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Sample records for fuzzy logic controlled

  1. 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 rule- base ... The greatest limitation of fuzzy logic control is the lack ..... c(kT)= e(kT)-e((k-1)T). (16) .... with the aid of fuzzy models”, It in Industrial.

  2. Fuzzy logic control of nuclear power plant

    International Nuclear Information System (INIS)

    Yao Liangzhong; Guo Renjun; Ma Changwen

    1996-01-01

    The main advantage of the fuzzy logic control is that the method does not require a detailed mathematical model of the object to be controlled. In this paper, the shortcomings and limitations of the model-based method in nuclear power plant control were presented, the theory of the fuzzy logic control was briefly introduced, and the applications of the fuzzy logic control technology in nuclear power plant controls were surveyed. Finally, the problems to be solved by using the fuzzy logic control in nuclear power plants were discussed

  3. Application of fuzzy logic control in industry

    International Nuclear Information System (INIS)

    Van der Wal, A.J.

    1994-01-01

    An overview is given of the various ways fuzzy logic can be used to improve industrial control. The application of fuzzy logic in control is illustrated by two case studies. The first example shows how fuzzy logic, incorporated in the hardware of an industrial controller, helps to finetune a PID controller, without the operator having any a priori knowledge of the system to be controlled. The second example is from process industry. Here, fuzzy logic supervisory control is implemented in software and enhances the operation of a sintering oven through a subtle combination of priority management and deviation-controlled timing

  4. Fuzzy logic control for camera tracking system

    Science.gov (United States)

    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.

  5. Fuzzy logic applications to control engineering

    Science.gov (United States)

    Langari, Reza

    1993-12-01

    This paper presents the results of a project presently under way at Texas A&M which focuses on the use of fuzzy logic in integrated control of manufacturing systems. The specific problems investigated here include diagnosis of critical tool wear in machining of metals via a neuro-fuzzy algorithm, as well as compensation of friction in mechanical positioning systems via an adaptive fuzzy logic algorithm. The results indicate that fuzzy logic in conjunction with conventional algorithmic based approaches or neural nets can prove useful in dealing with the intricacies of control/monitoring of manufacturing systems and can potentially play an active role in multi-modal integrated control systems of the future.

  6. Fuzzy logic

    CERN Document Server

    Smets, P

    1995-01-01

    We start by describing the nature of imperfect data, and giving an overview of the various models that have been proposed. Fuzzy sets theory is shown to be an extension of classical set theory, and as such has a proeminent role or modelling imperfect data. The mathematic of fuzzy sets theory is detailled, in particular the role of the triangular norms. The use of fuzzy sets theory in fuzzy logic and possibility theory,the nature of the generalized modus ponens and of the implication operator for approximate reasoning are analysed. The use of fuzzy logic is detailled for application oriented towards process control and database problems.

  7. Fuzzy Logic Controller Design for Intelligent Robots

    Directory of Open Access Journals (Sweden)

    Ching-Han Chen

    2017-01-01

    Full Text Available This paper presents a fuzzy logic controller by which a robot can imitate biological behaviors such as avoiding obstacles or following walls. The proposed structure is implemented by integrating multiple ultrasonic sensors into a robot to collect data from a real-world environment. The decisions that govern the robot’s behavior and autopilot navigation are driven by a field programmable gate array- (FPGA- based fuzzy logic controller. The validity of the proposed controller was demonstrated by simulating three real-world scenarios to test the bionic behavior of a custom-built robot. The results revealed satisfactorily intelligent performance of the proposed fuzzy logic controller. The controller enabled the robot to demonstrate intelligent behaviors in complex environments. Furthermore, the robot’s bionic functions satisfied its design objectives.

  8. Implementation of fuzzy logic control algorithm in embedded ...

    African Journals Online (AJOL)

    Fuzzy logic control algorithm solves problems that are difficult to address with traditional control techniques. This paper describes an implementation of fuzzy logic control algorithm using inexpensive hardware as well as how to use fuzzy logic to tackle a specific control problem without any special software tools. As a case ...

  9. Fuzzy Logic Based Autonomous Traffic Control System

    Directory of Open Access Journals (Sweden)

    Muhammad ABBAS

    2012-01-01

    Full Text Available The aim of this paper is to design and implement fuzzy logic based traffic light Control system to solve the traffic congestion issues. In this system four input parameters: Arrival, Queue, Pedestrian and Emergency Vehicle and two output parameters: Extension in Green and Pedestrian Signals are used. Using Fuzzy Rule Base, the system extends or terminates the Green Signal according to the Traffic situation at the junction. On the presence of emergency vehicle, the system decides which signal(s should be red and how much an extension should be given to Green Signal for Emergency Vehicle. The system also monitors the density of people and makes decisions accordingly. In order to verify the proposed design algorithm MATLAB simulation is adopted and results obtained show concurrency to the calculated values according to the Mamdani Model of the Fuzzy Control System.

  10. Efficient fuzzy logic controller for magnetic levitation systems | Shu ...

    African Journals Online (AJOL)

    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 ...

  11. control of a dc motor using fuzzy logic control algorithm

    African Journals Online (AJOL)

    user

    controller in the control performance of an industrial type DC motor using MATLAB. The fuzzy logic .... controlled separately excited permanent magnet DC motor (PMDC). ... When the field current is constant, the flux induced by the field ...

  12. Different control applications on a vehicle using fuzzy logic control

    Indian Academy of Sciences (India)

    Vehicle vibrations; active suspensions; fuzzy logic control; vehicle model. 1. .... The general expression of the mathematical model is shown below: .... Figure 5a presents the time history of the control force when the controller exists only under.

  13. 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

  14. Introduction to type-2 fuzzy logic control theory and applications

    CERN Document Server

    Mendel, Jerry M; Tan, Woei-Wan; Melek, William W; Ying, Hao

    2014-01-01

    Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students. The coverage provides both background and an extensive literature survey on fuzzy logic and related type-2 fuzzy control. It also includes research questions, experiment and simulation results, and downloadable computer programs on an associated website. This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications.

  15. Fuzzy logic control to be conventional method

    Energy Technology Data Exchange (ETDEWEB)

    Eker, Ilyas [University of Gaziantep, Gaziantep (Turkey). Department of Electrical and Electronic Engineering; Torun, Yunis [University of Gaziantep, Gaziantep (Turkey). Technical Vocational School of Higher Education

    2006-03-01

    Increasing demands for flexibility and fast reactions in modern process operation and production methods result in nonlinear system behaviour of partly unknown systems, and this necessitates application of alternative control methods to meet the demands. Fuzzy logic (FL) control can play an important role because knowledge based design rules can easily be implemented in systems with unknown structure, and it is going to be a conventional control method since the control design strategy is simple and practical and is based on linguistic information. Computational complexity is not a limitation any more because the computing power of computers has been significantly improved even for high speed industrial applications. This makes FL control an important alternative method to the conventional PID control method for use in nonlinear industrial systems. This paper presents a practical implementation of the FL control to an electrical drive system. Such drive systems used in industry are composed of masses moving under the action of position and velocity dependent forces. These forces exhibit nonlinear behaviour. For a multi-mass drive system, the nonlinearities, like Coulomb friction and dead zone, significantly influence the operation of the systems. The proposed FL control configuration is based on speed error and change of speed error. The feasibility and effectiveness of the control method are experimentally demonstrated. The results obtained from conventional FL control, fuzzy PID and adaptive FL control are compared with traditional PID control for the dynamic responses of the closed loop drive system. (author)

  16. Fuzzy logic control to be conventional method

    International Nuclear Information System (INIS)

    Eker, Ilyas; Torun, Yunis

    2006-01-01

    Increasing demands for flexibility and fast reactions in modern process operation and production methods result in nonlinear system behaviour of partly unknown systems, and this necessitates application of alternative control methods to meet the demands. Fuzzy logic (FL) control can play an important role because knowledge based design rules can easily be implemented in systems with unknown structure, and it is going to be a conventional control method since the control design strategy is simple and practical and is based on linguistic information. Computational complexity is not a limitation any more because the computing power of computers has been significantly improved even for high speed industrial applications. This makes FL control an important alternative method to the conventional PID control method for use in nonlinear industrial systems. This paper presents a practical implementation of the FL control to an electrical drive system. Such drive systems used in industry are composed of masses moving under the action of position and velocity dependent forces. These forces exhibit nonlinear behaviour. For a multi-mass drive system, the nonlinearities, like Coulomb friction and dead zone, significantly influence the operation of the systems. The proposed FL control configuration is based on speed error and change of speed error. The feasibility and effectiveness of the control method are experimentally demonstrated. The results obtained from conventional FL control, fuzzy PID and adaptive FL control are compared with traditional PID control for the dynamic responses of the closed loop drive system

  17. Implementation of a Fuzzy Logic Speed Controller for a Permanent ...

    African Journals Online (AJOL)

    In this paper DC motor control models were mathematically extracted and implemented using fuzzy logic speed controller. All control systems suffer from problems related to undesirable overshoot, longer settling times and vibrations while going from one state to another. To overcome the maximum overshoot, fuzzy logic ...

  18. Fuzzy logic controller using different inference methods

    International Nuclear Information System (INIS)

    Liu, Z.; De Keyser, R.

    1994-01-01

    In this paper the design of fuzzy controllers by using different inference methods is introduced. Configuration of the fuzzy controllers includes a general rule-base which is a collection of fuzzy PI or PD rules, the triangular fuzzy data model and a centre of gravity defuzzification algorithm. The generalized modus ponens (GMP) is used with the minimum operator of the triangular norm. Under the sup-min inference rule, six fuzzy implication operators are employed to calculate the fuzzy look-up tables for each rule base. The performance is tested in simulated systems with MATLAB/SIMULINK. Results show the effects of using the fuzzy controllers with different inference methods and applied to different test processes

  19. Fuzzy logic control and optimization system

    Science.gov (United States)

    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.

  20. Application of fuzzy logic operation and control to BWRs

    International Nuclear Information System (INIS)

    Junichi Tanji; Mitsuo Kinoshita; Takaharu Fukuzaki; Yasuhiro Kobayashi

    1993-01-01

    Fuzzy logic control schemes employing linguistic decision rules for flexible operator control strategies have undergone application tests in dynamic systems. The advantages claimed for fuzzy logic control are its abilities: (a) to facilitate direct use of skillful operator know-how for automatic operation and control of the systems and (b) to provide robust multivariable control for complex plants. The authors have also studied applications of fuzzy logic control to automatic startup operations and load-following control in boiling water reactors, pursuing these same advantages

  1. Implementation of Fuzzy Logic Based Temperature-Controlled Heat ...

    African Journals Online (AJOL)

    This research then compares the control performance of PID (Proportional Integral and Derivative) and Fuzzy logic controllers. Conclusions are made based on these control performances. The results show that the control performance for a Fuzzy controller is quite similar to PID controller but comparatively gives a better ...

  2. Robust position control of induction motor using fuzzy logic control

    International Nuclear Information System (INIS)

    Kim, Sei Chan; Kim, Duk Hun; Yang, Seung Ho; Won, Chung Yuen

    1993-01-01

    In recent years, fuzzy logic or fuzzy set theory has reveived attention of a number of researchers in the area of power electronics and motion control. The paper describes a vector-controlled induction motor position servo drive where fuzzy control is used to get robustness against parameter variation and load torque disturbance effects. Both coarse and fine control with the help of look-up rule tables are used to improve transient response and system settling time. The performance characteristics are then compared with those of proportional-integral(PI) control. The simulation results clearly indicate the superiority of fuzzy control with larger number of rules. The fuzzy controller was implemented with a 16-bit microprocessor and tested in laboratory on a 3-hp IGBT inverter induction motor drive system. The test results verify the simulation performance. (Author)

  3. Fuzzy logic control of vehicle suspensions with dry friction nonlinearity

    Indian Academy of Sciences (India)

    Fuzzy logic control; active vehicle suspension; suspension space. 1. ... surface unevenness, stability and directional control during handling ..... Burton A W, Truscott A J, Wellstead P E 1995 Analysis, modeling and control of an advanced.

  4. Fuzzy logic-based battery charge controller

    International Nuclear Information System (INIS)

    Daoud, A.; Midoun, A.

    2006-01-01

    Photovoltaic power system are generally classified according to their functional and operational requirements, their component configurations, and how the equipment is connected to other power sources and electrical loads, photovoltaic systems can be designed to provide DC and/or AC power service, can operate interconnected with or independent of the utility grid, and can be connected with other energy sources and energy storage systems. Batteries are often used in PV systems for the purpose of storing energy produced by the PV array during the day, and to supply it to electrical loads as needed (during the night and periods of cloudy weather). The lead acid battery, although know for more than one hundred years, has currently offered the best response in terms of price, energetic efficiency and lifetime. The main function of controller or regulator in PV system is too fully charge the battery without permitting overcharge while preventing reverse current flow at night. If a no-self-regulating solar array is connected to lead acid batteries with no overcharge protection, battery life will be compromised. Simple controllers contain a transistor that disconnects or reconnects the PV in the charging circuit once a pre-set voltage is reached. More sophisticated controllers utilize pulse with modulation (PWM) to assure the battery is being fully charged. The first 70% to 80% of battery capacity is easily replaced, but the last 20% to 30% requires more attention and therefore more complexity. This complexity is avoided by using a skilled operators experience in the form of the rules. Thus a fuzzy control system seeks to control the battery that cannot be controlled well by a conventional control such as PID, PD, PI etc., due to the unavailability of an accurate mathematical model of the battery. In this paper design of an intelligent battery charger, in which the control algorithm is implemented with fuzzy logic is discussed. The digital architecture is implemented with

  5. Fuzzy logic for structural system control

    Directory of Open Access Journals (Sweden)

    Herbert Martins Gomes

    Full Text Available This paper provides some information and numerical tests that aims to investigate the use of a Fuzzy Controller applied to control systems. Some advantages are reported regarding the use of this controller, such as the characteristic ease of implementation due to its semantic feature in the statement of the control rules. On the other hand, it is also hypothesized that these systems have a lower performance loss when the system to be controlled is nonlinear or has time varying parameters. Numerical tests are performed using modal LQR optimal control and Fuzzy control of non-collocated systems with full state feedback in a two-dimensional structure. The paper proposes a way of designing a controller that may be a supervisory Fuzzy controller for a traditional controller or even a fuzzy controller independent from the traditional control, consisting on individual mode controllers. Some comments are drawn regarding the performance of these proposals in a number of arrangements.

  6. reactor power control using fuzzy logic

    International Nuclear Information System (INIS)

    Ahmed, A.E.E.

    2001-01-01

    power stabilization is a critical issue in nuclear reactors. convention pd- controller is currently used in egypt second testing research reactor (ETRR-2). two fuzzy controllers are proposed to control the reactor power of ETRR-2 reactor. the design of the first one is based on a set of linguistic rules that were adopted from the human operators experience. after off-line fuzzy computations, the controller is a lookup table, and thus, real time controller is achieved. comparing this f lc response with the pd-controller response, which already exists in the system, through studying the expected transients during the normal operation of ETRR-2 reactor, the simulation results show that, fl s has the better response, the second controller is adaptive fuzzy controller, which is proposed to deal with system non-linearity . The simulation results show that the proposed adaptive fuzzy controller gives a better integral square error (i se) index than the existing conventional od controller

  7. Fuzzy logic controller to improve powerline communication

    Science.gov (United States)

    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.

  8. Determination Of Adaptive Control Parameter Using Fuzzy Logic Controller

    Directory of Open Access Journals (Sweden)

    Omur Can Ozguney

    2017-08-01

    Full Text Available The robot industry has developed along with the increasing the use of robots in industry. This has led to increase the studies on robots. The most important part of these studies is that the robots must be work with minimum tracking trajectory error. But it is not easy for robots to track the desired trajectory because of the external disturbances and parametric uncertainty. Therefore adaptive and robust controllers are used to decrease tracking error. The aim of this study is to increase the tracking performance of the robot and minimize the trajectory tracking error. For this purpose adaptive control law for robot manipulator is identified and fuzzy logic controller is applied to find the accurate values for adaptive control parameter. Based on the Lyapunov theory stability of the uncertain system is guaranteed. In this study robot parameters are assumed to be unknown. This controller is applied to a robot model and the results of simulations are given. Controller with fuzzy logic and without fuzzy logic are compared with each other. Simulation results show that the fuzzy logic controller has improved the results.

  9. Type-2 fuzzy logic uncertain systems’ modeling and control

    CERN Document Server

    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.

  10. Fuzzy logic controller for weaning neonates from mechanical ventilation.

    OpenAIRE

    Hatzakis, G. E.; Davis, G. M.

    2002-01-01

    Weaning from mechanical ventilation is the gradual detachment from any ventilatory support till normal spontaneous breathing can be fully resumed. To date, we have developed a fuzzy logic controller for weaning COPD adults using pressure support ventilation (PS). However, adults and newborns differ in the pathophysiology of lung disease. We therefore used our fuzzy logic-based weaning platform to develop modularized components for weaning newborns with lung disease. Our controller uses the he...

  11. Hybrid fuzzy logic control of laser surface heat treatments

    International Nuclear Information System (INIS)

    Perez, Jose Antonio; Ocana, Jose Luis; Molpeceres, Carlos

    2007-01-01

    This paper presents an advanced hybrid fuzzy logic control system for laser surface heat treatments, which allows to increase significantly the uniformity and final quality of the obtained product, reducing the rejection rate and increasing the productivity and efficiency of the treatment. Basically, the proposed hybrid control structure combines a fuzzy logic controller, with a pure integral action, both fully decoupled, improving the performances of the process with a reasonable design cost, since the system nonlinearities are fully compensated by the fuzzy component of the controller, while the integral action contributes to eliminate the steady-state error

  12. A fuzzy logic pitch angle controller for power system stabilization

    Energy Technology Data Exchange (ETDEWEB)

    Jauch, Clemens; Cronin, Tom; Sorensen, Poul [Wind Energy Department, Riso National Laboratory, PO Box 49, DK-4000 Roskilde, (Denmark); Jensen, Birgitte Bak [Institute of Energy Technology, Aalborg University, Pontoppidanstraede 101, DK-9220 Aalborg East, (Denmark)

    2006-07-12

    In this article the design of a fuzzy logic pitch angle controller for a fixed speed, active-stall wind turbine, which is used for power system stabilization, is presented. The system to be controlled, which is the wind turbine and the power system to which the turbine is connected, is described. The advantages of fuzzy logic control when applied to large-signal control of active-stall wind turbines are outlined. The general steps of the design process for a fuzzy logic controller, including definition of the controller inputs, set-up of the fuzzy rules and the method of defuzzification, are described. The performance of the controller is assessed by simulation, where the wind turbine's task is to dampen power system oscillations. In the scenario simulated for this work, the wind turbine has to ride through a transient short-circuit fault and subsequently contribute to the damping of the grid frequency oscillations that are caused by the transient fault. It is concluded that the fuzzy logic controller enables the wind turbine to dampen power system oscillations. It is also concluded that, owing to the inherent non-linearities in a wind turbine and the unpredictability of the whole system, the fuzzy logic controller is very suitable for this application. (Author).

  13. DC motor speed control using fuzzy logic controller

    Science.gov (United States)

    Ismail, N. L.; Zakaria, K. A.; Nazar, N. S. Moh; Syaripuddin, M.; Mokhtar, A. S. N.; Thanakodi, S.

