drive system supplied from Space Vector Pulse Width Modulation (SVPWMVoltage Source Inverter (VSI. The two-motordrive system consists of a six-phase and athree-phase induction motors connected in series. These motors and the supply system havebeen analyzed to construct a field-orientedmodel for them. This model clearly shows thepossibility of independent of control of the two machines. A fuzzy logic based speed controller has been constructed and used to drive the two-motor in this work . The two-motor system, inverter system, and the fuzzy controller models are implemented and tested using Simulink/Matlab facilities. The presented results show the validity of the model to dowell for the sake of speed control under different operating conditions.
Reasoning formalism in Boolean operator fuzzy logic
Institute of Scientific and Technical Information of China (English)
邓安生; 刘叙华
1995-01-01
Based on the newly introduced concepts of true-level and false-level, the formal structure of reasoning in Boolean operator fuzzy logic is presented. As a generalization of the theory of epistemic process in open logic, a formalism is also proposed to describe human reasoning with uncertain, inconsistent and insufficient knowledge, which can characterize the knowledge increment and revision, as well as the epistemic evolution. The formalism provides an explanation to the dynamic properties of human reasoning, i. e. continuous revision and combination of beliefs.
Astronomical pipeline processing using fuzzy logic
Shamir, Lior; Nemiroff, Robert J. Nemiroff
2008-01-01
Fundamental astronomical questions on the composition of the universe, the abundance of Earth-like planets, and the cause of the brightest explosions in the universe are being attacked by robotic telescopes costing billions of dollars and returning vast pipelines of data. The success of these programs depends on the accuracy of automated real time processing of images never seen by a human, and all predicated on fast and accurate automatic identifications of known astronomical objects and new astronomical transients. In this paper the needs of modern astronomical pipelines are discussed in the light of fuzzy-logic based decision-making. Several specific fuzzy-logic algorithms have been develop for the first time for astronomical purposes, and tested with excellent results on a test pipeline of data from the existing Night Sky Live sky survey.
Fuzzy logic for business, finance, and management
Bojadziev, George
1997-01-01
This is an interdisciplinary book for knowledge workers in business, finance, management, and socio-economic sciences. It provides a guide to and techniques for forecasting, decision making, conclusions, and evaluations in an environment involving uncertainty, vagueness, and impression. Traditional modeling techniques do not capture the nature of complex systems especially when humans are involved. Fuzzy logic provides effective tools for dealing with such systems. Emphasis is on applications presented in case studies including Time Forecasting for Project Management, New Product Pricing, Clie
Directory of Open Access Journals (Sweden)
Izadbakhsh Maziar
2014-12-01
Full Text Available The microgrid (MG technology integrates distributed generations, energy storage elements and loads. In this paper, dynamic performance enhancement of an MG consisting of wind turbine was investigated using permanent magnet synchronous generation (PMSG, photovoltaic (PV, microturbine generation (MTG systems and flywheel under different circumstances. In order to maximize the output of solar arrays, maximum power point tracking (MPPT technique was used by an adaptive neuro-fuzzy inference system (ANFIS; also, control of turbine output power in high speed winds was achieved using pitch angle control technic by fuzzy logic. For tracking the maximum point, the proposed ANFIS was trained by the optimum values. The simulation results showed that the ANFIS controller of grid-connected mode could easily meet the load demand with less fluctuation around the maximum power point. Moreover, pitch angle controller, which was based on fuzzy logic with wind speed and active power as the inputs, could have faster responses, thereby leading to flatter power curves, enhancement of the dynamic performance of wind turbine and prevention of both frazzle and mechanical damages to PMSG. The thorough wind power generation system, PV system, MTG, flywheel and power electronic converter interface were proposed by using Mat-lab/Simulink.
FPGA Fuzzy Controller Design for Magnetic Ball Levitation
Directory of Open Access Journals (Sweden)
Basil Hamed
2012-09-01
Full Text Available this paper presents a fuzzy controller design for nonlinear system using FPGA. A magnetic levitation system is considered as a case study and the fuzzy controller is designed to keep a magnetic object suspended in the air counteracting the weight of the object. Fuzzy controller will be implemented using FPGA chip. The design will use a high-level programming language HDL for implementing the fuzzy logic controller using the Xfuzzy tools to implement the fuzzy logic controller into HDL code. This paper, advocates a novel approach to implement the fuzzy logic controller for magnetic ball levitation system by using FPGA.