    2018-02-01

    The automatic control has played a vital role in the advance of engineering and science. Nowadays in industries, the control of direct current (DC) motor is a common practice thus the implementation of DC motor controller speed is important. The main purpose of motor speed control is to keep the rotation of the motor at the present speed and to drive a system at the demand speed. The main purpose of this project is to control speed of DC Series Wound Motor using Fuzzy Logic Controller (FLC). The expectation of this project is the Fuzzy Logic Controller will get the best performance compared to dc motor without controller in terms of settling time (Ts), rise time (Tr), peak time (Tp) and percent overshoot (%OS).

  14. 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.

  15. Wide-range nuclear reactor temperature control using automatically tuned fuzzy logic controller

    International Nuclear Information System (INIS)

    Ramaswamy, P.; Edwards, R.M.; Lee, K.Y.

    1992-01-01

    In this paper, a fuzzy logic controller design for optimal reactor temperature control is presented. Since fuzzy logic controllers rely on an expert's knowledge of the process, they are hard to optimize. An optimal controller is used in this paper as a reference model, and a Kalman filter is used to automatically determine the rules for the fuzzy logic controller. To demonstrate the robustness of this design, a nonlinear six-delayed-neutron-group plant is controlled using a fuzzy logic controller that utilizes estimated reactor temperatures from a one-delayed-neutron-group observer. The fuzzy logic controller displayed good stability and performance robustness characteristics for a wide range of operation

  16. A modeling of fuzzy logic controller on gamma scanning device

    International Nuclear Information System (INIS)

    Arjoni Amir

    2010-01-01

    Modeling and simulation of controller to set the high position and direction of the source of gamma radiation isotope Co-60 and Nal(TL) detector of gamma scanning device by using fuzzy logic controller FLC have been done. The high positions and in the right direction of gamma radiation and Nal (TI) detector obtained the optimal enumeration. The counting data obtained from gamma scanning device counting system is affected by the instability of high position and direction of the gamma radiation source and Nal(TI) detector or the height and direction are not equal between the gamma radiation source and Nal(TI) detector. Assumed a high position and direction of radiation sources can be fixed while the high position detector h (2, 1,0, -1, -2) can be adjusted up and down and the detector can be changed direction to the left or right angle ω (2, 1 , 0, -1, -2) when the position and direction are no longer aligned with the direction of the source of gamma radiation, the counting results obtained will not be optimal. Movement detector direction towards the left or right and the high detector arranged by the DC motor using fuzzy logic control in order to obtain the amount of output fuzzy logic control which forms the optimal output quantity count. The variation of height difference h between the source position of the gamma radiation detector and change direction with the detector angle ω becomes the input variable membership function (member function) whereas the fuzzy logic for the output variable membership function of fuzzy logic control output is selected scale fuzzy logic is directly proportional to the amount of optimal counting. From the simulation results obtained by the relationship between the amount of data output variable of fuzzy logic controller and the amount of data input variable height h and direction detector ω is depicted in graphical form surface. (author)

  17. Control of beam halo-chaos using fuzzy logic controller

    International Nuclear Information System (INIS)

    Gao Yuan; Yuan Haiying; Tan Guangxing; Luo Wenguang

    2012-01-01

    Considering the ion beam with initial K-V distribution in the periodic focusing magnetic filed channels (PFCs) as a typical sample, a fuzzy control method for control- ling beam halo-chaos was studied. A fuzzy proportional controller, using output of fuzzy inference as a control factor, was presented for adjusting exterior focusing magnetic field. The stability of controlled system was proved by fuzzy phase plane analysis. The simulation results demonstrate that the chaotic radius of envelope can be controlled to the matched radius via controlling magnetic field. This method was also applied to the multi-particle model. Under the control condition, the beam halos and its regeneration can be eliminated effectively, and that both the compactness and the uniformity of ion beam are improved evidently. Since the exterior magnetic field can be rather easily adjusted by proportional control and the fuzzy logic controller is independent to the mathematical model, this method has adaptive ability and is easily realized in experiment. The research offers a valuable reference for the design of the PFCs in the high- current linear ion accelerators. (authors)

  18. Coordinated signal control for arterial intersections using fuzzy logic

    Science.gov (United States)

    Kermanian, Davood; Zare, Assef; Balochian, Saeed

    2013-09-01

    Every day growth of the vehicles has become one of the biggest problems of urbanism especially in major cities. This can waste people's time, increase the fuel consumption, air pollution, and increase the density of cars and vehicles. Fuzzy controllers have been widely used in many consumer products and industrial applications with success over the past two decades. This article proposes a comprehensive model of urban traffic network using state space equations and then using Fuzzy Logic Tool Box and SIMULINK Program MATLAB a fuzzy controller in order to optimize and coordinate signal control at two intersections at an arterial road. The fuzzy controller decides to extend, early cut or terminate a signal phase and phase sequence to ensure smooth flow of traffic with minimal waiting time and length of queue. Results show that the performance of the proposed traffic controller at novel fuzzy model is better that of conventional controllers under normal and abnormal traffic conditions.

  19. Fuzzy logic controller for stabilization of biped robot gait

    Directory of Open Access Journals (Sweden)

    Ryadchikov I.V.

    2018-01-01

    Full Text Available The article centers round the problem of stabilization of biped robot gait through smoothing out the jumps of first and second order derivatives of a biped robot control vector using the fuzzy logic approach. The structure of a composite Takagi-Sugeno fuzzy logic controller developed by the authors is presented. The simulation study of a robot gait with climbing an obstacle is carried out and the results provided in the article showed that the developed controller performed significantly better than the analytical formula model in terms of smoothing out the derivatives of the control vector.

  20. Neutral network and fuzzy logic based grate control; Roststyrning med neutrala naetverk och fuzzy logic

    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

  1. Pneumatic motor speed control by trajectory tracking fuzzy logic

    Indian Academy of Sciences (India)

    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 ...

  2. Self-learning fuzzy logic controllers based on reinforcement

    International Nuclear Information System (INIS)

    Wang, Z.; Shao, S.; Ding, J.

    1996-01-01

    This paper proposes a new method for learning and tuning Fuzzy Logic Controllers. The self-learning scheme in this paper is composed of Bucket-Brigade and Genetic Algorithm. The proposed method is tested on the cart-pole system. Simulation results show that our approach has good learning and control performance

  3. Fuzzy Logic Decoupled Lateral Control for General Aviation Airplanes

    Science.gov (United States)

    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.

  4. Adaptive Interval Type-2 Fuzzy Logic Control for PMSM Drives with a Modified Reference Frame

    KAUST Repository

    Chaoui, Hicham; Khayamy, Mehdy; Aljarboua, Abdullah Abdulaziz

    2017-01-01

    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

  5. Autonomous vehicle motion control, approximate maps, and fuzzy logic

    Science.gov (United States)

    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.

  6. Distributed traffic signal control using fuzzy logic

    Science.gov (United States)

    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.

  7. Fuzzy logic control of vehicle suspensions with dry friction nonlinearity

    Indian Academy of Sciences (India)

    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 ...

  8. Self-tuning fuzzy logic nuclear reactor controller

    International Nuclear Information System (INIS)

    Sharif Heger, A.; Alang-Rashid, N.K.

    1996-01-01

    We present a method for self-tuning of fuzzy logic controllers based on the estimation of the optimum value of the centroids of its output fuzzy set. The method can be implemented on-line and does not require modification of membership functions and control rules. The main features of this method are: the rules are left intact to retain the operator's expertise in the FLC rule base, and the parameters that require any adjustment are identifiable in advance and their number is kept at a minimum. Therefore, the use of this method preserves the control statements in the original form. Results of simulation and actual tests show that this tuning method improves the performance of fuzzy logic controllers in following the desired reactor power level trajectories. In addition, this method demonstrates a similar improvement for power up and power down experiments, based on both simulation and actual case studies. For these experiments, the control rules for the fuzzy logic controller were derived from control statements that expressed the relationships between error, rate of error change, and duration of direction of control rod movements

  9. Fuzzy Logic Applied to an Oven Temperature Control System

    Directory of Open Access Journals (Sweden)

    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.

  10. Switch Reluctance Motor Control Based on Fuzzy Logic System

    Directory of Open Access Journals (Sweden)

    S. V. 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.

  11. Application of fuzzy logic control system for reactor feed-water control

    International Nuclear Information System (INIS)

    Iijima, T.; Nakajima, Y.

    1994-01-01

    The successful actual application of a fuzzy logic control system to the a nuclear Fugen nuclear power reactor is described. Fugen is a heavy-water moderated, light-water cooled reactor. The introduction of fuzzy logic control system has enabled operators to control the steam drum water level more effectively in comparison to a conventional proportional-integral (PI) control system

  12. Fuzzy logic controllers and chaotic natural convection loops

    International Nuclear Information System (INIS)

    Theler, German

    2007-01-01

    The study of natural circulation loops is a subject of special concern for the engineering design of advanced nuclear reactors, as natural convection provides an efficient and completely passive heat removal system. However, under certain circumstances thermal-fluid-dynamical instabilities may appear, threatening the reactor safety as a whole.On the other hand, fuzzy logic controllers provide an ideal framework to approach highly non-linear control problems. In the present work, we develop a software-based fuzzy logic controller and study its application to chaotic natural convection loops.We numerically analyse the linguistic control of the loop known as the Welander problem in such conditions that, if the controller were not present, the circulation flow would be non-periodic unstable.We also design a Taka gi-Sugeno fuzzy controller based on a fuzzy model of a natural convection loop with a toroidal geometry, in order to stabilize a Lorenz-chaotic behaviour.Finally, we show experimental results obtained in a rectangular natural circulation loop [es

  13. Fuzzy Logic Supervised Teleoperation Control for Mobile Robot

    Institute of Scientific and Technical Information of China (English)

    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.

  14. Intelligent control-I: review of fuzzy logic and fuzzy set theory

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    In the past decade or so, fuzzy systems have supplanted conventional technologies in many engineering systems, in particular in control systems and pattern recognition. Fuzzy logic has found applications in a variety of consumer products e.g. washing machines, camcorders, digital cameras, air conditioners, subway trains, cement kilns and many others. The fuzzy technology is also being applied in information technology, where it provides decision-support and expert systems with powerful reasoning capabilities. Fuzzy sets, introduced by Zadeh in 1965 as a mathematical way to represent vagueness in linguistics, can be considered a generalisation of classical set theory. Fuzziness is often confused with probability. This lecture will introduce the principal concepts and mathematical notions of fuzzy set theory. (author)

  15. SPEED CONTROL OF DC MOTOR ON LOAD USING FUZZY LOGIC ...

    African Journals Online (AJOL)

    This paper presents the development of a fuzzy logic controller for the driver DC motor in the lube oil system of the H25 Hitachi gas turbine generator. The turbine generator is required to run at an operating pressure of 1.5bar with the low and the high pressure trip points being 0.78 bar and 1.9 bar respectively. However, the ...

  16. Implementation of a fuzzy logic/neural network multivariable controller

    International Nuclear Information System (INIS)

    Cordes, G.A.; Clark, D.E.; Johnson, J.A.; Smartt, H.B.; Wickham, K.L.; Larson, T.K.

    1992-01-01

    This paper describes a multivariable controller developed at the Idaho National Engineering Laboratory (INEL) that incorporates both fuzzy logic rules and a neural network. The controller was implemented in a laboratory demonstration and was robust, producing smooth temperature and water level response curves with short time constants. In the future, intelligent control systems will be a necessity for optimal operation of autonomous reactor systems located on earth or in space. Even today, there is a need for control systems that adapt to the changing environment and process. Hybrid intelligent control systems promise to provide this adaptive capability. Fuzzy logic implements our imprecise, qualitative human reasoning. The values of system variables (controller inputs) and control variables (controller outputs) are described in linguistic terms and subdivided into fully overlapping value ranges. The fuzzy rule base describes how combinations of input parameter ranges determine the output control values. Neural networks implement our human learning. In this controller, neural networks were embedded in the software to explore their potential for adding adaptability

  17. Self-tuning fuzzy logic nuclear reactor controller

    International Nuclear Information System (INIS)

    Alang-Rashid, N. K.; Heger, A.S.

    1994-01-01

    A method for self-timing of a fuzzy logic controller (FLC) based on the estimation of the optimum value of the centroids of the its output fuzzy sets is proposed. The method can be implemented on-line and does not modify the membership function and the control rules, thus preserving the description of control statements in their original forms. Results of simulation and actual tests show that the tuning method improves the FLCs performance in following desired reactor power level trajectories (simulation tests) and simple power up and power down experiments (simulation and actual tests). The FLC control rules were derived from control statements expressing the relations between error, rate of error change, and control rod duration and direction of movements

  18. Self-tuning fuzzy logic nuclear reactor controller

    Energy Technology Data Exchange (ETDEWEB)

    Alang-Rashid, N K; Heger, A S

    1994-12-31

    A method for self-timing of a fuzzy logic controller (FLC) based on the estimation of the optimum value of the centroids of the its output fuzzy sets is proposed. The method can be implemented on-line and does not modify the membership function and the control rules, thus preserving the description of control statements in their original forms. Results of simulation and actual tests show that the tuning method improves the FLCs performance in following desired reactor power level trajectories (simulation tests) and simple power up and power down experiments (simulation and actual tests). The FLC control rules were derived from control statements expressing the relations between error, rate of error change, and control rod duration and direction of movements.

  19. An automatic tuning method of a fuzzy logic controller for nuclear reactors

    International Nuclear Information System (INIS)

    Ramaswamy, P.; Lee, K.Y.; Edwards, R.M.

    1993-01-01

    The design and evaluation by simulation of an automatically tuned fuzzy logic controller is presented. Typically, fuzzy logic controllers are designed based on an expert's knowledge of the process. However, this approach has its limitations in the fact that the controller is hard to optimize or tune to get the desired control action. A method to automate the tuning process using a simplified Kalman filter approach is presented for the fuzzy logic controller to track a suitable reference trajectory. Here, for purposes of illustration an optimal controller's response is used as a reference trajectory to determine automatically the rules for the fuzzy logic controller. To demonstrate the robustness of this design approach, a nonlinear six-delayed neutron group plant is controlled using a fuzzy logic controller that utilizes estimated reactor temperatures from a one-delayed neutron group observer. The fuzzy logic controller displayed good stability and performance robustness characteristics for a wide range of operation

  20. Use of UPFC device controlled by fuzzy logic controllers for decoupled power flow control

    Directory of Open Access Journals (Sweden)

    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.

  1. A fuzzy logic approach to control anaerobic digestion.

    Science.gov (United States)

    Domnanovich, A M; Strik, D P; Zani, L; Pfeiffer, B; Karlovits, M; 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 next day, to obtain a high biogas quality and production. The biogas should contain a high methane concentration (over 50%) and a low concentration of components toxic for fuel cells, e.g. hydrogen sulphide, siloxanes, ammonia and mercaptanes. For producing data to test the control tool, four 20 l anaerobic Continuously Stirred Tank Reactors (CSTR) are operated. For controlling two systems were investigated: a pure fuzzy logic system and a hybrid-system which contains a fuzzy based reactor condition calculation and a hierachial neural net in a cascade of optimisation algorithms.

  2. Control of Rotary Cranes Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    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.

  3. Fuzzy logic controller for weaning neonates from mechanical ventilation.

    Science.gov (United States)

    Hatzakis, G E; Davis, G M

    2002-01-01

    Weaning from mechanical ventilation is the gradual detachment from any ventilatory support till normal spontaneous breathing can be fully resumed. To date, we have developed a fuzzy logic controller for weaning COPD adults using pressure support ventilation (PS). However, adults and newborns differ in the pathophysiology of lung disease. We therefore used our fuzzy logic-based weaning platform to develop modularized components for weaning newborns with lung disease. Our controller uses the heart rate (HR), respiratory rate (RR), tidal volume (VT) and oxygen saturation (SaO2) and their trends deltaHR/deltat, deltaVT/deltat and deltaSaO2/deltat to evaluate, respectively, the Current and Trend weaning status of the newborn. Through appropriate fuzzification of these vital signs, Current and Trend weaning status can quantitatively determine the increase/decrease in the synchronized intermittent mandatory ventilation (SIMV) setting. The post-operative weaning courses of 10 newborns, 82+/-162 days old, were assessed at 2-hour intervals for 68+/-39 days. The SIMV levels, proposed by our algorithm, were matched to those levels actually applied. For 60% of the time both values coincided. For the remaining 40%, our algorithm suggested lower SIMV support than what was applied. The Area Under the Curve for integrated ventilatory support over time was 1203+/-846 for standard ventilatory strategies and 1152+/-802 for fuzzy controller. This suggests that the algorithm, approximates the actual weaning progression, and may advocate a more aggressive strategy. Moreover, the core of the fuzzy controller facilitates adaptation for body size and diversified disease patterns and sets the premises as an infant-weaning tool.

  4. A new approach of active compliance control via fuzzy logic control for multifingered robot hand

    Science.gov (United States)

    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.

  5. Active control of flexible structures using a fuzzy logic algorithm

    Science.gov (United States)

    Cohen, Kelly; Weller, Tanchum; Ben-Asher, Joseph Z.

    2002-08-01

    This study deals with the development and application of an active control law for the vibration suppression of beam-like flexible structures experiencing transient disturbances. Collocated pairs of sensors/actuators provide active control of the structure. A design methodology for the closed-loop control algorithm based on fuzzy logic is proposed. First, the behavior of the open-loop system is observed. Then, the number and locations of collocated actuator/sensor pairs are selected. The proposed control law, which is based on the principles of passivity, commands the actuator to emulate the behavior of a dynamic vibration absorber. The absorber is tuned to a targeted frequency, whereas the damping coefficient of the dashpot is varied in a closed loop using a fuzzy logic based algorithm. This approach not only ensures inherent stability associated with passive absorbers, but also circumvents the phenomenon of modal spillover. The developed controller is applied to the AFWAL/FIB 10 bar truss. Simulated results using MATLAB© show that the closed-loop system exhibits fairly quick settling times and desirable performance, as well as robustness characteristics. To demonstrate the robustness of the control system to changes in the temporal dynamics of the flexible structure, the transient response to a considerably perturbed plant is simulated. The modal frequencies of the 10 bar truss were raised as well as lowered substantially, thereby significantly perturbing the natural frequencies of vibration. For these cases, too, the developed control law provides adequate settling times and rates of vibrational energy dissipation.

  6. Design of a Tele-Control Electrical Vehicle System Using a Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    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.

  7. Intelligent neural network and fuzzy logic control of industrial and power systems

    Science.gov (United States)

    Kuljaca, Ognjen

    The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of

  8. Implementation Of Automatic Wiper Speed Control And Headlight Modes Control Systems Using Fuzzy Logic

    OpenAIRE

    ThetKoKo; ZawMyoTun; Hla Myo Tun

    2015-01-01

    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...

  9. Prototyping qualitative controllers for fuzzy-logic controller design

    International Nuclear Information System (INIS)

    Bakhtiari, S.; Jabedar-Maralani, P.

    1999-05-01

    Qualitative controls can be designed for linear and nonlinear models with the same computational complexity. At the same time they show the general form of the proper control. These properties can help ease the design process for quantitative controls. In this paper qualitative controls are used as prototypes for the design of linear or nonlinear, and in particular Sugeno-type fuzzy, controls. The LMS identification method is used to approximate the qualitative control with the nearest fuzzy control. The method is applied to the problem of position control in a permanent magnet synchronous motor; moreover, the performance and the robustness of the two controllers are compared

  10. Metamathematics of fuzzy logic

    CERN Document Server

    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.

  11. FUZZY LOGIC CONTROL OF ELECTRIC MOTORS AND MOTOR DRIVES: FEASIBILITY STUDY

    Science.gov (United States)

    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...

  12. Controlling Smart Green House Using Fuzzy Logic Method

    Directory of Open Access Journals (Sweden)

    Rafiuddin Syam

    2017-03-01

    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

  13. 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

  14. Fuzzy Logic vs. Neutrosophic Logic: Operations Logic

    Directory of Open Access Journals (Sweden)

    Salah Bouzina

    2016-12-01

    Full Text Available The goal of this research is first to show how different, thorough, widespread and effective are the operations logic of the neutrosophic logic compared to the fuzzy logic’s operations logical. The second aim is to observe how a fully new logic, the neutrosophic logic, is established starting by changing the previous logical perspective fuzzy logic, and by changing that, we mean changing changing the truth values from the truth and falsity degrees membership in fuzzy logic, to the truth, falsity and indeterminacy degrees membership in neutrosophic logic; and thirdly, to observe that there is no limit to the logical discoveries - we only change the principle, then the system changes completely.

  15. Power control of SAFE reactor using fuzzy logic

    International Nuclear Information System (INIS)

    Irvine, Claude

    2002-01-01

    Controlling the 100 kW SAFE (Safe Affordable Fission Engine) reactor consists of design and implementation of a fuzzy logic process control system to regulate dynamic variables related to nuclear system power. The first phase of development concentrates primarily on system power startup and regulation, maintaining core temperature equilibrium, and power profile matching. This paper discusses the experimental work performed in those areas. Nuclear core power from the fuel elements is simulated using resistive heating elements while heat rejection is processed by a series of heat pipes. Both axial and radial nuclear power distributions are determined from neuronic modeling codes. The axial temperature profile of the simulated core is matched to the nuclear power profile by varying the resistance of the heating elements. The SAFE model establishes radial temperature profile equivalence by establishing 32 control zones as the nodal coordinates. Control features also allow for slow warm up, since complete shutoff can occur in the heat pipes if heat-source temperatures drop/rise below a certain minimum value, depending on the specific fluid and gas combination in the heat pipe. The entire system is expected to be self-adaptive, i.e., capable of responding to long-range changes in the space environment. Particular attention in the development of the fuzzy logic algorithm shall ensure that the system process remains at set point, virtually eliminating overshoot on start-up and during in-process disturbances. The controller design will withstand harsh environments and applications where it might come in contact with water, corrosive chemicals, radiation fields, etc

  16. Autonomous Control of a Quadrotor UAV Using Fuzzy Logic

    Science.gov (United States)

    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

  17. Virtual reality simulation of fuzzy-logic control during underwater dynamic positioning

    Science.gov (United States)

    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.

  18. Fuzzy logic in management

    CERN Document Server

    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...

  19. Fuzzy logic controller versus classical logic controller for residential hybrid solar-wind-storage energy system

    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.

  20. Fuzzy logic controller versus classical logic controller for residential hybrid solar-wind-storage energy system

    International Nuclear Information System (INIS)

    Derrouazin, A.; Aillerie, M.; Charles, J. P.; Mekkakia-Maaza, N.

    2016-01-01

    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.

  1. 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.

  2. Systematic methods for the design of a class of fuzzy logic controllers

    Science.gov (United States)

    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

  3. Feasibility analysis of fuzzy logic control for ITER Poloidal field (PF) AC/DC converter system

    Energy Technology Data Exchange (ETDEWEB)

    Hassan, Mahmood Ul; Fu, Peng [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); University of Science and Technology of China (China); Song, Zhiquan, E-mail: zhquansong@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); Chen, Xiaojiao [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); University of Science and Technology of China (China); Zhang, Xiuqing [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); Humayun, Muhammad [Shanghai Jiaotong University (China)

    2017-05-15

    Highlights: • The implementation of the Fuzzy controller for the ITER PF converter system is presented. • The comparison of the FLC and PI simulation are investigated. • The FLC single and parallel bridge operation are presented. • Fuzzification and Defuzzification algorithms are presented using FLC controller. - Abstract: This paper describes the feasibility analysis of the fuzzy logic control to increase the performance of the ITER poloidal field (PF) converter systems. A fuzzy-logic-based controller is designed for ITER PF converter system, using the traditional PI controller and Fuzzy controller (FC), the dynamic behavior and transient response of the PF converter system are compared under normal operation by analysis and simulation. The analysis results show that the fuzzy logic control can achieve better operation performance than PI control.

  4. Evaluation of a Multi-Variable Self-Learning Fuzzy Logic Controller ...

    African Journals Online (AJOL)

    In spite of the usefulness of fuzzy control, its main drawback comes from lack of a systematic control design methodology. The most challenging aspect of the design of a fuzzy logic controller is the elicitation of the control rules for its rule base. In this paper, a scheme capable of elicitation of acceptable rules for multivariable ...

  5. 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.

  6. A fuzzy logic controller for feedwater regulation in pressurized water reactors

    International Nuclear Information System (INIS)

    Eryuerek, E.E.; Upadhyaya, B.R.; Alguindigue, I.E.

    1994-01-01

    Fuzzy control refers to the application of fuzzy logic theory to control systems. In this paper fuzzy controllers for steam generator water level control and pump speed control are presented, and their performance in the presence of perturbations is discussed. In order to test the robustness of the controllers, their performance is compared with the performance of model based adaptive controllers and traditional PID controllers. The control actions calculated by the fuzzy controllers is have the characteristic of quick and smooth control compared to the others

  7. Performance analysis of PM synchronous motor using fuzzy logic and self tuning fuzzy PI speed controls

    International Nuclear Information System (INIS)

    Karakaya, A.; Karakas, E.

    2008-01-01

    Permanent Magnet Synchronous Motors have nonlinear characteristics whose dynamics changes with time. In spite of this structure the permanent magnet synchronous motor has answered engineering problems in industry such as motion control which need high torque values. This paper obtains a nonlinear mathematical model for Permanent Magnet Synchronous Motor and realizes stimulation of the obtained model in the Matlab/Simulink program. Motor parameters are determined by an experimental set-up and they are used in the motor model. Speed control of motor model is made with Fuzzy Logic and Self Tuning logic PI controllers. Using the speed graphs obtained, rise time, overshoot, steady-state error and settling time are analyzed and controller performances are compared. (author)

  8. Performance of Globally Linearized Controller and Two Region Fuzzy Logic Controller on a Nonlinear Process

    Directory of Open Access Journals (Sweden)

    N. Jaya

    2008-10-01

    Full Text Available In this work, a design and implementation of a Conventional PI controller, single region fuzzy logic controller, two region fuzzy logic controller and Globally Linearized Controller (GLC for a two capacity interacting nonlinear process is carried out. The performance of this process using single region FLC, two region FLC and GLC are compared with the performance of conventional PI controller about an operating point of 50 %. It has been observed that GLC and two region FLC provides better performance. Further, this procedure is also validated by real time experimentation using dSPACE.

  9. Fuzzy logic controller for crude oil levels at Escravos Tank Farm ...

    African Journals Online (AJOL)

    Fuzzy logic controller (FLC) for crude oil flow rates and tank levels was designed for monitoring flow and tank level management at Escravos Tank Farm in Nigeria. The fuzzy control system incorporated essence of expert knowledge required to handle the tasks. Proportional Integral Derivative (PID) control of crude flow ...

  10. Sensitivity-based self-learning fuzzy logic control for a servo system

    NARCIS (Netherlands)

    Balenovic, M.

    1998-01-01

    Describes an experimental verification of a self-learning fuzzy logic controller (SLFLC). The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model related to the fuzzy controller parameters. The effectiveness of the proposed controller has been

  11. Development of Fuzzy Logic Controller for Quanser Bench-Top Helicopter

    Science.gov (United States)

    Jafri, M. H.; Mansor, H.; Gunawan, T. S.

    2017-11-01

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

  12. Development of Fuzzy Logic Control for Vehicle Air Conditioning System

    Directory of Open Access Journals (Sweden)

    Henry Nasution

    2008-08-01

    Full Text Available A vehicle air conditioning system is experimentally investigated. Measurements were taken during the experimental period at a time interval of one minute for a set point temperature of 22, 23 and 24oC with internal heat loads of 0, 1 and 2 kW. The cabin temperature and the speed of the compressor were varied and the performance of the system, energy consumption and energy saving ware analyzed. The main objective of the experimental work is to evaluate the energy saving obtained when the fuzzy logic control (FLC algorithm, through an inverter, continuously regulates the compressor speed. It demonstrates better control of the compressor operation in terms of energy consumption as compared to the control by using a thermostat imposing On/Off cycles on the compressor at the nominal frequency of 50 Hz. The experimental set-up consists of original components from the air conditioning system of a compact passenger vehicle. The experimental results indicate that the proposed technique can save energy and improve indoor comfort significantly for vehicle air conditioning systems compared to the conventional (On/Off control technique.

  13. A fuzzy logic sliding mode controlled electronic differential for a direct wheel drive EV

    Science.gov (United States)

    Ozkop, Emre; Altas, Ismail H.; Okumus, H. Ibrahim; Sharaf, Adel M.

    2015-11-01

    In this study, a direct wheel drive electric vehicle based on an electronic differential system with a fuzzy logic sliding mode controller (FLSMC) is studied. The conventional sliding surface is modified using a fuzzy rule base to obtain fuzzy dynamic sliding surfaces by changing its slopes using the global error and its derivative in a fuzzy logic inference system. The controller is compared with proportional-integral-derivative (PID) and sliding mode controllers (SMCs), which are usually preferred to be used in industry. The proposed controller provides robustness and flexibility to direct wheel drive electric vehicles. The fuzzy logic sliding mode controller, electronic differential system and the overall electrical vehicle mechanism are modelled and digitally simulated by using the Matlab software. Simulation results show that the system with FLSMC has better efficiency and performance compared to those of PID and SMCs.

  14. Efficient Fuzzy Logic Controller for Magnetic Levitation Systems

    African Journals Online (AJOL)

    Akorede

    ABSTRACT: Magnetic levitation is a system of suspending a body or a complete system against gravity. Suspending a system ... disturbance signal was applied to the input of the control system. Fuzzy ..... Automatic Control System, fifth edition.

  15. Energy Analysis for Air Conditioning System Using Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    Henry Nasution

    2011-04-01

    Full Text Available Reducing energy consumption and to ensure thermal comfort are two important considerations for the designing an air conditioning system. An alternative approach to reduce energy consumption proposed in this study is to use a variable speed compressor. The control strategy will be proposed using the fuzzy logic controller (FLC. FLC was developed to imitate the performance of human expert operators by encoding their knowledge in the form of linguistic rules. The system is installed on a thermal environmental room with a data acquisition system to monitor the temperature of the room, coefficient of performance (COP, energy consumption and energy saving. The measurements taken during the two hour experimental periods at 5-minutes interval times for temperature setpoints of 20oC, 22oC and 24oC with internal heat loads 0, 500, 700 and 1000 W. The experimental results indicate that the proposed technique can save energy in comparison with On/Off and proportional-integral-derivative (PID control.

  16. Operational Investigation of Overhead Crane with Fuzzy Logic Anti-Swing Controller Using 3-D Simulation

    Directory of Open Access Journals (Sweden)

    Y. N. Petrenko

    2011-01-01

    Full Text Available The purpose of a crane control system is to provide load transfer with minimum swinging. The paper presents a developed three-dimensional simulation model of a bridge crane with fuzzy logic controller designed with application of genetic algorithms. Comparative indices of oscillation while load transferring are given in the paper. The indices have been obtained at various parameters of the fuzzy logic controller

  17. 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. .

  18. evaluation of a multi-variable self-learning fuzzy logic controller

    African Journals Online (AJOL)

    Dr Obe

    2003-03-01

    Mar 1, 2003 ... The most challenging aspect of the design of a fuzzy logic controller is ... inaccuracy (or structured uncertainty) and unmodelled ... mathematical analysis on paper is impossible ... output (SISO) system that can self-construct ...

  19. Depth Control of Sevofluorane Anesthesia with Microcontroller Based Fuzzy Logic System

    National Research Council Canada - National Science Library

    Yardimci, A

    2001-01-01

    ... at the end of the anesthesia. In this study, sevofluorane depth of anesthesia was examined through a microcontroller-based fuzzy logic control system according to the blood pressure and heart rate taken from the patient...

  20. 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.

  1. DFCL: DYNAMIC FUZZY LOGIC CONTROLLER FOR INTRUSION DETECTION

    Directory of Open Access Journals (Sweden)

    Abdulrahim Haroun Ali

    2014-08-01

    Full Text Available Intrusions are a problem with the deployment of Networks which give misuse and abnormal behavior in running reliable network operations and services. In this work, a Dynamic Fuzzy Logic Controller (DFLC is proposed for an anomaly detection problem, with the aim of solving the problem of attack detection rate and faster response process. Data is collected by PingER project. PingER project actively measures the worldwide Internet’s end-to-end performance. It covers over 168 countries around the world. PingER uses simple ubiquitous Internet Ping facility to calculate number of useful performance parameters. From each set of 10 pings between a monitoring host and a remote host, the features being calculated include Minimum Round Trip Time (RTT, Jitter, Packet loss, Mean Opinion Score (MOS, Directness of Connection (Alpha, Throughput, ping unpredictability and ping reachability. A set of 10 pings is being sent from the monitoring node to the remote node every 30 minutes. The received data shows the current characteristic and behavior of the networks. Any changes in the received data signify the existence of potential threat or abnormal behavior. D-FLC uses the combination of parameters as an input to detect the existence of any abnormal behavior of the network. The proposed system is simulated in Matlab Simulink environment. Simulations results show that the system managed to catch 95% of the anomalies with the ability to distinguish normal and abnormal behavior of the network.

  2. 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.

  3. CONTROL SYSTEM DESIGN WITH FUZZY LOGIC PID-СONTROLLER TYPE 2

    Directory of Open Access Journals (Sweden)

    A. Tунік

    2011-04-01

    Full Text Available This paper presents a fuzzy logic PID-controller synthesis method for solid body guidance. Formany nonlinear systems with nonlinearities and uncertainties, the performance of fuzzy controllertype 1 may not be satisfactory. Therefore, in this work, fuzzy logic type 2 controller design isintroduced. These controllers capture the advantage of a linear controller in terms of simplicity andalso can handle nonlinearity because of their inference mechanism.The main feature of the proposedmethod constitutes in a membership functions type 2 applications. The membership function type 2is represented by upper and lower membership functions of type 1. The interval between these twofunctions represent the footprint of uncertainty, which give an opportunity to synthesize commonregulator for set of a models. The structure of fuzzy logic controller for solid body control isgrounded. Simulation results confirm the effectiveness of the proposed approach.

  4. Fuel Saving Strategy in Spark Ignition Engine Using Fuzzy Logic Engine Torque Control

    OpenAIRE

    Aris Triwiyatno; Sumardi

    2012-01-01

    In the case of injection gasoline engine, or better known as spark ignition engines, an effort to improve engine performance as well as to reduce fuel consumption is a fairly complex problem. Generally, engine performance improvement efforts will lead to increase in fuel consumption. However, this problem can be solved by implementing engine torque control based on intelligent regulation such as the fuzzy logic inference system. In this study, fuzzy logic engine torque regulation is used to c...

  5. Dynamic Fuzzy Logic Parameter Tuning for ACO and Its Application in the Fuzzy Logic Control of an Autonomous Mobile Robot

    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.

  6. Real Time Implementation of a DC Motor Speed Control by Fuzzy Logic Controller and PI Controller Using FPGA

    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.

  7. Fuzzy logic control of water level in advanced boiling water reactor

    International Nuclear Information System (INIS)

    Lin, Chaung; Lee, Chi-Szu; Raghavan, R.; Fahrner, D.M.

    1995-01-01

    The feedwater control system in the Advanced Boiling Water Reactor (ABWR) is more challenging to design compared to other control systems in the plant, due to the possible change in level from void collapses and swells during transient events. A basic fuzzy logic controller is developed using a simplified ABWR mathematical model to demonstrate and compare the performance of this controller with a simplified conventional controller. To reduce the design effort, methods are developed to automatically tune the scaling factors and control rules. As a first step in developing the fuzzy controller, a fuzzy controller with a limited number of rules is developed to respond to normal plant transients such as setpoint changes of plant parameters and load demand changes. Various simulations for setpoint and load demand changes of plant performances were conducted to evaluate the modeled fuzzy logic design against the simplified ABWR model control system. The simulation results show that the performance of the fuzzy logic controller is comparable to that of the Proportional-Integral (PI) controller, However, the fuzzy logic controller produced shorter settling time for step setpoint changes compared to the simplified conventional controller

  8. Control of a classical microtron and application of fuzzy logic

    International Nuclear Information System (INIS)

    Krist, Pavel; Bila, Jiri

    2011-01-01

    Control problems of the classical microtron with a Kapitza type accelerating cavity were addressed. A fuzzy controller was used, which enabled the system to be controlled even though the accelerating voltage, whose setting is vital for maintaining the accelerator in the stable state, cannot not be measured

  9. Automatic generation control of TCPS based hydrothermal system under open market scenario: A fuzzy logic approach

    Energy Technology Data Exchange (ETDEWEB)

    Rao, C. Srinivasa [EEE Department, G. Pulla Reddy Engineering College, Kurnool, Andhra Pradesh (India); Nagaraju, S. Siva [EEE Department, J.N.T.U College of Engg., Kakinada, Andhra Pradesh (India); Raju, P. Sangameswara [EEE Department, S.V. University, Tirupati, Andhra Pradesh (India)

    2009-09-15

    This paper presents the analysis of automatic generation control of a two-area interconnected thyristor controlled phase shifter based hydrothermal system in the continuous mode using fuzzy logic controller under open market scenario. Open transmission access and the evolving of more socialized companies for generation, transmission and distribution affects the formulation of AGC problem. So the traditional AGC two-area system is modified to take into account the effect of bilateral contracts on the dynamics. It is possible to stabilize the system frequency and tie-power oscillations by controlling the phase angle of TCPS which is expected to provide a new ancillary service for the future power systems. A control strategy using TCPS is proposed to provide active control of system frequency. Further dynamic responses for small perturbation considering fuzzy logic controller and PI controller (dual mode controller) have been observed and the superior performance of fuzzy logic controller has been reported analytically and also through simulation. (author)

  10. Fuzzy Logic Based MPPT Controller for a PV System

    Directory of Open Access Journals (Sweden)

    Carlos Robles Algarín

    2017-12-01

    Full Text Available The output power of a photovoltaic (PV module depends on the solar irradiance and the operating temperature; therefore, it is necessary to implement maximum power point tracking controllers (MPPT to obtain the maximum power of a PV system regardless of variations in climatic conditions. The traditional solution for MPPT controllers is the perturbation and observation (P&O algorithm, which presents oscillation problems around the operating point; the reason why improving the results obtained with this algorithm has become an important goal to reach for researchers. This paper presents the design and modeling of a fuzzy controller for tracking the maximum power point of a PV System. Matlab/Simulink (MathWorks, Natick, MA, USA was used for the modeling of the components of a 65 W PV system: PV module, buck converter and fuzzy controller; highlighting as main novelty the use of a mathematical model for the PV module, which, unlike diode based models, only needs to calculate the curve fitting parameter. A P&O controller to compare the results obtained with the fuzzy control was designed. The simulation results demonstrated the superiority of the fuzzy controller in terms of settling time, power loss and oscillations at the operating point.