Using Fuzzy Logical Rule to Control the rooms Temperature%用模糊智能规律控制房间温度
Institute of Scientific and Technical Information of China (English)
王凌云; 徐菱虹
2000-01-01
叙述了房间温度控制器的重要性，分析了传统控制方法的特性和缺点。提出了房间温度模糊智能控制的方法，并给出了模糊智能规则的具体构造和仿真结果。%This paper narrates the importance of the room temperature controller,analyzes the characteristics and the defect of traditional temperature control methodsPut forward a method using fuzzy logical rule to control the room temperature,and give out the rule of fuzzy inference and a sample of computer emulation
Fuzzy modeling and control theory and applications
Matía, Fernando; Jiménez, Emilio
2014-01-01
Much work on fuzzy control, covering research, development and applications, has been developed in Europe since the 90's. Nevertheless, the existing books in the field are compilations of articles without interconnection or logical structure or they express the personal point of view of the author. This book compiles the developments of researchers with demonstrated experience in the field of fuzzy control following a logic structure and a unified the style. The first chapters of the book are dedicated to the introduction of the main fuzzy logic techniques, where the following chapters focus on concrete applications. This book is supported by the EUSFLAT and CEA-IFAC societies, which include a large number of researchers in the field of fuzzy logic and control. The central topic of the book, Fuzzy Control, is one of the main research and development lines covered by these associations.
Fuzzy Sliding Mode Control for Discrete Nonlinear Systems
Institute of Scientific and Technical Information of China (English)
F.Qiao.Q.M.Zhu; A.Winfield; C.Melhuish
2003-01-01
Sliding mode control is introduced into classical model free fuzzy logic control for discrete time nonlinear systems with uncertainty to the design of a novel fuzzy sliding mode control to meet the requirement of necessary and sufficient reaching conditions of sliding mode control. The simulation results show that the proposed controller outperforms the original fuzzy sliding mode controller and the classical fuzzy logic controller in stability, convergence and robustness.
Holakooie, Mohammad Hosein; Ojaghi, Mansour; Taheri, Asghar
2016-01-01
This paper investigates sensorless indirect field oriented control (IFOC) of SLIM with full-order Luenberger observer. The dynamic equations of SLIM are first elaborated to draw full-order Luenberger observer with some simplifying assumption. The observer gain matrix is derived from conventional procedure so that observer poles are proportional to SLIM poles to ensure the stability of system for wide range of linear speed. The operation of observer is significantly impressed by adaptive scheme. A fuzzy logic control (FLC) is proposed as adaptive scheme to estimate linear speed using speed tuning signal. The parameters of FLC are tuned using an off-line method through chaotic optimization algorithm (COA). The performance of the proposed observer is verified by both numerical simulation and real-time hardware-in-the-loop (HIL) implementation. Moreover, a detailed comparative study among proposed and other speed observers is obtained under different operation conditions.
Mapping Shape Geometry And Emotions Using Fuzzy Logic
DEFF Research Database (Denmark)
Achiche, Sofiane; Ahmed, Saeema
2008-01-01
and the intended emotion using fuzzy logic. To achieve this; 3D objects (shapes) created by design engineering students to match a set of words/emotions were analyzed. The authors identified geometric information as inputs of the fuzzy model and developed a set of fuzzy if/then rules to map the relationships...... between the fuzzy sets on each input premise and the output premise. In our case the output premise of the fuzzy logic model is the level of belonging to the design context (emotion). An evaluation of how users perceived the shapes was conducted to validate the fuzzy logic model and showed a high...... correlation between the fuzzy logic model and user perception....
Delay Computation Using Fuzzy Logic Approach
Directory of Open Access Journals (Sweden)
Ramasesh G. R.
2012-10-01
Full Text Available The paper presents practical application of fuzzy sets and system theory in predicting delay, with reasonable accuracy, a wide range of factors pertaining to construction projects. In this paper we shall use fuzzy logic to predict delays on account of Delayed supplies and Labor shortage. It is observed that the project scheduling software use either deterministic method or probabilistic method for computation of schedule durations, delays, lags and other parameters. In other words, these methods use only quantitative inputs leaving-out the qualitative aspects associated with individual activity of work. The qualitative aspect viz., the expertise of the mason or the lack of experience can have a significant impact on the assessed duration. Such qualitative aspects do not find adequate representation in the Project Scheduling software. A realistic project is considered for which a PERT chart has been prepared using showing all the major activities in reasonable detail. This project has been periodically updated until its completion. It is observed that some of the activities are delayed due to extraneous factors resulting in the overall delay of the project. The software has the capability to calculate the overall delay through CPM (Critical Path Method when each of the activity-delays is reported. We shall now demonstrate that by using fuzzy logic, these delays could have been predicted well in advance.