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

    Science.gov (United States)

    Sahoo, Narayan; Tripathy, Ashis; Sharma, Priyaranjan

    2018-03-01

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

  12. Beta normal control of TFTR using fuzzy logic

    International Nuclear Information System (INIS)

    Lawson, J.E.; Bell, M.G.; Marsala, R.J.; Mueller, D.

    1995-01-01

    In TFTR plasmas heated by neutral beam injection, the fusion power yield increases rapidly with the plasma pressure. However, the pressure is limited by the onset of instabilities which may result in plasma disruptions that would have had an adverse effect on the performance of subsequent discharges and increase the risk of damage to internal components. The likelihood of disruption has been found to correlate with the normalized beta, defined as βN = 2 x 10 8 μ circle left angle p perpendicular to right angle a / BTIp where left angle p perpendicular to right angle is the volume-average plasma perpendicular pressure, a the mid-plane minor radius of the plasma, BT the toroidal magnetic field and Ip the plasma current. Other variables, such as the peaking of the plasma pressure and current profiles, have been found to influence the threshold of βN at which the probability of disruption begins to increase significantly. For TFTR plasmas with high fusion performance (TFTR ''supershots'') the probability of disruption has been found to increase rapidly for βN > 1.8. Since confinement in this regime is affected by plasma-wall interaction, which can vary from shot to shot, operation at high βN with preprogrammed heating power pulses can produce an unacceptably high risk of disruption. To reduce the risk of producing beta-limit disruptions during neutral beam heating experiments, a control system, the Neutral Beam Power Feedback System (NBPFS), has been developed to modulate the total heating power by switching individual neutral beam sources on and off in response to the evolution of the normalized beta so that the limit will not be exceeded. The value of βN is calculated in real time and transmitted to the NBPFS. The value of βN and its calculated time derivative are input to a fuzzy logic controller which implements a proportional-derivative control based on the difference between βN and a programmed reference level βNREF which can be programmed as a function

  13. Fuzzy Logic and PID control of a 3 DOF Robotic Arm

    Directory of Open Access Journals (Sweden)

    Korhan Kayışlı

    2017-12-01

    Full Text Available The robotic arms are used in many industrial applications at the present time. At this point, high precision control is required for robotics used in fields such as healthcare area. Therefore, the control method applied to robots is also important. In this study, a force was applied to the end function of a three degree-of-freedom robot and the robustness of the controllers are tested. PID and Fuzzy Logic control method are used for this process. The control process of robotic arm which is designed and simulated is obtained by using Fuzzy Logic and classical PID controllers and the results are presented comparatively

  14. Intuitionistic fuzzy logics

    CERN Document Server

    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.

  15. Design of a fuzzy logic based controller for neutron power regulation

    International Nuclear Information System (INIS)

    Velez D, D.

    2000-01-01

    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)

  16. Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms

    CERN Document Server

    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...

  17. Fuzzy logic applied to the control of the energy consumption in intelligent buildings; Logica fuzzy aplicada ao controle do consumo de energia eletrica em edificios inteligentes

    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.

  18. Design a Fuzzy Logic Controller for a Rotary Flexible Joint Robotic Arm

    Directory of Open Access Journals (Sweden)

    Jalani Jamaludin

    2018-01-01

    Full Text Available The purpose of this research is to design a fuzzy logic feedback controller (FLC in order to control a desired tip angle position a rotary flexible joint robotic arm. The FLC is also employed to dampen the vibration emanated from a rotary flexible joint robotic arm when reaching a desired tip angle position. The performance of FLC is tested in simulation and experiment. It is found that the FLC is successfully designed, applied and tested. The results show that fuzzy logic controller performed satisfactorily control a desired tip angle position and reduce the oscillations.

  19. Implementation Of Automatic Wiper Speed Control And Headlight Modes Control Systems Using Fuzzy Logic

    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.

  20. A fuzzy-logic antiswing controller for three-dimensional overhead cranes.

    Science.gov (United States)

    Cho, Sung-Kun; Lee, Ho-Hoon

    2002-04-01

    In this paper, a new fuzzy antiswing control scheme is proposed for a three-dimensional overhead crane. The proposed control consists of a position servo control and a fuzzy-logic control. The position servo control is used to control crane position and rope length, and the fuzzy-logic control is used to suppress load swing. The proposed control guarantees not only prompt suppression of load swing but also accurate control of crane position and rope length for simultaneous travel, traverse, and hoisting motions of the crane. Furthermore, the proposed control provides practical gain tuning criteria for easy application. The effectiveness of the proposed control is shown by experiments with a three-dimensional prototype overhead crane.

  1. Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

    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)

  2. Fuzzy logic controller implementation for a solar air-conditioning system

    International Nuclear Information System (INIS)

    Lygouras, J.N.; Botsaris, P.N.; Vourvoulakis, J.; Kodogiannis, V.

    2007-01-01

    The implementation of a variable structure fuzzy logic controller for a solar powered air conditioning system and its advantages are investigated in this paper. Two DC motors are used to drive the generator pump and the feed pump of the solar air-conditioner. Two different control schemes for the DC motors rotational speed adjustment are implemented and tested: the first one is a pure fuzzy controller, its output being the control signal for the DC motor driver. A 7 x 7 fuzzy matrix assigns the controller output with respect to the error value and the derivative of the error. The second scheme is a two-level controller. The lower level is a conventional PID controller, and the higher level is a fuzzy controller acting over the parameters of the low level controller. Step response of the two control loops are presented as experimental results. The contribution of this design is that in the control system, the fuzzy logic is implemented through software in a common, inexpensive, 16-bit microcontroller, which does not have special abilities for fuzzy control

  3. Fuzzy logic controller implementation for a solar air-conditioning system

    Energy Technology Data Exchange (ETDEWEB)

    Lygouras, J.N.; Vourvoulakis, J. [Laboratory of Electronics, School of Electrical and Computer Engineering, Democritus University of Thrace, Vas. Sofias 12, 67100 Xanthi (Greece); Botsaris, P.N. [Laboratory of Materials, Processes and Mechanical Design, School of Production and Management Engineering, Democritus University of Thrace 67100 Xanthi (Greece); Kodogiannis, V. [Centre for Systems Analysis, School of Computer Science, University of Westminster, London, HA1 3TP (United Kingdom)

    2007-12-15

    The implementation of a variable structure fuzzy logic controller for a solar powered air conditioning system and its advantages are investigated in this paper. Two DC motors are used to drive the generator pump and the feed pump of the solar air-conditioner. Two different control schemes for the DC motors rotational speed adjustment are implemented and tested: the first one is a pure fuzzy controller, its output being the control signal for the DC motor driver. A 7 x 7 fuzzy matrix assigns the controller output with respect to the error value and the derivative of the error. The second scheme is a two-level controller. The lower level is a conventional PID controller, and the higher level is a fuzzy controller acting over the parameters of the low level controller. Step response of the two control loops are presented as experimental results. The contribution of this design is that in the control system, the fuzzy logic is implemented through software in a common, inexpensive, 16-bit microcontroller, which does not have special abilities for fuzzy control. (author)

  4. Realworld maximum power point tracking simulation of PV system based on Fuzzy Logic control

    Science.gov (United States)

    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.

  5. 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.

  6. Adaptive Fuzzy Logic based MPPT Control for PV System Under Partial Shading Condition

    OpenAIRE

    Choudhury, Subhashree; Rout, Pravat Kumar

    2016-01-01

    Partial shading causes power loss, hotspots and threatens the reliability of the Photovoltaic generation system. Moreover characteristic curves exhibit multiple peaks. Conventional MPPT techniques under this condition often fail to give optimum MPP. Focusing on the afore mentioned problem an attempt has been made to design an Adaptive Takagi-Sugeno Fuzzy Inference System based Fuzzy Logic Control MPPT.The mathematical model of PV array is simulated using in MATLAB/Simulink environment.Various...

  7. Fuzzy Logic Controlled Solar Module for Driving Three- Phase Induction Motor

    Science.gov (United States)

    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.

  8. Fuzzy Logic Controlled Solar Module for Driving Three- Phase Induction Motor

    International Nuclear Information System (INIS)

    Zainal, Nurul Afiqah; Tat, Chan Sooi; Ajisman

    2016-01-01

    Renewable energy produced by solar module gives advantages for generated three- phase induction motor in remote area. But, solar module's output 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. (paper)

  9. Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control

    International Nuclear Information System (INIS)

    Itik, Mehmet; Sabetghadam, Mohammadreza; Alici, Gursel

    2014-01-01

    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. (paper)

  10. Control of motion stability of the line tracer robot using fuzzy logic and kalman filter

    Science.gov (United States)

    Novelan, M. S.; Tulus; Zamzami, E. M.

    2018-03-01

    Setting of motion and balance line tracer robot two wheels is actually a combination of a two-wheeled robot balance concept and the concept of line follower robot. The main objective of this research is to maintain the robot in an upright and can move to follow the line of the Wizard while maintaining balance. In this study the motion balance system on line tracer robot by considering the presence of a noise, so that it takes the estimator is used to mengestimasi the line tracer robot motion. The estimation is done by the method of Kalman Filter and the combination of Fuzzy logic-Fuzzy Kalman Filter called Kalman Filter, as well as optimal smooting. Based on the results of the study, the value of the output of the fuzzy results obtained from the sensor input value has been filtered before entering the calculation of the fuzzy. The results of the output of the fuzzy logic hasn’t been able to control dc motors are well balanced at the moment to be able to run. The results of the fuzzy logic by using membership function of triangular membership function or yet can control with good dc motor movement in order to be balanced

  11. FUZZY LOGIC CONTROLLER AS MODELING TOOL FOR THE BURNING PROCESS OF A CEMENT PRODUCTION PLANT

    Directory of Open Access Journals (Sweden)

    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.

  12. ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

    Institute of Scientific and Technical Information of China (English)

    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.

  13. Nuclear reactor control with fuzzy logic approaches - strengths, weakness, opportunities, and threats

    International Nuclear Information System (INIS)

    Ruan, Da

    2004-01-01

    As part of the special track on 'Lessons learned from computational intelligence in nuclear applications' at the forthcoming FLINS 2004 conference on Applied Computational Intelligence (Blankenberge, Belgium, September 1-3, 2004), research experiences on fuzzy logic techniques in applications of nuclear reactor control operation are critically reviewed in this presentation. Assessment of four real fuzzy control applications at the MIT research reactor in the US, the FUGEN heavy water reactor in Japan, the BR1 research reactor in Belgium, and a TRIGA Mark III reactor in Mexico will be examined thought a SWOT analysis (strengths, weakness, opportunities, and threats). Special attention will be paid to the current cooperation between the Belgian Nuclear Research Centre (SCK-CEN) and the Mexican Nuclear Centre (ININ) on the fuzzy logic control for nuclear reactor control project under the partial support of the National Council for Science and Technology of Mexico (CONACYT). (Author)

  14. Speed Control Design of Permanent Magnet Synchronous Motor using TakagiSugeno Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    Ahmad Asri Abd Samat

    2017-12-01

    Full Text Available This paper proposes a speed control design of Permanent Magnet Synchronous Motor (PMSM using Field Oriented Control (FOC. The focus is to design a speed control using Takagi — Sugeno Fuzzy Logic Control (T-S FLS. These systems will replace the conventional method which is proportional-integral (PI. The objective of this paper is to study the T—S Fuzzy Inference System (FIS speed regulator and acceleration observer for PMSM. The scope of study basically is to design and analyse the Takagi Sugeno FLC and the PMSM. This paper also will describe the methodology and process of modelling the PMSM including data analysis. The simulation work is implemented in Matlab-Simulink to verify the control method. The effectiveness of this proposed control method was confirmed through various range of speed and torque variation.

  15. FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM

    Science.gov (United States)

    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...

  16. Controlling the power output of a nuclear reactor with fuzzy logic

    NARCIS (Netherlands)

    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

  17. Controlling the Power Output of a Nuclear Reactor with Fuzzy Logic

    NARCIS (Netherlands)

    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

  18. FUZZY-LOGIC-BASED CONTROLLERS FOR EFFICIENCY OPTIMIZATION OF INVERTER-FED INDUCTION MOTOR DRIVES

    Science.gov (United States)

    This paper describes a fuzzy-logic-based energy optimizing controller to improve the efficiency of induction motor/drives operating at various load (torque) and speed conditions. Improvement of induction motor efficiency is important not only from the considerations of energy sav...

  19. A VIRTUAL REALITY EXPOSURE THERAPY FOR PTSD PATIENTS CONTROLLED BY A FUZZY LOGIC SYSTEM

    OpenAIRE

    Rosa Maria Esteves Moreira da Costa; Fernando Moraes de Oliveira; Regina Serrão Lanzillotti; Raquel Gonçalves; Luis Alfredo Vidal de Carvalho

    2014-01-01

    This paper describes the main characteristics of two integrated systems that explore Virtual Reality technology and Fuzzy Logic to support and to control the assessment of people with Post-Traumatic Stress Disorder during the Virtual Reality Exposure Therapy. The integration of different technologies, the development methodology and the test procedures are described throughout the paper.

  20. A VIRTUAL REALITY EXPOSURE THERAPY FOR PTSD PATIENTS CONTROLLED BY A FUZZY LOGIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Rosa Maria Esteves Moreira da Costa

    2014-06-01

    Full Text Available This paper describes the main characteristics of two integrated systems that explore Virtual Reality technology and Fuzzy Logic to support and to control the assessment of people with Post-Traumatic Stress Disorder during the Virtual Reality Exposure Therapy. The integration of different technologies, the development methodology and the test procedures are described throughout the paper.

  1. A virtual reality exposure therapy for PTSD patients controlled by a fuzzy logic system

    OpenAIRE

    Oliveira, F. M.; Lanzillotti, R. S.; Da Costa, R. M. E. M.; Gonçalves, R.; Ventura, P.; Carvalho, L. A. V. de

    2014-01-01

    This paper describes the main characteristics of two integrated systems that explore Virtual Reality technology and Fuzzy Logic to support and to control the assessment of people with Post-Traumatic Stress Disorder during the Virtual Reality Exposure Therapy. The integration of different technologies, the development methodology and the test procedures are described throughout the paper. Peer Reviewed

  2. Fuzzy logic electric vehicle regenerative antiskid braking and traction control system

    Science.gov (United States)

    Cikanek, Susan R.

    1994-01-01

    An regenerative antiskid braking and traction control system using fuzzy logic for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensor and determining if regenerative antiskid braking control, requiring hydraulic braking control, and requiring traction control are required. The processor then employs fuzzy logic based on the determined vehicle state and provides command signals to a motor controller to control operation of the electric traction motor and to the brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative braking control, hydraulic braking control, and traction control.

  3. Fuzzy logic electric vehicle regenerative antiskid braking and traction control system

    Science.gov (United States)

    Cikanek, S.R.

    1994-10-25

    An regenerative antiskid braking and traction control system using fuzzy logic for an electric or hybrid vehicle having a regenerative braking system operatively connected to an electric traction motor, and a separate hydraulic braking system includes sensors for monitoring present vehicle parameters and a processor, responsive to the sensors, for calculating vehicle parameters defining the vehicle behavior not directly measurable by the sensor and determining if regenerative antiskid braking control, requiring hydraulic braking control, and requiring traction control are required. The processor then employs fuzzy logic based on the determined vehicle state and provides command signals to a motor controller to control operation of the electric traction motor and to the brake controller to control fluid pressure applied at each vehicle wheel to provide the appropriate regenerative braking control, hydraulic braking control, and traction control. 123 figs.

  4. Variable structure TITO fuzzy-logic controller implementation for a solar air-conditioning system

    Energy Technology Data Exchange (ETDEWEB)

    Lygouras, J.N.; Pachidis, Th. [Laboratory of Electronics, School of Electrical and Computer Engineering, Democritus University of Thrace, GR-67100 Xanthi (Greece); Kodogiannis, V.S. [Centre for Systems Analysis, School of Computer Science, University of Westminster, London HA1 3TP (United Kingdom); Tarchanidis, K.N. [Department of Petroleum Technology, Technological Education Institute of Kavala, GR-65404, Kavala (Greece); Koukourlis, C.S. [Laboratory of Telecommunications, School of Electrical and Computer Engineering, Democritus University of Thrace, GR-67100 Xanthi (Greece)

    2008-04-15

    The design and implementation of a Two-Input/Two-Output (TITO) variable structure fuzzy-logic controller for a solar-powered air-conditioning system is described in this paper. Two DC motors are used to drive the generator pump and the feed pump of the solar air-conditioner. The first affects the temperature in the generator of the solar air-conditioner, while the second, the pressure in the power loop. The difficulty of Multi-Input/Multi-Output (MIMO) systems control is how to overcome the coupling effects among each degree of freedom. First, a traditional fuzzy-controller has been designed, its output being one of the components of the control signal for each DC motor driver. Secondly, according to the characteristics of the system's dynamics coupling, an appropriate coupling fuzzy-controller (CFC) is incorporated into a traditional fuzzy-controller (TFC) to compensate for the dynamic coupling among each degree of freedom. This control strategy simplifies the implementation problem of fuzzy control, but can also improve the control performance. This mixed fuzzy controller (MFC) can effectively improve the coupling effects of the systems, and this control strategy is easy to design and implement. Experimental results from the implemented system are presented. (author)

  5. CONTROL TEMPERATURE ON PLANT BABY INCUBATOR WITH FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Noor Yulita Dwi Setyaningsih

    2016-04-01

    Full Text Available Inkubator bayi merupakan salah satu media medis yang digunakan untuk menjaga kondisi suhu dari bayi prematur atau bayi yang baru lahir. Suhu merupakan salah satu faktor yang sangat penting untuk dijaga bagi bayi baru lahir, karena kondisi bayi baru lahir yang tidak stabil dan belum bisa melakukan produksi panas sendiri untuk menghangatkan tubuhnya dan memproduksi panas untuk menjaga kestabilan tubuhnya. Kendali logika fuzzy digunakan untuk mengendalikan suhu pada penelitian ini, karena kebutuhan bayi yang berbeda-beda sehingga pemanfaatan sistem kendali fuzzy ini sangat mempermudah dalam melakukan pengendalian. Parameter yang digunakan dalam pengendalian ini adalah nilai Error, d-eror, dan sinyal kontrol. Hasil penggunaan sistem kendali logika fuzzy untuk pengendalian suhu pada plant inkubator bayi adalah kesalahan yang terjadi dapat dikurangi dan kestabilan dapat dipertahankan. Meskipun adanya gangguan yang diberikan pada sistem, dengan pemanfaatan sistem kendali fuzzy ini, dapat menjaga sistem pada keadaan yang stabil. Kata kunci: sistem kendali, temperature, inkubator bayi, plant, logika fuzzy, new born.

  6. Improved Fuzzy Logic based DTC of Induction machine for wide range of speed control using AI based controllers

    Directory of Open Access Journals (Sweden)

    H. Sudheer

    2016-06-01

    Full Text Available This paper presents improvements in Direct Torque control of induction motor using Fuzzy logic switching controller (FDTC. The conventional DTC (CDTC and FDTC drive performance is compared using Conventional PI, Fuzzy controller and Neural Network controllers. The major disadvantages of CDTC are high torque and flux ripples in steady state operation of the drive, inferior performance at low speed operation and variable switching frequency. The presence of hysteresis bands is the major reason for high torque and flux ripples in CDTC. In FDTC the hysteresis band and switching table are replaced by Fuzzy logic switching controller. Using fuzzy logic torque, stator flux space are divided into smaller subsections which results in precise and optimal selection of switching state to meet load torque. In high performance drives accurate tuning of PI speed controller is required. The conventional PI controller cannot adapt to the variation in model parameters. Artificial intelligence based fuzzy controller and neural network controller are compared with PI controller for both CDTC and FDTC of Induction machine. The proposed schemes are developed in Matlab/Simulink environment. Simulation results shows reduction in torque and flux ripples in FDTC and dynamic performance of the drive at low speeds and sudden change in load torque can be improved using Fuzzy logic controller compared to PI and neural network controller.