Muniraj, Murali; Arulmozhiyal, Ramaswamy
2015-01-01
A control actuation system has been used extensively in automotive, aerospace, and defense applications. The major challenges in modeling control actuation system are rise time, maximum peak to peak overshoot, and response to nonlinear system with percentage error. This paper addresses the challenges in modeling and real time implementation of control actuation system for missiles glider applications. As an alternative fuzzy-PID controller is proposed in BLDC motor drive followed by linkage mechanism to actuate fins in missiles and gliders. The proposed system will realize better rise time and less overshoot while operating in extreme nonlinear dynamic system conditions. A mathematical model of BLDC motor is derived in state space form. The complete control actuation system is modeled in MATLAB/Simulink environment and verified by performing simulation studies. A real time prototype of the control actuation is developed with dSPACE-1104 hardware controller and a detailed analysis is carried out to confirm the viability of the proposed system. PMID:26613102
Directory of Open Access Journals (Sweden)
Murali Muniraj
2015-01-01
Full Text Available A control actuation system has been used extensively in automotive, aerospace, and defense applications. The major challenges in modeling control actuation system are rise time, maximum peak to peak overshoot, and response to nonlinear system with percentage error. This paper addresses the challenges in modeling and real time implementation of control actuation system for missiles glider applications. As an alternative fuzzy-PID controller is proposed in BLDC motor drive followed by linkage mechanism to actuate fins in missiles and gliders. The proposed system will realize better rise time and less overshoot while operating in extreme nonlinear dynamic system conditions. A mathematical model of BLDC motor is derived in state space form. The complete control actuation system is modeled in MATLAB/Simulink environment and verified by performing simulation studies. A real time prototype of the control actuation is developed with dSPACE-1104 hardware controller and a detailed analysis is carried out to confirm the viability of the proposed system.
Directory of Open Access Journals (Sweden)
Camilo Caraveo
2017-07-01
Full Text Available Fuzzy logic is a soft computing technique that has been very successful in recent years when it is used as a complement to improve meta-heuristic optimization. In this paper, we present a new variant of the bio-inspired optimization algorithm based on the self-defense mechanisms of plants in the nature. The optimization algorithm proposed in this work is based on the predator-prey model originally presented by Lotka and Volterra, where two populations interact with each other and the objective is to maintain a balance. The system of predator-prey equations use four variables (α, β, λ, δ and the values of these variables are very important since they are in charge of maintaining a balance between the pair of equations. In this work, we propose the use of Type-2 fuzzy logic for the dynamic adaptation of the variables of the system. This time a fuzzy controller is in charge of finding the optimal values for the model variables, the use of this technique will allow the algorithm to have a higher performance and accuracy in the exploration of the values.
Output-back fuzzy logic systems and equivalence with feedback neural networks
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A new idea, output-back fuzzy logic systems, is proposed. It is proved that output-back fuzzy logic systems must be equivalent to feedback neural networks. After the notion of generalized fuzzy logic systems is defined, which contains at least a typical fuzzy logic system and an output-back fuzzy logic system, one important conclusion is drawn that generalized fuzzy logic systems are almost equivalent to neural networks.
Q-V droop control using fuzzy logic and reciprocal characteristic
DEFF Research Database (Denmark)
Wanga, Lu; Hu, Yanting; Chen, Zhe
2014-01-01
characteristic. Matlab/Simulink is used for analysing the performance of system. The feasibility of the improved droop control strategy has been verified and discussed. The results demonstrate the improved Q-V droop control strategy could have good effects in grid-connected and islanded mode, and during...
Fuzzy Logic Connectivity in Semiconductor Defect Clustering
Energy Technology Data Exchange (ETDEWEB)
Gleason, S.S.; Kamowski, T.P.; Tobin, K.W.
1999-01-24
In joining defects on semiconductor wafer maps into clusters, it is common for defects caused by different sources to overlap. Simple morphological image processing tends to either join too many unrelated defects together or not enough together. Expert semiconductor fabrication engineers have demonstrated that they can easily group clusters of defects from a common manufacturing problem source into a single signature. Capturing this thought process is ideally suited for fuzzy logic. A system of rules was developed to join disconnected clusters based on properties such as elongation, orientation, and distance. The clusters are evaluated on a pair-wise basis using the fuzzy rules and are joined or not joined based on a defuzzification and threshold. The system continuously re-evaluates the clusters under consideration as their fuzzy memberships change with each joining action. The fuzzy membership functions for each pair-wise feature, the techniques used to measure the features, and methods for improving the speed of the system are all developed. Examples of the process are shown using real-world semiconductor wafer maps obtained from chip manufacturers. The algorithm is utilized in the Spatial Signature Analyzer (SSA) software, a joint development project between Oak Ridge National Lab (ORNL) and SEMATECH.
Fuzzy Logic Connectivity in Semiconductor Defect Clustering
Energy Technology Data Exchange (ETDEWEB)
Gleason, S.S.; Kamowski, T.P.; Tobin, K.W.
1999-01-24
In joining defects on semiconductor wafer maps into clusters, it is common for defects caused by different sources to overlap. Simple morphological image processing tends to either join too many unrelated defects together or not enough together. Expert semiconductor fabrication engineers have demonstrated that they can easily group clusters of defects from a common manufacturing problem source into a single signature. Capturing this thought process is ideally suited for fuzzy logic. A system of rules was developed to join disconnected clusters based on properties such as elongation, orientation, and distance. The clusters are evaluated on a pair-wise basis using the fuzzy rules and are joined or not joined based on a defuzzification and threshold. The system continuously re-evaluates the clusters under consideration as their fuzzy memberships change with each joining action. The fuzzy membership functions for each pair-wise feature, the techniques used to measure the features, and methods for improving the speed of the system are all developed. Examples of the process are shown using real-world semiconductor wafer maps obtained from chip manufacturers. The algorithm is utilized in the Spatial Signature Analyzer (SSA) software, a joint development project between Oak Ridge National Lab (ORNL) and SEMATECH.
A Fuzzy-Logic Subsumption Controller for Home Energy Management Systems
Energy Technology Data Exchange (ETDEWEB)
Ainstworth, Nathan; Johnson, Brian; Lundstrom, Blake
2015-10-05
Presentation for NAPS 2015 associated with conference publication CP-64392. Home Energy Management Systems (HEMS) are controllers that manage and coordinate the generation, storage, and loads in a home. These controllers are increasingly necessary to ensure that increasing penetrations of distributed energy resources are used effectively and do not disrupt the operation of the grid. In this paper, we propose a novel approach to HEMS design based on behavioral control methods, which do not require accurate models or predictions and are very responsive to changing conditions.
Real-Time Implementation of a Fuzzy Logic Controller for DC-DC Switching Converters
2007-11-02
537-546, May 1997. [3] H. Sira -Ramirez, “Design of P-I controllers for DC-to-DC power supplies via extended linearization,” Int. J. Control, vol. 51...Technology, vol. 7, pp. 230-237, Mar. 1999. [5] G. Escobar, R. Ortega, H. Sira -Ramirez, J.P. Vilain and I. Zein, “An experimental comparison of several
Fuzzy Logic in Inverse Continuous Method
Directory of Open Access Journals (Sweden)
Víťazoslav Krúpa
2004-12-01
Full Text Available In the field of geotechnics, certain vagueness and ambiquity appears. We might not be able to design a mathematically accuratedescription of rock, whose properties change during the excavation (rock strength, discontinuities direction, dislocations, rock type.Furthermore, the excavation regime (thrust, revolutions, torque changes too, as well as the edge angle of cutting tools (due to wear andworking ability of cutterhead as result of sequential exchanges of worn-out cutterhead discs. All of these facts cause that the cutterheadoperates using the discs with different wear stage. The above mentioned problems led us to the decision to use the fuzzy logic and fuzzy sets,e.g. techniques operating with vagueness and ambiguity.
FUZZY LOGIC STATIC SYNCHRONOUS COMPENSATOR (FLSTATCOM
Directory of Open Access Journals (Sweden)
I Made Mataram
2016-06-01
Full Text Available Penerapan teknik fuzzy membawa perubahan yang signifikan khusus pada perhitungan dan analisis sistem konvensional. Peranan peralatan FACTS (Flexible AC Transmission System untuk memperbaiki kualitas tegangan dari pembangkit menuju beban sangat besar. STATCOM merupakan peralatan paling berpengaruh untuk memperbaiki tegangan pada jaringan transmisi tenaga listrik. Pembahasan pada penelitian ini dikhususkan pada FLSTATCOM. Model Fuzzy Logic dengan dua input digunakan sebagai pengontrol IGBT, sehingga mampu meningkatkan unjuk kerja STATCOM konvensional. Sistem Single Machine Infinite Bus menjadi sistem uji coba penggunaan FLSTATCOM.Hasil simulasi menggunakan simulink MATLAB, diperoleh nilai tegangan pada tiap sisi terima tanpa menggunakan STATCOM menghasilkan tegangan sebesar 217,3 kV, menggunakan STATCOM menghasilkan tegangan sebesar 220 kV, dan penggunaan FLSTATCOM mampu meningkatkan tegangan menjadi 228,9 kV (5,34%
Power transformer protection by using Fuzzy Logic
Directory of Open Access Journals (Sweden)
A. Aziz
2009-01-01
Full Text Available Power transformer protective relay should block the tripping during magnetizing inrush and rapidly operate the tripping during internal faults. Recently, the frequency environment of power system has been made more complicated and the quantity of 2nd frequency component in inrush state has been decreased because of the improvement of core steel. And then, traditional approaches will likely be maloperated in the case of magnetizing inrush with low second harmonic component and internal faults with high second harmonic component. This paper proposes a new relaying algorithm to enhance the fault detection sensitivities of conventional techniques by using a fuzzy logic approach. The proposed fuzzy-based relaying algorithm consists of flux-differential current derivative curve, harmonic restraint, and percentage differential characteristic curve. The proposed relaying was tested with MATLAB simulation software and showed a fast and accurate trip operation
Modelling on fuzzy control systems
Institute of Scientific and Technical Information of China (English)
LI; Hongxing(李洪兴); WANG; Jiayin(王加银); MIAO; Zhihong(苗志宏)
2002-01-01
A kind of modelling method for fuzzy control systems is first proposed here, which is calledmodelling method based on fuzzy inference (MMFI). It should be regarded as the third modelling method thatis different from two well-known modelling methods, that is, the first modelling method, mechanism modellingmethod (MMM), and the second modelling method, system identification modelling method (SlMM). Thismethod can, based on the interpolation mechanism on fuzzy logic system, transfer a group of fuzzy inferencerules describing a practice system into a kind of nonlinear differential equation with variable coefficients, calledHX equations, so that the mathematical model of the system can be obtained. This means that we solve thedifficult problem of how to get a model represented as differential equations on a complicated or fuzzy controlsystem.