  7. Fuzzy logic-based advanced on–off control for thermal comfort in residential buildings

    International Nuclear Information System (INIS)

    Kang, Chang-Soon; Hyun, Chang-Ho; Park, Mignon

    2015-01-01

    Highlights: • Fuzzy logic-based advanced on–off control is proposed. • An anticipative control mechanism is implemented by using fuzzy theory. • Novel thermal analysis program including solar irradiation as a factor is developed. • The proposed controller solves over-heating and under-heating thermal problems. • Solar energy compensation method is applied to compensate for the solar energy. - Abstract: In this paper, an advanced on–off control method based on fuzzy logic is proposed for maintaining thermal comfort in residential buildings. Due to the time-lag of the control systems and the late building thermal response, an anticipative control mechanism is required to reduce energy loss and thermal discomfort. The proposed controller is implemented based on an on–off controller combined with a fuzzy algorithm. On–off control was chosen over other conventional control methods because of its structural simplicity. However, because conventional on–off control has a fixed operating range and a limited ability for improvements in control performance, fuzzy theory can be applied to overcome these limitations. Furthermore, a fuzzy-based solar energy compensation algorithm can be applied to the proposed controller to compensate for the energy gained from solar radiation according to the time of day. Simulations were conducted to compare the proposed controller with a conventional on–off controller under identical external conditions such as outdoor temperature and solar energy; these simulations were carried out by using a previously reported thermal analysis program that was modified to consider such external conditions. In addition, experiments were conducted in a residential building called Green Home Plus, in which hydronic radiant floor heating is used; in these experiments, the proposed system performed better than a system employing conventional on–off control methods

  8. Localized and Energy-Efficient Topology Control in Wireless Sensor Networks Using Fuzzy-Logic Control Approaches

    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.

  9. Fuzzy logic, PSO based fuzzy logic algorithm and current controls comparative for grid-connected hybrid system

    Science.gov (United States)

    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.

  10. Fuzzy Logic System for Intermixed Biogas and Photovoltaics Measurement and Control

    Directory of Open Access Journals (Sweden)

    Liston Matindife

    2018-01-01

    Full Text Available This study develops a new integrated measurement and control system for intermixed biogas and photovoltaic systems to achieve safe and optimal energy usage. Literature and field studies show that existing control methods on small- to medium-scale systems fall short of comprehensive system optimization and fault diagnosis, hence the need to revisit these control methods. The control strategy developed in this study is intelligent as it is wholly based on fuzzy logic algorithms. Fuzzy logic controllers due to their superior nonlinear problem solving capabilities to classical controllers considerably simplify controller design. The mathematical models that define classical controllers are difficult or impossible to realize in biogas and photovoltaic generation process. A microcontroller centered fuzzy logic measurement and control embedded system is designed and developed on the existing hybrid biogas and photovoltaic installations. The designed system is able to accurately predict digester stability, quantify biogas output, and carry out biogas fault detection and control. Optimized battery charging and photovoltaic fault detection and control are also successfully implemented. The system is able to optimize the operation and performance of biogas and photovoltaic energy generation.

  11. The Medical Microrobot Control System Design via Fuzzy Logic Application

    Directory of Open Access Journals (Sweden)

    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

  12. High-Precision Control of a Piezo-Driven Nanopositioner Using Fuzzy Logic Controllers

    Directory of Open Access Journals (Sweden)

    Mohammed Altaher

    2018-01-01

    Full Text Available This paper presents single- and dual-loop fuzzy control schemes to precisely control the piezo-driven nanopositioner in the x- and y-axis directions. Various issues are associated with this control problem, such as low stability margin due to the sharp resonant peak, nonlinear dynamics, parameter uncertainty, etc. As such, damping controllers are often utilised to damp the mechanical resonance of the nanopositioners. The Integral Resonant Controller (IRC is used in this paper as a damping controller to damp the mechanical resonance. A further inherent problem is the hysteresis phenomenon (disturbance, which leads to degrading the positioning performance (accuracy of the piezo-driven stage. The common approach to treat this disturbance is to invoke tracking controllers in a closed-loop feedback scheme in conjunction with the damping controllers. The traditional approach uses the Integral Controller (I or Proportional Integral (PI as a tracking controller, whereas this paper introduces the Proportional and Integral (PI-like Fuzzy Logic Controller (FLC as a tracking controller. The effectiveness of the proposed control schemes over conventional schemes is confirmed through comparative simulation studies, and results are presented. The stability boundaries of the proposed control schemes are determined in the same way as with a conventional controller. Robustness against variations in the resonant frequency of the proposed control schemes is verified.

  13. Investigation of the Flutter Suppression by Fuzzy Logic Control for Hypersonic Wing

    Science.gov (United States)

    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.

  14. Intelligent Mechatronics Systems for Transport Climate Parameters Optimization Using Fuzzy Logic Control

    OpenAIRE

    Beinarts, I; Ļevčenkovs, A; Kuņicina, N

    2007-01-01

    In article interest is concentrated on the climate parameters optimization in passengers’ salon of public electric transportation vehicles. The article presents mathematical problem for using intelligent agents in mechatronics problems for climate parameters optimal control. Idea is to use fuzzy logic and intelligent algorithms to create coordination mechanism for climate parameters control to save electrical energy, and it increases the level of comfort for passengers. A special interest for...

  15. Neural-Network-Based Fuzzy Logic Navigation Control for Intelligent Vehicles

    Directory of Open Access Journals (Sweden)

    Ahcene Farah

    2002-06-01

    Full Text Available This paper proposes a Neural-Network-Based Fuzzy logic system for navigation control of intelligent vehicles. First, the use of Neural Networks and Fuzzy Logic to provide intelligent vehicles  with more autonomy and intelligence is discussed. Second, the system  for the obstacle avoidance behavior is developed. Fuzzy Logic improves Neural Networks (NN obstacle avoidance approach by handling imprecision and rule-based approximate reasoning. This system must make the vehicle able, after supervised learning, to achieve two tasks: 1- to make one’s way towards its target by a NN, and 2- to avoid static or dynamic obstacles by a Fuzzy NN capturing the behavior of a human expert. Afterwards, two association phases between each task and the appropriate actions are carried out by Trial and Error learning and their coordination allows to decide the appropriate action. Finally, the simulation results display the generalization and adaptation abilities of the system by testing it in new unexplored environments.

  16. Electric Drive Control with Rotor Resistance and Rotor Speed Observers Based on Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    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.

  17. Design and FPGA-implementation of an improved adaptive fuzzy logic controller for DC motor speed control

    Directory of Open Access Journals (Sweden)

    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.

  18. Optimization of the Fermentation Process in a Brewery with a Fuzzy Logic Controller

    Directory of Open Access Journals (Sweden)

    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.

  19. Fuzzy logic control for improved pressurizer systems in nuclear power plants

    International Nuclear Information System (INIS)

    Brown, Chris; Gabbar, Hossam A.

    2014-01-01

    Highlights: • Improved performance of the pressurizer system in a CANDU nuclear power plant (NPP). • Inventory control for the pressurizer system in NPP. • Compare fuzzy logic with PID in pressurizer system in NPP. • Develop a fuzzy controller to regulate the pressurizer inventory control. • Compare control performance with current proportional controller used at NPP. - Abstract: The pressurizer system in a CANDU nuclear power plant is responsible for maintaining the pressure of the primary heat transport system to ensure the plant is operated within its safe operating envelope. The inventory control for the pressurizer system use a combination of level sensors, feed valves and bleed valves to ensure that there is adequate room in the pressurizer to accommodate any swell or shrinkage in the PHT system. The Darlington Nuclear Generating Station (DNGS) in Ontario, Canada currently uses a proportional controller for the bleed and feed valves to regulate the pressurizer inventory control which can result in large coolant level overshoot along with excessive settling times. The purpose of this paper is to develop a fuzzy controller to regulate the pressurizer inventory control and compare its performance to the current proportional controller used at DNGS. The simulation of the pressurizer inventory control system shows the fuzzy controller performs better than the proportional controller in terms of settling time and overshoot

  20. Optimized Aircraft Electric Control System Based on Adaptive Tabu Search Algorithm and Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    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.

  1. Development and comparison of integrated dynamics control systems with fuzzy logic control and sliding mode control

    International Nuclear Information System (INIS)

    Song, Jeong Hoon

    2013-01-01

    In this study, four integrated dynamics control (IDC) systems abbreviated as IDCB, IDCS, IDCF, and IDCR are developed, evaluated and compared. IDC systems were integrated with brake and steer control systems to enhance lateral stability and handling performance. To construct the IDC systems, a vehicle model with fourteen degrees of freedom, a fuzzy logic controller, and a sliding mode ABS controller were used. They were tested with various steering inputs when excessive full brake pressure or no brake pressure was applied on dry asphalt, wet asphalt, a snow-covered paved road, and a split-µ road. The results showed that an IDC-equipped vehicle improved lateral stability and controllability in every driving condition compared to an ABS-equipped vehicle. Under all road conditions, IDC controllers enabled the yaw rate to follow the reference yaw rate almost perfectly and reduced the body slip angle. On a split-µ road, IDCB, IDCS, IDCF, and IDCR vehicles drove straight ahead with only very small deviations.

  2. Increase efficiency CNC lathe with the help of fuzzy logic controller (FLC

    Directory of Open Access Journals (Sweden)

    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.

  3. A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.

    Science.gov (United States)

    Hajri, S; Liouane, N; Hammadi, S; Borne, P

    2000-01-01

    Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.

  4. 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....

  5. Application of a PID controller based on fuzzy logic to reduce variations in the control parameters in PWR reactors

    International Nuclear Information System (INIS)

    Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira; Brito, Thiago Souza Pereira de; Afonso, Antonio Claudio Marques; Cruz Filho, Antonio Jose da; Marques, Jose Antonio; Teixeira, Marcello Goulart

    2013-01-01

    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)

  6. FPGA based Fuzzy Logic Controller for plasma position control in ADITYA Tokamak

    International Nuclear Information System (INIS)

    Suratia, Pooja; Patel, Jigneshkumar; Rajpal, Rachana; Kotia, Sorum; Govindarajan, J.

    2012-01-01

    Highlights: ► Evaluation and comparison of the working performance of FLC is done with that of PID Controller. ► FLC is designed using MATLAB Fuzzy Logic Toolbox, and validated on ADITYA RZIP model. ► FLC was implemented on a FPGA. The close-loop testing is done by interfacing FPGA to MATLAB/Simulink. ► 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).

  7. Multi-region fuzzy logic controller with local PID controllers for U-tube steam generator in nuclear power plant

    Directory of Open Access Journals (Sweden)

    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.

  8. A comparison of fuzzy logic-PID control strategies for PWR pressurizer control

    International Nuclear Information System (INIS)

    Kavaklioglu, K.; Ikonomopoulos, A.

    1993-01-01

    This paper describes the results obtained from a comparison performed between classical proportional-integral-derivative (PID) and fuzzy logic (FL) controlling the pressure in a pressurized water reactor (PWR). The two methodologies have been tested under various transient scenarios, and their performances are evaluated with respect to robustness and on-time response to external stimuli. One of the main concerns in the safe operation of PWR is the pressure control in the primary side of the system. In order to maintain the pressure in a PWR at the desired level, the pressurizer component equipped with sprayers, heaters, and safety relief valves is used. The control strategy in a Westinghouse PWR is implemented with a PID controller that initiates either the electric heaters or the sprayers, depending on the direction of the coolant pressure deviation from the setpoint

  9. 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.

  10. 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

    determination, self-tuning FLC for speed control, and a current controller. The turn-on and turn-off angle determination, as its name implies, controls the turn-on and turn-off angles of power switches to improve the efficiency and torque regulation of the SRG. The self-tuning FLC is the speed controller which......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...

  11. Comparative Analysis between Conventional PI and Fuzzy LogicPI Controllers for Indoor Benzene Concentrations

    Directory of Open Access Journals (Sweden)

    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.

  12. Fuzzy logic control of steam generator water level in pressurized water reactors

    International Nuclear Information System (INIS)

    Kuan, C.C.; Lin, C.; Hsu, C.C.

    1992-01-01

    In this paper a fuzzy logic controller is applied to control the steam generator water level in a pressurized water reactor. The method does not require a detailed mathematical mode of the object to be controlled. The design is based on a set of linguistic rules that were adopted from the human operator's experience. After off-line fuzzy computation, the controller is a lookup table, and thus, real-time control is achieved. Shrink-and-swell phenomena are considered in the linguistic rules, and the simulation results show that their effect is dramatically reduced. The performance of the control system can also be improved by changing the input and output scaling factors, which is convenient for on-line tuning

  13. Robust Longitudinal Aircraft- Control Based on an Adaptive Fuzzy-Logic Algorithm

    Directory of Open Access Journals (Sweden)

    Abdel- Latif Elshafei

    2002-06-01

    Full Text Available To study the aircraft response to a fast pull-up manoeuvre, a short period approximation of the longitudinal model is considered. The model is highly nonlinear and includes parametric uncertainties. To cope with a wide range of command signals, a robust adaptive fuzzy logic controller is proposed. The proposed controller adopts a dynamic inversion approach. Since feedback linearization is practically imperfect, robustifying and adaptive components are included in the control law to compensate for modeling errors and achieve acceptable tracking errors. Two fuzzy systems are implemented. The first system models the nominal values of the system’s nonlinearity. The second system is an adaptive one that compensates for modeling errors. The derivation of the control law based on a dynamic game approach is given in detail. Stability of the closed-loop control system is also verified. Simulation results based on an F16-model illustrate a successful tracking performance of the proposed controller.

  14. Hardware simulation of automatic braking system based on fuzzy logic control

    Directory of Open Access Journals (Sweden)

    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.

  15. Fuzzy logic control for selective hydrogenation of acetylene in ethylene rich streams using visual basic

    International Nuclear Information System (INIS)

    Malik, S.R.; Suleman, H.; Khan, J.R.

    2010-01-01

    Presence of acetylene is technically disadvantageous in the ethylene rich gas streams from steam crackers. Acetylene tends to polymerize and inactivates the transition metal catalysts, forming highly explosive compounds. The acetylene content has to be selectively reduced to less than one part per million for such streams. The acetylene hydrogenation unit requires stringent control parameters and needs specialized process control techniques for its operation. This study is concerned with application of Fuzzy Logic Control to manipulate and control the process plant with higher precision and greater simplicity. The control program has been written in visual Basic and entails all major scenarios of work modes for successful hydrogenation of Acetylene. (author)

  16. Design of stability-guaranteed fuzzy logic controller for nuclear steam generators

    International Nuclear Information System (INIS)

    Cho, B.H.; No, H.C.

    1996-01-01

    A fuzzy logic controller (FLC) and a fuzzy logic filter (FLF), which have a special type of fuzzifier, inference engine, and defuzzifier, are applied to the water level control of a nuclear steam generator (S/G). It is shown that arbitrary two-input, single-output linear controllers can be adequately expressed by this FLC. A procedure to construct stability-guaranteed FLC rules is proposed. It contains the following steps: (1) the stable sector of linear feedback gains is obtained from the suboptimal concept based on LQR theory and the Lyapunov's stability criteria; (2) the stable sector of linear gains is mapped into two linear rule tables that are used as limits for the FLC rules; and (3) the construction of an FLC rule table is done by choosing certain rules that lie between these limits. This type of FLC guarantees asymptotic stability of the control system. The FLF generates a feedforward signal of S/G feedwater from the steam flow measurement using a fuzzy concept. Through computer simulation, it is found that the FLC with the FLF works better than a well-tuned PID controller with variable gains to reduce swell/shrink phenomena, especially for the water level deviation and abrupt steam flow disturbances that are typical in the existing power plants

  17. Perancangan Coupled Fuzzy Logic Controller pada Prototipe Mesin Computer Numerical Control (CNC

    Directory of Open Access Journals (Sweden)

    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

  18. A New Control Strategy Based Multi Converter UPQC Using Fuzzy Logic Controller to Improve the Power Quality Issues

    Directory of Open Access Journals (Sweden)

    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.

  19. Automatic control with fuzzy logic of home-made beer production in maceration and cooking stages

    Directory of Open Access Journals (Sweden)

    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.

  20. A novel GUI modeled fuzzy logic controller for a solar powered energy utilization scheme

    International Nuclear Information System (INIS)

    Altas, I. H.; Sharaf, A. M.

    2007-01-01

    Photovoltaic PVA-solar powered electrical systems comprise different components and subsystems to be controlled separately. Since the generated solar power is dependant on uncontrollable environmental conditions, it requires extra caution to design controllers that handle unpredictable events and maintain efficient load matching power. In this study, a photovoltaic (PV) solar array model is developed for Matlab/Simulink GUI environment and controlled using a fuzzy logic controller (FLC), which is also developed for GUI environment. The FLC is also used to control the DC load bus voltage at constant value as well as controlling the speed of a PMDC motor as one of the loads being fed. The FLC controller designed using the Matlab/Simuling GUI environment has flexible design criteria's so that it can easily be modified and extended for controlling different systems. The proposed FLC is used in three different parts of the PVA stand alone utilization scheme here. One of these parts is the speed control of the PMDC load, one of the other parts is controlling the DC load bus voltage, and the third part is the maximum power point (MPPT) tracking control, which is used to operate the PVA at its available maximum power as the solar insolation and ambient temperature change. This paper presents a study of a standalone Photovoltaic energy utilization system feeding a DC and AC hybrid electric load and is fully controlled by a novel and simple on-line fuzzy logic based dynamic search, detection and tracking controller that ensures maximum power point operation under excursions in Solar Insolation, Ambient temperature and electric load variations. The maximum power point MPP-Search and Detection algorithm is fully dynamic in nature and operates without any required direct measurement or forecasted PV array information about the irradiation and temperature. An added Search sensitivity measure is defined and also used in the MPP search algorithm to sense and dynamic response for

  1. Expert systems with fuzzy logic for intelligent diagnosis and control of nuclear power plants

    International Nuclear Information System (INIS)

    Abdelhai, M.I.; Upadhyaya, B.R.

    1990-01-01

    A model-based production-rule analysis system was developed for the tracking and diagnosis of the condition of a reactor coolant system (RCS) using a fuzzy logic algorithm. Since nuclear power plants are large and complex systems, it is natural that vagueness, uncertainty, and imprecision are introduced to such systems. Even in fully automated power plants, the critical diagnostic and control changes must be made by operators who usually express their diagnostic and control strategies linguistically as sets of heuristic decision rules. Therefore, additional imprecisions are introduced into the systems because of the imprecise nature of such qualitative strategies when they are converted into quantitative rules. Such problems, in which the source of imprecision is the absence of sharply defined criteria of class membership, could be dealt with using fuzzy set theory. Hence, a fuzzy logic algorithm could be initiated to implement a known heuristic whenever the given information is vague and qualitative, and it will allow operators to introduce certain linguistic assertions and commands to diagnose and control the system

  2. MPPT Based on Fuzzy Logic Controller (FLC) for Photovoltaic (PV) System in Solar Car

    OpenAIRE

    Aji, Seno; Ajiatmo, Dwi; Robandi, Imam; Suryoatmojo, Heri

    2013-01-01

    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 cy...

  3. Network Based Building Lighting Design and Fuzzy Logic via Remote Control

    Directory of Open Access Journals (Sweden)

    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.

  4. Fuzzy Logic based Coordinated Control of Battery Energy Storage System and Dispatchable Distributed Generation for Microgrid

    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...... (BESS) and dispatchableDG units is proposed in this paper for the microgridmanagement system (MMS). In the proposed coordinatedcontrol strategy, the BESS is used to mitigate the activepower exchange at the point of common coupling of themicrogrid for the grid-connected operation, and is used forthe...... frequency control for the island operation. Theeffectiveness of the proposed control strategy was verifiedby case studies using DIgSILENT/PowerFactroy....

  5. Fuzzy Logic Based Controller for a Grid-Connected Solid Oxide Fuel Cell Power Plant.

    Science.gov (United States)

    Chatterjee, Kalyan; Shankar, Ravi; Kumar, Amit

    2014-10-01

    This paper describes a mathematical model of a solid oxide fuel cell (SOFC) power plant integrated in a multimachine power system. The utilization factor of a fuel stack maintains steady state by tuning the fuel valve in the fuel processor at a rate proportional to a current drawn from the fuel stack. A suitable fuzzy logic control is used for the overall system, its objective being controlling the current drawn by the power conditioning unit and meet a desirable output power demand. The proposed control scheme is verified through computer simulations.

  6. Intelligent control aspects of fuzzy logic and neural nets

    CERN Document Server

    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

  7. Fuzzy logic control of air-conditioning system in residential buildings

    Directory of Open Access Journals (Sweden)

    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.

  8. 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.

  9. Implementation of fuzzy logic for mitigating conflicts of frequency containment control

    DEFF Research Database (Denmark)

    Rikos, Evangelos; Syed, Mazheruddin; Caerts, Chris

    2017-01-01

    Ever increasing shares of intermittent renewable energy sources (RES) in present and future power systems pose new challenges with regard to operation, particularly balance, frequency and voltage stability. Towards effective solutions, the ELECTRA IRP project has developed a novel structure...... imposed by different system conditions. To this end, a design method based on fuzzy logic for avoiding conflicts caused from these conditions or multiple control loops implemented on the same resource is proposed. Simulation results for various selected scenarios and controllers show the effectiveness...

  10. Chaotic queue-based genetic algorithm for design of a self-tuning fuzzy logic controller

    Science.gov (United States)

    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.

  11. Balancing Inverted Pendulum by Angle Sensing Using Fuzzy Logic Supervised PID Controller Optimized by Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Ashutosh K. AGARWAL

    2011-10-01

    Full Text Available Genetic algorithms are robust search techniques based on the principles of evolution. A genetic algorithm maintains a population of encoded solutions and guides the population towards the optimum solution. This important property of genetic algorithm is used in this paper to stabilize the Inverted pendulum system. This paper highlights the application and stability of inverted pendulum using PID controller with fuzzy logic genetic algorithm supervisor . There are a large number of well established search techniques in use within the information technology industry. We propose a method to control inverted pendulum steady state error and overshoot using genetic algorithm technique.

  12. A proposal for off-grid photovoltaic systems with non-controllable loads using fuzzy logic

    International Nuclear Information System (INIS)

    Yahyaoui, Imene; Sallem, Souhir; Kamoun, M.B.A.; Tadeo, Fernando

    2014-01-01

    Highlights: • An energy management system is proposed for off-grid PV systems, based on fuzzy logic. • The proposal guarantees the energy balance and battery protection. • The approach is demonstrated using data measured at the target location. - Abstract: A fuzzy-logic based methodology is proposed and evaluated for energy management in off-grid installations with photovoltaic panels as the source of energy and a limited storage capacity in batteries. The decision on the connection or disconnection of components is based on fuzzy rules on the basis of the Photovoltaic Panel Generation measurement, the measured power required by the load, and the estimation of the stored energy in the batteries (this last is obtained from the estimation of the Depth-of-Discharge). The algorithm aims to ensure the system’s autonomy by controlling the switches linking the system components with respect to a multi-objective management criterion developed from the requirements (supply of the load, protection of the battery, etc.). Detailed tests of the proposed system are carried out using data (irradiation, temperature, power consumption, etc.) measured in a household at the target area at several days of the year. The results demonstrate that the proposed approach achieves the objectives of system autonomy, battery protection and power supply stability. Compared with a basic algorithm, the proposed algorithm is not sensitive to sudden changes in atmospheric parameters and avoids overcharging the battery

  13. FPA Tuned Fuzzy Logic Controlled Synchronous Buck Converter for a Wave/SC Energy System

    Directory of Open Access Journals (Sweden)

    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.

  14. Particle swarm optimization based fuzzy logic controller for autonomous green power energy system with hydrogen storage

    International Nuclear Information System (INIS)

    Safari, S.; Ardehali, M.M.; Sirizi, M.J.

    2013-01-01

    Highlights: ► Optimized fuzzy logic controller for a hybrid green power system is developed. ► PSO algorithm is used to optimize membership functions of controller. ► Optimized fuzzy logic controller results in lower O and M costs and LPSP. ► Optimization results in less variation of battery state of charge. - Abstract: The objective of this study is to develop an optimized fuzzy logic controller (FLC) for operating an autonomous hybrid green power system (HGPS) based on the particle swarm optimization (PSO) algorithm. An electrolyzer produces hydrogen from surplus energy generated by the wind turbine and photovoltaic array of HGPS for later use by a fuel cell. The PSO algorithm is used to optimize membership functions of the FLC. The FLC inputs are (a) net power flow and (b) batteries state of charge (SOC) and FLC output determines the time for hydrogen production or consumption. Actual data for weekly residential load, wind speed, ambient temperature, and solar irradiation are used for performance simulation and analysis of the HGPS examined. The weekly operation and maintenance (O and M) costs and the loss of power supply probability (LPSP) are considered in the optimization procedure. It is determined that FLC optimization results in (a) reduced fluctuations in batteries SOC which translates into longer life for batteries and the average SOC is increased by 6.18% and (b) less working hours for fuel cell, when the load is met by wind and PV. It is found that the optimized FLC results in lower O and M costs and LPSP by 57% and 33%, respectively, as compared to its un-optimized counterpart. In addition, a reduction of 18% in investment cost is achievable by optimal sizing and reducing the capacity of HGPS equipment.

  15. Application of fuzzy logic in nuclear reactor control Part I: An assessment of state-of-the-art

    International Nuclear Information System (INIS)

    Herger, A.S.; Jamshidl, M.; Alang-Rashid, N.K.

    1995-01-01

    This article discusses the application of fuzzy logic to nuclear reactor control. The method has been suggested by many investigators in many control applications. Reviews of the application of fuzzy logic in process control are given by Tong and Sugeno. Because fuzzy logic control (FLC) provides a pathway for transforming human abstractions into the numerical domain, it has the potential to assist nuclear reactor operators in the control room. With this transformation, linguistically expressed control principles can be coded into the fuzzy controller rule base. Having acquired the skill of the operators, the FLC can assist an operator in controlling the complex system. The thrust of FLC is to derive a conceptual model of the control operation, without expressing the process as mathematical equations, to assist the human operator in interpreting incoming plant variables and arriving at a proper control action. To introduce the concept of FLC in nuclear reactor operation, an overview of the mythology and a review of its application in both nuclear and nonnuclear control application domains are presented along with subsequent discussion of fuzzy logic controllers, their structures, and their method of information processing. The article concludes with the application of a tunable FLC to a typical reactor control problem

  16. Application of fuzzy logic in nuclear reactor control: Part 1: An assessment of state-of-the-art

    International Nuclear Information System (INIS)

    Heger, A.S.; Alang-Rashid, N.K.; Jamshidi, M.

    1995-01-01

    This article discusses the application of fuzzy logic of nuclear reactor control. The method has been suggested by many investigators in many control applications. Reviews of the application of fuzzy logic in process control are given by Tong and Sugeno. Because fuzzy logic control (FLC) provides a pathway for transforming human abstractions into the numerical domain, it has the potential to assist nuclear reactor operators in the control room. With this transformation, linguistically expressed control principles can be coded into the fuzzy controller rule base. Having acquired the skill of he operators, the FLC can assist an operator in controlling the complex system. The thrust of FLC is to derive a conceptual model of the control operation, without expressing the process as mathematical equations, to assist the human operator in interpreting incoming plant variables and arriving at a proper control action. To introduce the concept of FLC in nuclear reactor operation, an overview of the mythology and a review of its application in both nuclear and nonnuclear control application domains are presented along with subsequent discussion of fuzzy logic controllers, their structures, and their method of information processing. The article concludes with the application of a tunable FLC to a typical reactor control problem. 49 refs., 9 figs., 3 tabs

  17. Studi Eksperimental Pengontrolan Air Conditioning System Dengan Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    Sudirman -

    2012-11-01

    Full Text Available Electrical energy available in Indonesia at this time is not yet sufficient for all existing activities, this can be proved byfrequent occurrence of blackouts in several areas in Indonesia. It is necessary for a saving in electrical energy consumptionin all sectors, it is one of the refrigeration system. Research was conducted by testing AC (3 HP / 3 phase using 2 differentcontrol systems, namely conventional control and FLC. Testing is done by placing the indoor units in cold storage room.Each test performed with varying load in the test room, ie no light burden, lamp 1000 Watt, and lamp 2000 Watt. Testingusing a conventional control system set point temperature 26 ° C and 3 variations of the differential is 1 , 2 and 3 , the FLCusing the temperature setting point 26 ° C. From this research we can conclude that the application of FLC system produceselectric energy consumption of the lowest compared to conventional control in this case is the differential 1. FLC applicationof electrical energy consumption at load 1000 Watt lower 11% and the load 2000 Watt 4% lower compared withconventional control in diffrensial 1.

  18. Priority-based queuing and transmission rate management using a fuzzy logic controller in WSNs

    Directory of Open Access Journals (Sweden)

    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.

  19. Optimal fuzzy logic-based PID controller for load-frequency control including superconducting magnetic energy storage units

    International Nuclear Information System (INIS)

    Pothiya, Saravuth; Ngamroo, Issarachai

    2008-01-01

    This paper proposes a new optimal fuzzy logic-based-proportional-integral-derivative (FLPID) controller for load frequency control (LFC) including superconducting magnetic energy storage (SMES) units. Conventionally, the membership functions and control rules of fuzzy logic control are obtained by trial and error method or experiences of designers. To overcome this problem, the multiple tabu search (MTS) algorithm is applied to simultaneously tune PID gains, membership functions and control rules of FLPID controller to minimize frequency deviations of the system against load disturbances. The MTS algorithm introduces additional techniques for improvement of search process such as initialization, adaptive search, multiple searches, crossover and restarting process. Simulation results explicitly show that the performance of the optimum FLPID controller is superior to the conventional PID controller and the non-optimum FLPID controller in terms of the overshoot, settling time and robustness against variations of system parameters

  20. Rule-bases construction through self-learning for a table-based Sugeno-Takagi fuzzy logic control system

    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.

  1. Expert system for fault diagnosis in process control valves using fuzzy-logic

    International Nuclear Information System (INIS)

    Carneiro, Alvaro L.G.; Porto Junior, Almir C.S.

    2013-01-01

    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 rule base

  2. 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

  3. Adaptive Interval Type-2 Fuzzy Logic Control for PMSM Drives with a Modified Reference Frame

    KAUST Repository

    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.

  4. Enhancement of micro-grid performance during islanding mode using storage batteries and new fuzzy logic pitch angle controller

    International Nuclear Information System (INIS)

    Kamel, Rashad M.; Chaouachi, A.; Nagasaka, Ken

    2011-01-01

    Research highlights: → Novel fuzzy pitch angle controller is proposed for smoothing wind fluctuation. → Storage batteries are used for performance improve of MG in islanding mode. → Those new techniques are compared with conventional PI pitch angle controller. -- Abstract: Power system deregulation, shortage of transmission capacities and needing to reduce green house gas have led to increase interesting in distributed generations (DGs) especially renewable sources. This study developed a complete model able to analysis and simulates in details the transient dynamic performance of the Micro-Grid (MG) during and subsequent islanding process. Wind speed fluctuations cause high fluctuations in output power of wind turbine which lead to fluctuations of frequency and voltages of the MG during the islanding mode. In this paper a new fuzzy logic pitch angle controller is proposed to smooth the output power of wind turbine to reduce MG frequency and voltage fluctuations during the islanding mode. The proposed fuzzy logic pitch controller is compared with the conventional PI pitch angle controller which usually used for wind turbine power control. Results proved the effectiveness of the proposed fuzzy controller in improvement of the MG performance. Also, this paper proposed using storage batteries technique to reduce the frequency deviation and fluctuations originated from wind power solar power fluctuations. Results indicate that the storage batteries technique is superior than fuzzy logic pitch controller in reducing frequency deviation, but with more expensive than the fuzzy controller. All models and controllers are built using Matlab (registered) Simulink (registered) environment.

  5. Power-Constrained Fuzzy Logic Control of Video Streaming over a Wireless Interconnect

    Science.gov (United States)

    Razavi, Rouzbeh; Fleury, Martin; Ghanbari, Mohammed

    2008-12-01

    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.

  6. Fuzzy Logic Controller Stability Analysis Using a Satisfiability Modulo Theories Approach

    Science.gov (United States)

    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.

  7. Implementasi Fuzzy Logic Controller untuk Mengatur Ph Nutrisi pada Sistem Hidroponik Nutrient Film Technique (NFT

    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.

  8. Simulation comparison of proportional integral derivative and fuzzy logic in controlling AC-DC buck boost converter

    Science.gov (United States)

    Faisal, A.; Hasan, S.; Suherman

    2018-03-01

    AC-DC converter is widely used in the commercial industry even for daily purposes. The AC-DC converter is used to convert AC voltage into DC. In order to obtain the desired output voltage, the converter usually has a controllable regulator. This paper discusses buck boost regulator with a power MOSFET as switching component which is adjusted based on the duty cycle of pulse width modulation (PWM). The main problems of the buck boost converter at start up are the high overshoot, the long peak time and rise time. This paper compares the effectiveness of two control techniques: proportional integral derivative (PID) and fuzzy logic control in controlling the buck boost converter through simulations. The results show that the PID is more sensitive to voltage change than fuzzy logic. However, PID generates higher overshoot, long peak time and rise time. On the other hand, fuzzy logic generates no overshoot and shorter rise time.

  9. Optimizing biological waste water cleaning by means of modern control systems (fuzzy logic); Optimierung der biologischen Abwasserreinigung durch moderne Regelsysteme (Fuzzy-Logik)

    Energy Technology Data Exchange (ETDEWEB)

    Lohse, M.; Boening, T.; Hegemann, G. [Fachhochschule Muenster (Germany). Inst. fuer Abfall- und Abwasserwirtschaft e.V.

    1999-07-01

    Within the framework of a project sponsored by EUREGIO, test series with the biological activation stages of a German and a Dutch sewage treatment plant each are carried out using different process concepts for the control of oxygen supply by fuzzy logic. As the currently available results demonstrate, the developed fuzzy-logic fields of characteristic curves permit establishing a stable and, thus, little energy-consuming process with optimum oxygen supply in comparison with conventional control. (orig.) [German] Im Rahmen eines von der EUREGIO gefoerderten Forschungsprojektes werden Versuchsreihen im Bereich der biologischen Belebungsstufen einer deutschen und einer niederlaendischen Abwasserreinigungsanlage (ARA) mit unterschiedlichen Verfahrenskonzepten hinsichtlich der Regelung der Sauerstoffzufuhr mit Hilfe der Fuzzy-Logik Technik durchgefuehrt. Die bisherigen Versuchsergebnisse zeigen, dass - im Vergleich zur konventionellen Regelung - durch die entwickelten Fuzzy-Logik Kennfelder ein stabiler und damit energiearmer Prozess mit optimaler Sauerstoffzufuhr erzeugt wird. (orig.)

  10. Gas Turbine Engine Control Design Using Fuzzy Logic and Neural Networks

    Directory of Open Access Journals (Sweden)

    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.

  11. A study of photovoltaic/thermal (PVT)-ground source heat pump hybrid system by using fuzzy logic control

    International Nuclear Information System (INIS)

    Andrew Putrayudha, S.; Kang, Eun Chul; Evgueniy, E.; Libing, Y.; Lee, Euy Joon

    2015-01-01

    Renewable Heat Obligation (RHO) implementation in every country becomes an important issue to utilize more renewable energy sources while reducing the usage of fossil fuel. In 2014, South Korea has a target that every commercial building construction that exceeding 10,000 m 2 has to have on-site new & renewable power generation such as combined heat in the beginning of 2016. Photovoltaic/Thermal (PVT) and Geothermal hybrid systems have been introduced in previous research (E.J. Lee et al.) and it showed a great result from its efficiency and also its power consumption for single and multi-building cases. In this paper, Fuzzy Logic control has been applied to optimize the energy consumption of the system. By comparing it with conventional on–off control, fuzzy logic control system shows a better result in reducing primary energy consumption for both heating and cooling systems annually. Two cases were introduced in this paper, GSHP system and PVT–GSHP system with both on–off and fuzzy logic applied respectively. As a result, it shows that fuzzy logic control consumed 13.3% less energy compared with on–off controller for GSHP system annually and 18.3% less energy compared to on–off controller for PVT–GSHP system annually. - Highlights: • Two renewable systems were designed to produce heating, cooling and electricity. • System optimization by applying Fuzzy Logic in terms of energy saving. • Conventional on–off control system vs advance fuzzy logic control system. • Assumption used based on previous research experience, guidelines.

  12. Fuzzy Control Tutorial

    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....

  13. Fuzzy logic control of stand-alone photovoltaic system with battery storage

    Science.gov (United States)

    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.

  14. Structural Completeness in Fuzzy Logics

    Czech Academy of Sciences Publication Activity Database

    Cintula, Petr; Metcalfe, G.

    2009-01-01

    Roč. 50, č. 2 (2009), s. 153-183 ISSN 0029-4527 R&D Projects: GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504 Keywords : structral logics * fuzzy logics * structural completeness * admissible rules * primitive variety * residuated lattices Subject RIV: BA - General Mathematics

  15. Integrated development environment for fuzzy logic applications

    Science.gov (United States)

    Pagni, Andrea; Poluzzi, Rinaldo; Rizzotto, GianGuido; Lo Presti, Matteo

    1993-12-01

    During the last five years, Fuzzy Logic has gained enormous popularity, both in the academic and industrial worlds, breaking up the traditional resistance against changes thanks to its innovative approach to problems formalization. The success of this new methodology is pushing the creation of a brand new class of devices, called Fuzzy Machines, to overcome the limitations of traditional computing systems when acting as Fuzzy Systems and adequate Software Tools to efficiently develop new applications. This paper aims to present a complete development environment for the definition of fuzzy logic based applications. The environment is also coupled with a sophisticated software tool for semiautomatic synthesis and optimization of the rules with stability verifications. Later it is presented the architecture of WARP, a dedicate VLSI programmable chip allowing to compute in real time a fuzzy control process. The article is completed with two application examples, which have been carried out exploiting the aforementioned tools and devices.