Indian Academy of Sciences (India)
R BALASUBRAMANIAN; R SANKARAN; S PALANI
2017-09-01
This paper deals with design and simulation of a three-phase shunt hybrid power filter consisting of a pair of 5th and 7th selective harmonic elimination passive power filters connected in series with a conventional active power filter with reduced kVA rating. The objective is to enhance the power quality in a distributionnetwork feeding variety of non-linear, time-varying and unbalanced loads. The theory and modelling of the entire power circuit in terms of synchronously rotating reference frame and leading to a non-linear control scheme is presented. This work involves introduction of individual fuzzy logic controllers for d and q axiscurrent control and for voltage regulation of the DC link capacitor. The simulation schematic covering the power and control circuits have been developed taking into account severe harmonic distortion caused by non-linear and unbalanced loads. The effectiveness of the fuzzy logic controller for the compensation of harmonics and reactive power has been verified by successive simulation runs and analysis of the results. The proposed controller is also able to compensate the distortion generated by the voltage- and current-fed non-linear loads, unbalanced and dynamically varying loads. Further, excellent regulation of the DC link voltage is accomplished, which significantly contributes to improvement of power quality.
Directory of Open Access Journals (Sweden)
Dedid Cahya Happyanto
2012-05-01
Full Text Available Driving system of electric car for low speed has a performance of controller that is not easily set up on large span so it does not give a comfort to passengers. The study has been tested in the bumpy road conditions, by providing disturbances in the motor load, it is to describe the condition of the road. To improve the system performance, the speed and torque controller was applied using Field Oriented Control (FOC method. In this method, On-Line Proportional Integral Derivative Fuzzy Logic Controller (PID-FLC is used to give dynamic response to the change of speed and maximum torque on the electric car and this results the smooth movement on every change of car performance both in fast and slow movement when breaking action is taken. Optimization of membership functions in Fuzzy PID controller is required to obtain a new PID parameter values which is done in autotuning in any changes of the input or disturbance. PID parameter tuning in this case using the Ziegler-Nichols method based on frequency response. The mechanism is done by adjusting the PID parameters and the strengthening of the system output. The test results show that the controller Fuzzy Self-Tuning PID appropriate for Electric cars because they have a good response about 0.85% overshoot at to changes in speed and braking of electric cars.
Angelo A. Beltran Jr.; Felicito S. Caluyo
2014-01-01
—The control and operation of electronic systems relies and depends on the availability of the power supply. Rechargeable batteries have been more pervasively used as the energy storage and power source for various electrical and electronic systems and devices, such as communication systems, electronic devices, renewable power systems, electric vehicles, etc. However, the rechargeable batteries are subjected to the availability of the external power source when ...
Energy Technology Data Exchange (ETDEWEB)
Rajagopalan, A.; Washington, G.; Rizzoni, G.; Guezennec, Y.
2003-12-01
This report describes the development of new control strategies and models for Hybrid Electric Vehicles (HEV) by the Ohio State University. The report indicates results from models created in NREL's ADvanced VehIcle SimulatOR (ADVISOR 3.2), and results of a scalable IC Engine model, called in Willan's Line technique, implemented in ADVISOR 3.2.
FUZZY LOGIC MULTI-AGENT SYSTEM
Atef GHARBI; Ben Ahmed, Samir
2014-01-01
The paper deals with distributed planning in a Multi-Agent System (MAS) constituted by several intelligent agents each one has to interact with the other autonomous agents. The problem faced is how to ensure a distributed planning through the cooperation in our multi-agent system. To do so, we propose the use of fuzzy logic to represent the response of the agent in case of interaction with the other. Finally, we use JADE platform to create agents and ensure the communication be...
Institute of Scientific and Technical Information of China (English)
CHEN Yong-jun; HUANG Sheng-hua; WAN Shan-ming; WU Fang
2008-01-01
A high-performance digital servo system built on the platform of a field programmable gate array (FPGA), a fully digitized hardware design scheme of a direct torque control (DTC) and a low speed permanent magnet synchronous motor (PMSM) is proposed. The DTC strategy of PMSM is described with Verilog hardware description language and is employed on-chip FPGA in accordance with the electronic design automation design methodology. Due to large torque ripples in low speed PMSM, the hysteresis controller in a conventional PMSM DTC was replaced by a fuzzy controller. This FPGA scheme integrates the direct torque controller strategy, the time speed measurement algorithm, the fuzzy regulating technique and the space vector pulse width modulation principle. Experimental results indicate the fuzzy controller can provide a controllable speed at 20 r min-1 and torque at 330 N m with satisfactory dynamic and static performance. Furthermore, the results show that this new control strategy decreases the torque ripple drastically and enhances control performance.
A High Efficiency Power Factor Correction Using Interleaved Boost Converter With Fuzzy Logic Control
Directory of Open Access Journals (Sweden)
M.BHUVANESWARI
2013-06-01
Full Text Available This paper presents interleaved front end boost converter to perform better power factor correction to store energy for electric vehicles. The interleaved boost converter increases reliability, decreased stress on critical components, improves efficiency and more flexibility. The parallel connection of two boost converters reduces the input ripple current of the converter. The interleaved boost converter with coupled inductors reduces the volume and copper usage of the magnetic components and also achieves high power density. The coupled inductor delivers continuous current to improve the efficiency. The boost power factor correction (PFC converter with auxiliary circuit optimizes the amount of reactive current during light load condition. In addition the control system regulates the amount of reactive current to guarantee zero voltage switching (ZVS during line cycle for different load conditions. The proposed interleaved boost converter with coupled inductor was modeled and its performance is simulated and analyzed in Mat lab/Simulink environment.
DEFF Research Database (Denmark)
Boiocchi, Riccardo; Mauricio Iglesias, Miguel; Vangsgaard, Anna Katrine
2015-01-01
to the reactor.The diagnosis tool was first evaluated using 100 days of real process operation data obtained from a lab-scale single-stage autotrophic nitrogen removing reactor. This evaluation revealed that the fuzzy logic diagnosis is able to provide a realistic description of the microbiological state...
SISTEM PENGEMBANGAN KENDALI FUZZY LOGIC BERBASIS MIKROKONTROLER KELUARGA MCS51 (PetraFuz
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Thiang Thiang
1999-01-01
Full Text Available This paper presents a Fuzzy Logic Development Tool called PetraFuz which has been developed at Control System Laboratory, Electrical Engineering Department, Petra Christian University. The system consists of a hardware target based on MCS51 microcontroller and a software support running under PC Windows. The system is targeted for developing fuzzy logic based systems. It supports fuzzy logic design, evaluation, assembly language generator and downloading process to the target hardware to perform on-line fuzzy process. Process action and fuzzy parameters could be transferred to PC monitor via RS-232 serial communication, this on-line process parameters is used for fuzzy tuning, i.e. fuzzy if-then rules and fuzzy membership functions. The PetraFuz tool helps very much for Fuzzy system developments, it could reduce development time significantly. The tool could spur the development of fuzzy systems based on microcontroller systems such as fuzzy control systems, fuzzy information processing, etc. Abstract in Bahasa Indonesia : Makalah ini menyajikan sebuah sistem pengembangan kendali fuzzy logic (PetraFuz, Petra Fuzzy Development System yang dikembangkan oleh laboratorium Sistem Kontrol, Jurusan Teknik Elektro, Universitas Kristen Petra Surabaya. Sistem ini terdiri dari perangkat keras sistem mikrokontroler MCS51 dan perangkat lunak pendukung yang berjalan pada PC. Sistem PetraFuz digunakan untuk mengembangkan sistem berbasis fuzzy logic utamanya pada bidang kendali. Kemampuan sistem meliputi pengembangan pada fase perancangan kendali, evaluasi kendali, pembentukan program bahasa assembly MCS51 dan proses downloading program menuju target sistem mikrokontroler MCS51 untuk dieksekusi melakukan kendali pada plant yang nyata. Aksi kendali dapat diakuisi oleh program PC melalui komunikasi serial RS232 sehingga respon kendali dapat digambarkan pada layar monitor untuk dilakukan analisis lebih lanjut yang diperlukan pada proses tuning if-then fuzzy rules
Directory of Open Access Journals (Sweden)
Liyang Wang
2016-01-01
Full Text Available Time-varying external disturbances cause instability of humanoid robots or even tip robots over. In this work, a trapezoidal fuzzy least squares support vector regression- (TF-LSSVR- based control system is proposed to learn the external disturbances and increase the zero-moment-point (ZMP stability margin of humanoid robots. First, the humanoid states and the corresponding control torques of the joints for training the controller are collected by implementing simulation experiments. Secondly, a TF-LSSVR with a time-related trapezoidal fuzzy membership function (TFMF is proposed to train the controller using the simulated data. Thirdly, the parameters of the proposed TF-LSSVR are updated using a cubature Kalman filter (CKF. Simulation results are provided. The proposed method is shown to be effective in learning and adapting occasional external disturbances and ensuring the stability margin of the robot.
Directory of Open Access Journals (Sweden)
R. Lasri
2013-01-01
Full Text Available The main objective of this paper is to prove the great advantage that brings our novel approach to the intelligent control area. A set of various types of intelligent controllers have been designed to control the temperature of a room in a real-time control process in order to compare the obtained results with each other. Through a training board that allows us to control the temperature, all the used algorithms should present their best performances in this control process; therefore, our self-organized and online adaptive fuzzy logic controller (FLC will be required to present great improvements in the control task and a real high control performance. Simulation results can show clearly that the new approach presented and tested in this work is very efficient. Thus, our adaptive and self-organizing FLC presents the best accuracy compared with the remaining used controllers, and, besides that, it can guarantee an important reduction of the power consumption during the control process.