  16. Fuzzy Logic Based Set-Point Weighting Controller Tuning for an Internal Model Control Based PID Controller

    Directory of Open Access Journals (Sweden)

    Maruthai Suresh

    2009-10-01

    Full Text Available Controller tuning is the process of adjusting the parameters of the selected controller to achieve optimum response for the controlled process. For many of the control problems, a satisfactory performance is obtained by using PID controllers. One of the main problems with mathematical models of physical systems is that the parameters used in the models cannot be determined with absolute accuracy. The values of the parameters may change with time or various effects. In these cases, conventional controller tuning methods suffer when trying a lot to produce optimum response. In order to overcome these difficulties a fuzzy logic based Set- Point weighting controller tuning method is proposed. The effectiveness of the proposed scheme is analyzed through computer simulation using SIMULINK software and the results are presented. The fuzzy logic based simulation results are compared with Cohen-Coon (CC, Ziegler- Nichols (ZN, Ziegler – Nichols with Set- Point weighting (ZN-SPW, Internal Model Control (IMC and Internal model based PID controller responses (IMC-PID. The effects of process modeling errors and the importance of controller tuning have been brought out using the proposed control scheme.

  17. Fuzzy Logic Based Control of the Lateral Stability of Tractor Semitrailer Vehicle

    Directory of Open Access Journals (Sweden)

    Xiujian Yang

    2015-01-01

    Full Text Available A novel control scheme is proposed to improve the yaw stability of a tractor semitrailer vehicle in critical situations. The control scheme is a two-layer structure consisting of an upper yaw moment controller and a lower brake force distributor. The tractor and the trailer are, respectively, stabilized by two independent fuzzy logic based yaw moment controllers. The controllers for the tractor and the trailer are, respectively, designed to track the reference yaw rate of the tractor and the hitch angle between the tractor and the trailer while considering the variation of the hitch angular rate at the same time. The corrective yaw moments determined by the corresponding upper fuzzy yaw moment controllers are realized by active wheel braking. The performance of the proposed control scheme is evaluated by simulations on a nonlinear vehicle model. The results demonstrate that the proposed control scheme is robust and effective in stabilizing the severe instabilities such as jackknife and trailer oscillation in the chosen simulation scenarios. It is believed that this control scheme is robust to the variation of road adhesion conditions.

  18. FUZZY LOGIC BASED ADAPTATION MECHANISM FOR ADAPTIVE LUENBERGER OBSERVER SENSORLESS DIRECT TORQUE CONTROL OF INDUCTION MOTOR

    Directory of Open Access Journals (Sweden)

    A. BENNASSAR

    2016-01-01

    Full Text Available Many industrial applications require high performance speed sensorless operation and demand new control methods in order to obtain fast dynamic response and insensitive to external disturbances. The current research aims to present the performance of the sensorless direct torque control (DTC of an induction motor (IM using adaptive Luenberger observer (ALO with fuzzy logic controller (FLC for adaptation mechanism. The rotor speed is regulated by proportional integral (PI anti-windup controller. The proposed strategy is directed to reduce the ripple on the torque and the flux. Numerical simulation results show the good performance and effectiveness of the proposed sensorless control for different references of the speed even both low and high speeds.

  19. 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.

  20. Fuzzy-logic-based power control system for multifield electrostatic precipitators

    Energy Technology Data Exchange (ETDEWEB)

    Grass, N. [Siemens AG, Erlangen (Germany)

    2002-10-01

    The power consumption of large precipitators can be in the range of 1 MW and above. Depending on the dust load properties, the electrical power may be reduced by up to 50% by applying fuzzy logic, without significantly increasing the dust emissions. The new approach uses fuzzy logic for optimization of existing electrostatic precipitators. The software runs on a standard personal computer platform under the, Windows NT operating system. The controllers of the electrostatic precipitator power supplies are linked to the personal computer via an industrial network (e.g., PROFIBUS). The system determines online the differentials of emission versus electrical power of each field. This measurement is difficult because of overlaid events in the other zones, and process changes. The long response time of the resultant dust emission due to electrical power changes in the precipitator is an additional complication. Rules were defined for a coarse, but fast-response power adaptation of all zones. Fine tuning the running system after the coarse optimization increased the accuracy and reliability. When installed on a 4 x 5 zone precipitator in a power station, significant results were obtained. The power savings over three months of operation were in the range of 40%-60% depending on the load and fuel characteristics. Data were recorded over the test period of three months. The results are presented.

  1. FUZZY LOGIC IN LEGAL EDUCATION

    Directory of Open Access Journals (Sweden)

    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

  2. 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.

  3. 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.

  4. Fuzzy logic controller architecture for water level control in nuclear power plant steam generator using ANFIS training method

    International Nuclear Information System (INIS)

    Vosoughi, Naser; Ekrami, AmirHasan; Naseri, Zahra

    2003-01-01

    Since suitable control of water level can greatly enhance the operation of a power station, a fuzzy logic controller is applied to control the steam generator water level in a pressurized water reactor. The method does not require a detailed mathematical model of the object to be controlled. It is shown that two inputs, a single output and the least number of rules (9 rules) are considered for a controller, and the ANFIS training method is employed to model functions in a controlled system. By using ANFIS training method, initial membership functions will be trained and appropriate functions are generated to control water level inside the steam generator while using the stated rules. The proposed architecture can construct an input-output mapping based on both human knowledge (in the from of fuzzy if - then rules) and stipulated input-output data. This fuzzy logic controller is applied to the steam generator level control by computer simulations. The simulation results confirm the excellent performance of this control architecture in compare with a well-turned PID controller. (author)

  5. Logical Characterisation of Ontology Construction using Fuzzy Description Logics

    DEFF Research Database (Denmark)

    Badie, Farshad; Götzsche, Hans

    had the extension of ontologies with Fuzzy Logic capabilities which plan to make proper backgrounds for ontology driven reasoning and argumentation on vague and imprecise domains. This presentation conceptualises learning from fuzzy classes using the Inductive Logic Programming framework. Then......, employs Description Logics in characterising and analysing fuzzy statements. And finally, provides a conceptual framework describing fuzzy concept learning in ontologies using the Inductive Logic Programming....

  6. An Improvement of a Fuzzy Logic-Controlled Maximum Power Point Tracking Algorithm for Photovoltic Applications

    Directory of Open Access Journals (Sweden)

    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.

  7. Fuzzy Logic and Arithmetical Hierarchy III

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr

    2001-01-01

    Roč. 68, č. 1 (2001), s. 129-142 ISSN 0039-3215 R&D Projects: GA AV ČR IAA1030004 Institutional research plan: AV0Z1030915 Keywords : fuzzy logic * basic fuzzy logic * Lukasiewicz logic * Godel logic * product logic * arithmetical hierarchy Subject RIV: BA - General Mathematics

  8. Comparison of Sliding Mode Control and Fuzzy Logic control applied to Variable Speed Wind Energy Conversion Systems

    Directory of Open Access Journals (Sweden)

    Souhila Rached Zine

    2015-08-01

    Full Text Available wind energy features prominently as a supplementary energy booster. It does not pollute and is inexhaustible. However, its high cost is a major constraint, especially on the less windy sites. The purpose of wind energy systems is to maximize energy efficiency, and extract maximum power from the wind speed. In This case, the MPPT control becomes important. To realize this control, strategy conventional Proportional and Integral (PI controller is usually used. However, this strategy cannot achieve better performance. This paper proposes other control methods of a turbine which optimizes its production such as fuzzy logic, sliding mode control. These methods improve the quality and energy efficiency. The proposed Sliding Mode Control (SMC strategy and the fuzzy controllers have presented attractive features such as robustness to parametric uncertainties of the turbine, simplicity of its design and good performances. The simulation result under Matlab\\Simulink has validated the performance of the proposed MPPT strategies.

  9. Fuzzy Logic in Medicine and Bioinformatics

    Directory of Open Access Journals (Sweden)

    Angela Torres

    2006-01-01

    Full Text Available The purpose of this paper is to present a general view of the current applications of fuzzy logic in medicine and bioinformatics. We particularly review the medical literature using fuzzy logic. We then recall the geometrical interpretation of fuzzy sets as points in a fuzzy hypercube and present two concrete illustrations in medicine (drug addictions and in bioinformatics (comparison of genomes.

  10. Fuzzy Logic and Education: Teaching the Basics of Fuzzy Logic through an Example (By Way of Cycling)

    Science.gov (United States)

    Sobrino, Alejandro

    2013-01-01

    Fuzzy logic dates back to 1965 and it is related not only to current areas of knowledge, such as Control Theory and Computer Science, but also to traditional ones, such as Philosophy and Linguistics. Like any logic, fuzzy logic is concerned with argumentation, but unlike other modalities, which focus on the crisp reasoning of Mathematics, it deals…

  11. Real Time Implementation of Incremental Fuzzy Logic Controller for Gas Pipeline Corrosion Control

    Directory of Open Access Journals (Sweden)

    Gopalakrishnan Jayapalan

    2014-01-01

    Full Text Available A robust virtual instrumentation based fuzzy incremental corrosion controller is presented to protect metallic gas pipelines. Controller output depends on error and change in error of the controlled variable. For corrosion control purpose pipe to soil potential is considered as process variable. The proposed fuzzy incremental controller is designed using a very simple control rule base and the most natural and unbiased membership functions. The proposed scheme is tested for a wide range of pipe to soil potential control. Performance comparison between the conventional proportional integral type and proposed fuzzy incremental controller is made in terms of several performance criteria such as peak overshoot, settling time, and rise time. Result shows that the proposed controller outperforms its conventional counterpart in each case. Designed controller can be taken in automode without waiting for initial polarization to stabilize. Initial startup curve of proportional integral controller and fuzzy incremental controller is reported. This controller can be used to protect any metallic structures such as pipelines, tanks, concrete structures, ship, and offshore structures.

  12. [Research on the Application of Fuzzy Logic to Systems Analysis and Control

    Science.gov (United States)

    1998-01-01

    Research conducted with the support of NASA Grant NCC2-275 has been focused in the main on the development of fuzzy logic and soft computing methodologies and their applications to systems analysis and control. with emphasis 011 problem areas which are of relevance to NASA's missions. One of the principal results of our research has been the development of a new methodology called Computing with Words (CW). Basically, in CW words drawn from a natural language are employed in place of numbers for computing and reasoning. There are two major imperatives for computing with words. First, computing with words is a necessity when the available information is too imprecise to justify the use of numbers, and second, when there is a tolerance for imprecision which can be exploited to achieve tractability, robustness, low solution cost, and better rapport with reality. Exploitation of the tolerance for imprecision is an issue of central importance in CW.

  13. Combining fuzzy mathematics with fuzzy logic to solve business management problems

    Science.gov (United States)

    Vrba, Joseph A.

    1993-12-01

    Fuzzy logic technology has been applied to control problems with great success. Because of this, many observers fell that fuzzy logic is applicable only in the control arena. However, business management problems almost never deal with crisp values. Fuzzy systems technology--a combination of fuzzy logic, fuzzy mathematics and a graphical user interface--is a natural fit for developing software to assist in typical business activities such as planning, modeling and estimating. This presentation discusses how fuzzy logic systems can be extended through the application of fuzzy mathematics and the use of a graphical user interface to make the information contained in fuzzy numbers accessible to business managers. As demonstrated through examples from actual deployed systems, this fuzzy systems technology has been employed successfully to provide solutions to the complex real-world problems found in the business environment.

  14. Design of stability-guaranteed fuzzy logic controller for nuclear steam generators

    International Nuclear Information System (INIS)

    Cho, Byung Hak

    1996-02-01

    A fuzzy logic controller(FLC) and a fuzzy logic filter(FLF), which have a special type of fuzzifier, inference engine, and defuzzifier, are applied to the water level control of a nuclear steam generator (S/G). It is shown that arbitrary two-input, single-output linear state feedback controllers can be adequately expressed by this FLC. A procedure to construct stability-guaranteed FLC rules is proposed. It contains the following steps: (1) The stable sector of linear feedback gains is obtained from the suboptimal concept based on LQR theory and the Lyapunov's stability criteria: (2) The stable sector of linear gains is mapped into two linear rule tables that are used as limits for the FLC rules: (3) The construction of an FLC rule table is done by choosing certain rules that lie between these limits. This type of FLC guarantees asymptotic stability of the control system. The FLF generates a feedforward signal of S/G feedwater from the steam flow measurement using a fuzzy concept. Through computer simulation, it is found that the FLC with the FLF works better than well-tuned PID controller with variable gains to reduce swell/shrink phenomena especially for the water level deviation and abrupt steam flow disturbances that are typical in the existing power plants. A neurofuzzy logic controller (NFLC), that is implemented by using multi-layered neural network to have the same function as the FLC discussed above, is designed. The automatic generation of NFLC rule table is accomplished by using back-error-propagation (BEP) algorithm. There are two separated paths at the error back-propagation in the S/G. One is to consider the level dynamics depending on the tank capacity, and the other is to take into account the reverse dynamics of S/G. The amounts of error back-propagated through these paths show opposite effects to the BEP algorithm each other at the swell/shrink phenomena. Through the computer simulation, it is found that the BEP algorithm adequately generates NFLC

  15. Fuzzy control and identification

    CERN Document Server

    Lilly, John H

    2010-01-01

    This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.

  16. The first order fuzzy predicate logic (I)

    International Nuclear Information System (INIS)

    Sheng, Y.M.

    1986-01-01

    Some analysis tools of fuzzy measures, Sugeno's integrals, etc. are introduced into the semantic of the first order predicate logic to explain the concept of fuzzy quantifiers. The truth value of a fuzzy quantification proposition is represented by Sugeno's integral. With this framework, several important notions of formation rules, fuzzy valutions and fuzzy validity are discussed

  17. Fuzzy Logic Based Controller for Maintaining Human Comfort within Intelligent Building System

    Directory of Open Access Journals (Sweden)

    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

  18. The Design of Artificial Intelligence Robot Based on Fuzzy Logic Controller Algorithm

    Science.gov (United States)

    Zuhrie, M. S.; Munoto; Hariadi, E.; Muslim, S.

    2018-04-01

    Artificial Intelligence Robot is a wheeled robot driven by a DC motor that moves along the wall using an ultrasonic sensor as a detector of obstacles. This study uses ultrasonic sensors HC-SR04 to measure the distance between the robot with the wall based ultrasonic wave. This robot uses Fuzzy Logic Controller to adjust the speed of DC motor. When the ultrasonic sensor detects a certain distance, sensor data is processed on ATmega8 then the data goes to ATmega16. From ATmega16, sensor data is calculated based on Fuzzy rules to drive DC motor speed. The program used to adjust the speed of a DC motor is CVAVR program (Code Vision AVR). The readable distance of ultrasonic sensor is 3 cm to 250 cm with response time 0.5 s. Testing of robots on walls with a setpoint value of 9 cm to 10 cm produce an average error value of -12% on the wall of L, -8% on T walls, -8% on U wall, and -1% in square wall.

  19. Supervisory System and Multivariable Control Applying Weighted Fuzzy-PID Logic in an Alcoholic Fermentation Process

    Directory of Open Access Journals (Sweden)

    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.

  20. Introduction to fuzzy logic using Matlab

    CERN Document Server

    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.

  1. Position controller for the arm of a neutron diffractometer using fuzzy logic

    International Nuclear Information System (INIS)

    Ayala P, G.F.

    1994-01-01

    The neutron diffractometer is an important instrument coupled to one of the radial outlets of the TRIGA-3-Salazar Reactor and is used mainly to analyze textures and crystal lattices. One of its main components is the velocity analysis goniometer which controls in a tangential way the movements of the sensor requiring for this a resolution of a hundredth of degree, but at the same time wide displacements are required. It is necessary to design and construct a system on the basis of a micro controller which control the long movements in a rapid way and with the needed accuracy. In this work, a proposition is presented: to replace the A.C. motor with a D.C. motor with a wide range of velocity and supplied with a card (DAC) to control the velocity by means of digital data. Moreover, a programmed micro controller with an algorithm based on fuzzy logic receiving data in BCD will be use. The use of micro controller will allow to set free the personal computer of the position of the goniometer; nevertheless, the system will report to the P C and its control program about the present position of the goniometer and the time when the desired position is reached. It is also consider that the user will be away from the system (a minimum of 15 meters) in order to avoid the zone with a high intensity of background radiation. (Author)

  2. A novel fuzzy-logic control strategy minimizing N2O emissions.

    Science.gov (United States)

    Boiocchi, Riccardo; Gernaey, Krist V; Sin, Gürkan

    2017-10-15

    A novel control strategy for achieving low N 2 O emissions and low effluent NH 4 + 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 the balance among the microbial groups. More specifically, the ratio will indicate if there is a complete nitrification. In case nitrification is not complete, the controller will adjust the aeration level of the plant in order to inhibit the production of N 2 O from AOB and HB denitrification. The controller 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 N 2 O 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 N 2 O producing process. However, in treatment plants having incomplete NH 2 OH oxidation as the main N 2 O producing pathway, a cascade controller configuration adapting the oxygen supply to respect only the effluent ammonium concentration limits was found to be more effective to ensure low N 2 O emissions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Fuzzy forecasting based on fuzzy-trend logical relationship groups.

    Science.gov (United States)

    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.

  4. Controlling the process of composting farm biomass with the use of fuzzy logic

    Energy Technology Data Exchange (ETDEWEB)

    Neugebauer, M. [Warmia and Mazury Univ., Olsztyn (Poland)

    2010-07-01

    The process of composting organic waste produces organic fertilizer. The main phases of composting include the mesophilic and thermophilic stages followed by cooling down and maturing. The thermophilic phase involves a relatively high temperature, from 45 to 80 degrees C and carbon dioxide emission. Extending this phase of the composting process may reduce the entire process time and the amount of methane produced. The process can be controlled by adjusting the amount of air supplied to the compost heap and controlling the temperature in the bed or oxygen content in the air leaving the heap. Precise control would help optimize the composting process in terms of heat reception, duration of the process and the temperature inside the bed. Excess heat could be put to use elsewhere, such as warming the substrate in a greenhouse. However, overheating the heap reduces the amount of thermophilic microorganisms and may actually reduce the compost temperature, thus slow down or even stop the thermophilic phase of the composting process. A literature survey focused on complex non-linear processes has shown that systems based on fuzzy logic are effective in controlling the process.

  5. A fuzzy logic urea dosage controller design for two-cell selective catalytic reduction systems.

    Science.gov (United States)

    You, Kun; Wei, Lijiang; Jiang, Kai

    2017-12-22

    Diesel engines have dominated in the heavy-duty vehicular and marine power source. However, the induced air pollution is a big problem. As people's awareness of environmental protection increasing, the emission regulations of diesel-engine are becoming more stringent. In order to achieve the emission regulations, the after-treatment system is a necessary choice. Specifically, the selective catalytic reduction (SCR) system has been widely applied to reduce the NO X emissions of diesel engine. Different from single-cell SCR systems, the two-cell systems have various benefits from the modeling and control perspective. In this paper, the urea dosage controller design for two-cell SCR systems was investigated. Firstly, the two-cell SCR modeling was introduced. Based on the developed model, the design procedure for the fuzzy logic urea dosage controller was well addressed. Secondly, simulations and comparisons were employed via an experimental verification of the whole vehicle simulator. And the results showed that the designed controller simultaneously achieved high NO X reduction rate and low tail-pipe ammonia slip. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Innovative teaching tools of automatic control and evaluation of trainees’s mathematical knowledge using fuzzy logic

    Directory of Open Access Journals (Sweden)

    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.