Recommendation application for video head impulse test based on fuzzy logic control
Institute of Scientific and Technical Information of China (English)
NGUYEN Thi Anh Dao; KIM Dae Young; LEE Sang Min; KIM Kyu Sung; Seong Ro Lee; KWON Jang Woo
2016-01-01
Vestibulo-ocular reflex (VOR) is an important biological reflex that controls eye movement to ensure clear vision while the head is in motion. Nowadays, VOR measurement is commonly done with a video head impulse test based on a velocity gain algorithm or a position gain algorithm, in which velocity gain is a VOR calculation on head and eye velocity, whereas position gain is calculated from head and eye position. The aim of this work is first to compare the two algorithms’ performance and to detect covert catch-up saccade, then to propose a stand-alone recommendation application for the patient’s diagnosis. In the first experiment, for ipsilesional and contralesional sides, the calculated position gain (0.94±0.17) is higher than velocity gain (0.84±0.19). Moreover, gain asymmetry of both lesion and intact sides using velocity gain is mostly higher than that from using position gain (four out of five subjects). Consequently, for subjects who have unilateral vestibular neuritis diagnosed from clinical symptoms and a vestibular function test, vestibular weakness is depicted by velocity gain much better than by position gain. Covert catch-up saccade and position gain then are used as inputs for recommendation applications.
Looking for Oriental fundamentals Fuzzy Logic
Directory of Open Access Journals (Sweden)
Angel Garrido
2013-10-01
Full Text Available For quite some time we have been trying to trace the river of Non-ClassicalLogics, and especially, Fuzzy Logic, trying to find the sources of this today flowing quite mighty river. Following from Lotfi A. Zadeh, we have traced his inspiring, the Polish logician Jan Lukasiewicz, who in turn was inspired by Aristotle's Peri Hermeneias (De Interpretatione. Also, Lukasiewicz occupies a central position in the Lvov-Warsaw School, who founded Kazimierz Twardowski, a student of Franz Brentano, and this in turn disciple of Bernard Bolzano. The connection with Leibniz and Bolzano come through medieval scholastic thinkers, especially John Duns Scotus and William of Ockham and the problem of future contingents, they had collected from the Aristotelian tradition. But there was to trace the “eastern (oriental track, which leads to the ancient Chinese and Indian philosophy. Here we will treat it as a first and necessary approach.
Fault Diagnosis and Reliability Analysis Using Fuzzy Logic Method
Institute of Scientific and Technical Information of China (English)
Miao Zhinong; Xu Yang; Zhao Xiangyu
2006-01-01
A new fuzzy logic fault diagnosis method is proposed. In this method, fuzzy equations are employed to estimate the component state of a system based on the measured system performance and the relationship between component state and system performance which is called as "performance-parameter" knowledge base and constructed by expert. Compared with the traditional fault diagnosis method, this fuzzy logic method can use humans intuitive knowledge and dose not need a precise mapping between system performance and component state. Simulation proves its effectiveness in fault diagnosis. Then, the reliability analysis is performed based on the fuzzy logic method.
The Application of Fuzzy Logic to Collocation Extraction
Bisht, Raj Kishor
2008-01-01
Collocations are important for many tasks of Natural language processing such as information retrieval, machine translation, computational lexicography etc. So far many statistical methods have been used for collocation extraction. Almost all the methods form a classical crisp set of collocation. We propose a fuzzy logic approach of collocation extraction to form a fuzzy set of collocations in which each word combination has a certain grade of membership for being collocation. Fuzzy logic provides an easy way to express natural language into fuzzy logic rules. Two existing methods; Mutual information and t-test have been utilized for the input of the fuzzy inference system. The resulting membership function could be easily seen and demonstrated. To show the utility of the fuzzy logic some word pairs have been examined as an example. The working data has been based on a corpus of about one million words contained in different novels constituting project Gutenberg available on www.gutenberg.org. The proposed me...
DSP-based fuzzy implementation of indirect vector controlled induction motor
Energy Technology Data Exchange (ETDEWEB)
Radwan, T.S.; Uddin, M.N.; Rahman, M.A. [Memorial University of Newfoundland, Faculty of Engineering and Applied Science, St John' s, NF (Canada)
2000-08-01
In this paper, the fuzzy logic speed controller for high performance induction motor drive is proposed. The controller is based on the indirect vector control. The fuzzy logic speed controller is employed as an outer loop. The results of applying the developed fuzzy logic controllers are compared to those obtained by the application of a conventional PI controller. The results indicate superior performance and robustness of fuzzy logic controllers over the PI controller at any working conditions. (orig.)
Applications of Fuzzy Logic in Image Processing – A Brief
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Mahesh Prasanna K
2015-10-01
Full Text Available The subject of this study is to show the application of fuzzy logic in image processing with a brief introduction to fuzzy logic and digital image processing. Digital image processing is an ever expanding and dynamic area with applications reaching out into our everyday life such as medicine, space exploration, surveillance, authentication, automated industry inspection and many more areas. Fuzzy logic, one of the decision-making techniques of artificial intelligence, has many application areas. Although it has been subjected to criticisms since its birth, especially in recent years, fuzzy logic has been proven to be applicable in almost all scientific fields. This shows that the concept of fuzzy logic will maintain its validity and the number of fields where it draws attention will increase further.
Fuzzy logic, neural networks, and soft computing
Zadeh, Lofti A.
1994-01-01
The past few years have witnessed a rapid growth of interest in a cluster of modes of modeling and computation which may be described collectively as soft computing. The distinguishing characteristic of soft computing is that its primary aims are to achieve tractability, robustness, low cost, and high MIQ (machine intelligence quotient) through an exploitation of the tolerance for imprecision and uncertainty. Thus, in soft computing what is usually sought is an approximate solution to a precisely formulated problem or, more typically, an approximate solution to an imprecisely formulated problem. A simple case in point is the problem of parking a car. Generally, humans can park a car rather easily because the final position of the car is not specified exactly. If it were specified to within, say, a few millimeters and a fraction of a degree, it would take hours or days of maneuvering and precise measurements of distance and angular position to solve the problem. What this simple example points to is the fact that, in general, high precision carries a high cost. The challenge, then, is to exploit the tolerance for imprecision by devising methods of computation which lead to an acceptable solution at low cost. By its nature, soft computing is much closer to human reasoning than the traditional modes of computation. At this juncture, the major components of soft computing are fuzzy logic (FL), neural network theory (NN), and probabilistic reasoning techniques (PR), including genetic algorithms, chaos theory, and part of learning theory. Increasingly, these techniques are used in combination to achieve significant improvement in performance and adaptability. Among the important application areas for soft computing are control systems, expert systems, data compression techniques, image processing, and decision support systems. It may be argued that it is soft computing, rather than the traditional hard computing, that should be viewed as the foundation for artificial
Fuzzy logic, neural networks, and soft computing
Zadeh, Lofti A.
1994-01-01
The past few years have witnessed a rapid growth of interest in a cluster of modes of modeling and computation which may be described collectively as soft computing. The distinguishing characteristic of soft computing is that its primary aims are to achieve tractability, robustness, low cost, and high MIQ (machine intelligence quotient) through an exploitation of the tolerance for imprecision and uncertainty. Thus, in soft computing what is usually sought is an approximate solution to a precisely formulated problem or, more typically, an approximate solution to an imprecisely formulated problem. A simple case in point is the problem of parking a car. Generally, humans can park a car rather easily because the final position of the car is not specified exactly. If it were specified to within, say, a few millimeters and a fraction of a degree, it would take hours or days of maneuvering and precise measurements of distance and angular position to solve the problem. What this simple example points to is the fact that, in general, high precision carries a high cost. The challenge, then, is to exploit the tolerance for imprecision by devising methods of computation which lead to an acceptable solution at low cost. By its nature, soft computing is much closer to human reasoning than the traditional modes of computation. At this juncture, the major components of soft computing are fuzzy logic (FL), neural network theory (NN), and probabilistic reasoning techniques (PR), including genetic algorithms, chaos theory, and part of learning theory. Increasingly, these techniques are used in combination to achieve significant improvement in performance and adaptability. Among the important application areas for soft computing are control systems, expert systems, data compression techniques, image processing, and decision support systems. It may be argued that it is soft computing, rather than the traditional hard computing, that should be viewed as the foundation for artificial
Chen, Shyi-Ming; Chen, Shen-Wen
2015-03-01
In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy-trend logical relationships. Firstly, the proposed method fuzzifies the historical training data of the main factor and the secondary factor into fuzzy sets, respectively, to form two-factors second-order fuzzy logical relationships. Then, it groups the obtained two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, it calculates the probability of the "down-trend," the probability of the "equal-trend" and the probability of the "up-trend" of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group, respectively. Finally, it performs the forecasting based on the probabilities of the down-trend, the equal-trend, and the up-trend of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the NTD/USD exchange rates. The experimental results show that the proposed method outperforms the existing methods.
基于MATLAB的ASR模糊控制仿真研究%Simulation Research of Fuzzy Logic Control for ASR Based on MATLAB
Institute of Scientific and Technical Information of China (English)
李发均; 王亚军; 董雅丽; 李家强
2011-01-01
Adopt the fuzzy control theories,pass theories analysis and experiment data,construct the perfect fuzzy controller.The purpose is to make the car wheel working at the best glide rate,short the accelerating distance and improve directional stability.The simulation results present that the design which is adopted fuzzy logic controller is simple and it does not need a complex math model.It can make the glide rate at a anticipant level,and short the accelerating distance.%采用模糊控制理论,通过理论分析和已有的试验数据,构造出满意的模糊控制器。使车轮工作在最佳滑动率附近,缩短驱动加速距离并有效的改善驱动时的方向稳定性。仿真结果表明,采用模糊控制算法使整个驱动防滑系统的设计简单,避免建立复杂的驱动过程数学模型,可以控制滑动率在最佳滑动率附近,并缩短了驱动加速距离。