  7. Energy Management of An Extended Hybrid Renewable Energy System For Isolated Sites Using A Fuzzy Logic Controller

    Science.gov (United States)

    Faquir, Sanaa; Yahyaouy, Ali; Tairi, Hamid; Sabor, Jalal

    2018-05-01

    This paper presents the implementation of a fuzzy logic controller to manage the flow of energy in an extended hybrid renewable energy system employed to satisfy the load for a wide isolated site at the city of Essaouira in Morocco. To achieve Efficient energy management, the system is combining two important renewable energies: solar and wind. Lithium Ion batteries were also used as storage devices to store the excess of energy provided by the renewable sources or to supply the system with the required energy when the energy delivered by the input sources is not enough to satisfy the load demand. To manage the energy in the system, a controller based on fuzzy logic was implemented. Real data taken from previous research and meteorological sites was used to test the controller.

  8. Modelling and simulation of a PEM fuel cell power system with a fuzzy logic controller

    International Nuclear Information System (INIS)

    Al-Dabbagh, A.W.; Lu, L.; Mazza, A.

    2009-01-01

    Fuel cell power systems are emerging as promising means of electrical power generation on account of the associated clean electricity generation process, as well as their suitability for use in a wide range of applications. During the design stage, the development of a computer model for simulating the behaviour of a system under development can facilitate the experimentation and testing of that system's performance. Since the electrical power output of a fuel cell stack is seldom at a suitable fixed voltage, conditioning circuits and their associated controllers must be incorporated in the design of the fuel cell power system. This paper presents a MATLAB/Simulink model that simulates the behaviour of a Proton Exchange Membrane (PEM) fuel cell, conditioning circuits and their controllers. The computer modelling of the PEMFC was based on adopted mathematical models that describe the fuel cell's operational voltage, while accounting for the irreversibilities associated with the fuel cell stack. The conditioning circuits that are included in the Simulink model are a DC-DC converter and DC-AC inverter circuits. These circuits are the commonly utilized power electronics circuits for regulating and conditioning the output voltage from a fuel cell stack. The modelling of the circuits is based on relationships that govern the output voltage behaviour with respect to their input voltages, switching duty cycle and efficiency. In addition, this paper describes a Fuzzy Logic Controller (FLC) design that is aimed at regulating the conditioning circuits to provide and maintain suitable electrical power for a wide range of applications. (author)

  9. Analysis of maizena drying system using temperature control based fuzzy logic method

    Science.gov (United States)

    Arief, Ulfah Mediaty; Nugroho, Fajar; Purbawanto, Sugeng; Setyaningsih, Dyah Nurani; Suryono

    2018-03-01

    Corn is one of the rice subtitution food that has good potential. Corn can be processed to be a maizena, and it can be used to make type of food that has been made from maizena, viz. Brownies cake, egg roll, and other cookies. Generally, maizena obtained by drying process carried out 2-3 days under the sun. However, drying process not possible during the rainy season. This drying process can be done using an automatic drying tool. This study was to analyze the design result and manufacture of maizena drying system with temperature control based fuzzylogic method. The result show that temperature of drying system with set point 40°C - 60°C work in suitable condition. The level of water content in 15% (BSN) and temperatureat 50°C included in good drying process. Time required to reach the set point of temperature in 50°C is 7.05 minutes. Drying time for 500 gr samples with temperature 50°C and power capacity 127.6 watt was 1 hour. Based on the result, drying process using temperature control based fuzzy logic method can improve energy efficiency than the conventional method of drying using a direct sunlight source with a temperature that cannot be directly controlled by human being causing the quality of drying result of flour is erratic.

  10. A Two-Stage Fuzzy Logic Control Method of Traffic Signal Based on Traffic Urgency Degree

    OpenAIRE

    Yan Ge

    2014-01-01

    City intersection traffic signal control is an important method to improve the efficiency of road network and alleviate traffic congestion. This paper researches traffic signal fuzzy control method on a single intersection. A two-stage traffic signal control method based on traffic urgency degree is proposed according to two-stage fuzzy inference on single intersection. At the first stage, calculate traffic urgency degree for all red phases using traffic urgency evaluation module and select t...

  11. Efficiency of Photovoltaic Maximum Power Point Tracking Controller Based on a Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Ammar Al-Gizi

    2017-07-01

    Full Text Available This paper examines the efficiency of a fuzzy logic control (FLC based maximum power point tracking (MPPT of a photovoltaic (PV system under variable climate conditions and connected load requirements. The PV system including a PV module BP SX150S, buck-boost DC-DC converter, MPPT, and a resistive load is modeled and simulated using Matlab/Simulink package. In order to compare the performance of FLC-based MPPT controller with the conventional perturb and observe (P&O method at different irradiation (G, temperature (T and connected load (RL variations – rising time (tr, recovering time, total average power and MPPT efficiency topics are calculated. The simulation results show that the FLC-based MPPT method can quickly track the maximum power point (MPP of the PV module at the transient state and effectively eliminates the power oscillation around the MPP of the PV module at steady state, hence more average power can be extracted, in comparison with the conventional P&O method.

  12. An Improved Fuzzy Logic Controller Design for PV Inverters Utilizing Differential Search Optimization

    Directory of Open Access Journals (Sweden)

    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.

  13. Fuzzy logic speed control for the engine of an air-powered vehicle

    Directory of Open Access Journals (Sweden)

    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.

  14. Mathematical Fuzzy Logic - State of Art 2001

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr

    2003-01-01

    Roč. 24, - (2003), s. 71-89 ISSN 0103-9059. [WOLLIC'2001. Brasília, 31.07.2001-03.08.2001] R&D Projects: GA MŠk LN00A056 Keywords : fuzzy logic * many valued logic * basic fuzzy logic BL Subject RIV: BA - General Mathematics http://www.mat.unb.br/~matcont/24_4.pdf

  15. Fuzzy logic and intelligent technologies in nuclear science

    International Nuclear Information System (INIS)

    Ruan, D.

    1998-01-01

    The research project on Fuzzy Logic and Intelligent technologies (FLINS) aims to bridge the gap between novel technologies and the nuclear industry. It aims to initiate research and development programs for solving intricate problems pertaining to the nuclear environment by using modern technologies as additional tool. The major achievements for 1997 include the application of the fuzzy-logic to the BR-1 reactor, the elaboration of a Fuzzy-control model as well as contributions to several workshops and publications

  16. Foundations Of Fuzzy Control

    DEFF Research Database (Denmark)

    Jantzen, Jan

    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...... 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...

  17. Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique

    Directory of Open Access Journals (Sweden)

    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.

  18. Comparative Analysis of Reduced-Rule Compressed Fuzzy Logic Control and Incremental Conductance MPPT Methods

    Science.gov (United States)

    Kandemir, Ekrem; Borekci, Selim; Cetin, Numan S.

    2018-04-01

    Photovoltaic (PV) power generation has been widely used in recent years, with techniques for increasing the power efficiency representing one of the most important issues. The available maximum power of a PV panel is dependent on environmental conditions such as solar irradiance and temperature. To extract the maximum available power from a PV panel, various maximum-power-point tracking (MPPT) methods are used. In this work, two different MPPT methods were implemented for a 150-W PV panel. The first method, known as incremental conductance (Inc. Cond.) MPPT, determines the maximum power by measuring the derivative of the PV voltage and current. The other method is based on reduced-rule compressed fuzzy logic control (RR-FLC), using which it is relatively easier to determine the maximum power because a single input variable is used to reduce computing loads. In this study, a 150-W PV panel system model was realized using these MPPT methods in MATLAB and the results compared. According to the simulation results, the proposed RR-FLC-based MPPT could increase the response rate and tracking accuracy by 4.66% under standard test conditions.

  19. An optimized Fuzzy Logic Controller by Water Cycle Algorithm for power management of Stand-alone Hybrid Green Power generation

    International Nuclear Information System (INIS)

    Sarvi, Mohammad; Avanaki, Isa Nasiri

    2015-01-01

    Highlights: • A new method to improve the performance of renewable power management is proposed. • The proposed method is based on Fuzzy Logic optimized by the Water Cycle Algorithm. • The proposed method characteristics are compared with two other methods. • The comparisons confirm that the proposed method is robust and effectiveness one. - Abstract: This paper aims to improve the power management system of a Stand-alone Hybrid Green Power generation based on the Fuzzy Logic Controller optimized by the Water Cycle Algorithm. The proposed Stand-alone Hybrid Green Power consists of wind energy conversion and photovoltaic systems as primary power sources and a battery, fuel cell, and Electrolyzer as energy storage systems. Hydrogen is produced from surplus power generated by the wind energy conversion and photovoltaic systems of Stand-alone Hybrid Green Power and stored in the hydrogen storage tank for fuel cell later using when the power generated by primary sources is lower than load demand. The proposed optimized Fuzzy Logic Controller based power management system determines the power that is generated by fuel cell or use by Electrolyzer. In a hybrid system, operation and maintenance cost and reliability of the system are the important issues that should be considered in studies. In this regard, Water Cycle Algorithm is used to optimize membership functions in order to simultaneously minimize the Loss of Power Supply Probability and operation and maintenance. The results are compared with the particle swarm optimization and the un-optimized Fuzzy Logic Controller power management system to prove that the proposed method is robust and effective. Reduction in Loss of Power Supply Probability and operation and maintenance, are the most advantages of the proposed method. Moreover the level of the State of Charge of the battery in the proposed method is higher than other mentioned methods which leads to increase battery lifetime.

  20. Fully automatic control of paraplegic FES pedaling using higher-order sliding mode and fuzzy logic control.

    Science.gov (United States)

    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.

  1. Multi input-output fuzzy logic smart controller for a residential hybrid solar-wind-storage energy system

    International Nuclear Information System (INIS)

    Derrouazin, A.; Aillerie, M.; Mekkakia-Maaza, N.; Charles, J.-P.

    2017-01-01

    Highlights: • We present a fuzzy smart controller for hybrid renewable and conventional energy system. • The rules are based on human intelligence and implemented in the smart controller. • Efficient tracking capability of the proposed controller is proofed in this paper by an example. • Excess produced renewable energy is converted to hydrogen for household use . • Considerable electric grid energy saving is highlighted in the proposed controller system. - Abstract: This study concerns the conception and development of an efficient multi input-output fuzzy logic smart controller, to manage the energy flux of a sustainable hybrid power system, based on renewable power sources, integrating solar panels and a wind turbine associated with storage, applied to a typical residential habitat. In the suggested topology, the energy surplus is redirected to an electrolysis system to produce hydrogen suitable for household utilities. To assume a constant access to electricity in case of consumption peak, connection to the grid is also considered as an exceptional rescue resource. The objective of the presented controller is to exploit instantaneously the produced renewable electric energy and insure savings of electric grid energy. The proposed multi input-output fuzzy logic smart controller has been achieved and verified, outcome switches command signals are discussed and the renewable energy system integration ratio is highlighted.

  2. Robust nonlinear PID-like fuzzy logic control of a planar parallel (2PRP-PPR) manipulator.

    Science.gov (United States)

    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. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  3. Some uses and limitations of Fuzzy Logic in artificial intelligence reasoning for reactor control

    International Nuclear Information System (INIS)

    Guth, M.A.S.

    1989-01-01

    This paper describes some potential uses for Fuzzy Logic as well as its limitations based on experience designing a small prototype expert system that can be used in a computer laboratory to study a government research reactor. The expert system designed in this study diagnoses problems in the interface between the heat exchanger and the core. Engineers who had first-hand experience with the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory suggested logical relations incorporated in the knowledge base. The expert system has a production rule backward-chaining-based architecture, and the knowledge base incorporates four kinds of information. First, the structural relationship between causes and consequences are given by nuclear engineering experts. Second, numerical values for the initiating events can be taken from observed performance of the HFIR during normal conditions. Third, the causes of particular events are ordinally ranked by their expected chance of occuring based on a combination of knowledge about the reactor design and actual experiences with the reactor in operation. Fourth, Bellman-Zadeh Fuzzy Logic is introduced to maintain truth values for expert system parameter values that can be true with some degree of certainty. (orig.)

  4. Improvement of Performance Range of Centrifugal Compressors Gas by Surge Line Modification Using Active Controller Based on Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    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.

  5. Molecular processors: from qubits to fuzzy logic.

    Science.gov (United States)

    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.

  6. A fuzzy-logic based diagnosis and control of a reactor performing complete autotrophic nitrogen removal

    DEFF Research Database (Denmark)

    Mauricio Iglesias, Miguel; Vangsgaard, Anna Katrine; Gernaey, Krist

    2013-01-01

    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 d...... autotrophic nitrogen removal process. The whole module is evaluated by dynamic simulation....

  7. Design and Simulation of the Robust ABS and ESP Fuzzy Logic Controller on the Complex Braking Maneuvers

    Directory of Open Access Journals (Sweden)

    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.

  8. Fuzzy colored petri nets and their application to efficient design and V and V of fuzzy logic controllers

    International Nuclear Information System (INIS)

    Son, Han Seong; Seong, Poong Hyun

    1998-01-01

    Generally, FLC design causes the designer to spend too much efforts and time. If a design support is provided to apply various membership functions to and simulate a FLC without coding at the early development stage, the cost problem may be solved to a remarkable degree. In order to offer the systematic approach to support FLC design, Fuzzy Colored Petri Nets (FCPN) is introduced as design support in this work. The feasibility of FCPN is demonstrated through a controller design example

  9. 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.

  10. A model reference and sensitivity model-based self-learning fuzzy logic controller as a solution for control of nonlinear servo systems

    NARCIS (Netherlands)

    Kovacic, Z.; Bogdan, S.; Balenovic, M.

    1999-01-01

    In this paper, the design, simulation and experimental verification of a self-learning fuzzy logic controller (SLFLC) suitable for the control of nonlinear servo systems are described. The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model

  11. Enric Trillas a passion for fuzzy sets : a collection of recent works on fuzzy logic

    CERN Document Server

    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.

  12. 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.

  13. Non-collocated fuzzy logic and input shaping control strategy for elastic joint manipulator: vibration suppression and time response analysis

    Energy Technology Data Exchange (ETDEWEB)

    Rashidifar, Mohammed Amin [Faculty of Mechanical Engineering, Islamic Azad University, SHADEGAN (Iran, Islamic Republic of); Rashidifar, Ali Amin, E-mail: rashidifar_58@yahoo.com [Computer Science, Islamic Azad University, SHADEGAN (Iran, Islamic Republic of)

    2014-07-01

    Conventional model-based control strategies are very complex and difficult to synthesize due to high complexity of the dynamics of robots manipulator considering joint elasticity. This paper presents investigations into the development of hybrid control schemes for trajectory tracking and vibration control of a flexible joint manipulator. To study the effectiveness of the controllers, initially a collocated proportional-derivative (P D)-type Fuzzy Logic Controller (FLC) is developed for tip angular position control of a flexible joint manipulator. This is then extended to incorporate a non-collocated Fuzzy Logic Controller and input shaping scheme for vibration reduction of the flexible joint system. The positive zero-vibration-derivative-derivative (ZVDD) shaper is designed based on the properties of the system. Simulation 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. (Author)

  14. Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS)

    International Nuclear Information System (INIS)

    Da Ruan

    2000-01-01

    FLINS is the acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science. In 1994, SCK-CEN launched a programme on FLINS. The first FLINS project dealt with the specific prototyping of fuzzy logic control (FLC) of the BR-1 research reactor. This project focussed on controlling the power level of the BR1 reactor added value of FLC for both safety and economic aspects for a nuclear reactor control operation. Main achievements in 1999 are reported

  15. Fuzzy Versions of Epistemic and Deontic Logic

    Science.gov (United States)

    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.

  16. French-speaking meeting on fuzzy logic and its applications

    International Nuclear Information System (INIS)

    1997-01-01

    The 1997 edition of LFA'97 meeting for fuzzy logic has been organized by the Pattern Recognition and Computer Vision Laboratory of the National Institute of Applied Sciences. The objective of the meeting was to provide a forum for researchers and users of fuzzy logic and possibility theory to present and discuss theoretical researches and concrete applications. The domains in concern are: the control decision theory, the pattern recognition and image analysis, the artificial intelligence and the information systems. From the 41 papers of this book, two were selected for ETDE and deal with fuzzy regulation systems for heating systems and with fuzzy controllers for gas refining plants, and one was selected for INIS and deal with real-time surveillance and fuzzy logic control systems for nuclear power plants. (J.S.)

  17. Modeling and simulation of fuzzy logic controller for optimization of the greenhouse microclimate management

    Directory of Open Access Journals (Sweden)

    Didi Faouzi

    2017-06-01

    become increasingly sophisticated and of an industrial nature (heating, air conditioning, control, computer, regulation, etc. New climate driving techniques have emerged, including the use of control devices from the classic to the use of artificial intelligence such as neural networks and / or fuzzy logic, etc. As a result, the greenhouse growers prefer these new technologies while optimizing the investment in the field to effectively meet the supply and demand of these fresh products cheaply and widely available throughout the year, The application of artificial intelligence in the industry known for considerable growth, which is not the case in the field of agricultural greenhouses, where enforcement remains timid. It is from this fact, we undertake research work in this area and conduct a simulation based on meteorological data through MATLAB Simulink to finally analyze the thermal behavior - greenhouse microclimate energy.

  18. Design of a fuzzy logic based controller for neutron power regulation; Diseno de un controlador basado en logica difusa para la regulacion de flujo neutronico

    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)

  19. 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.

  20. Model dynamic behaviour analysis with chaotic noise using fuzzy logic based control

    International Nuclear Information System (INIS)

    Silva, Glauco Antonio Santos da

    2002-01-01

    This work presents an application of fuzzy control on dynamical system models. It has been observed that fuzzy controllers maybe used as a good alternative to the classical PI controller, once it incorporates human line behavior. Three implication relationships were used for the fussy controllers, namely, Mamdani Min, Larsen and Takagi-Sugeno. Performance comparisons were made aiming at achieving the best performance for each model used. The PI controller was used as a minimum standard, once it has been present in the industry for many years, giving acceptable performances and some degree of reliability . Two kinds of perturbations were introduced in the models to test the controllers: a ramp and chaotic perturbations. The first one is a monotonic, standard increase of an input parameter. The second one presents non-periodicity and irregularity in such a way to be quite rough to the controllers. The chaotic signal, as an analysis tool to dynamical systems, is an interesting contribution of this work. As a general conclusion it can be said the best performance, in this work, was achieved by the Takagi-Sugeno fuzzy controller. (author)

  1. The use of fuzzy logic in quality control testing of automotive and tractor equipment

    Directory of Open Access Journals (Sweden)

    Korobko А.

    2016-08-01

    Full Text Available The article analyzes the relevance of the research topics, defines goals and objectives, subject and object of research. On the basis of the literature analysis, the following eduction was made: not all the test methods in road and agricultural vehicles (tractors contribute to the effective implementation of the requirements of normative documents including international, inter-laboratory comparative tests. The approach in laboratory testing to the synthesis adaptive system of metrological assurance the use of fuzzy logic is proposed. These labs conduct testing of automotive and tractor equipment. The decision is under risk. The scheme of metrological assurance system covers all parties to ensure the necessary accuracy of measurements and tests; the necessary normative-technical documentation is provided; availability of measuring instruments and test equipment, standards and reference measures; availability of qualified personnel; the assurance that test results are accurate (correct and precision; provides effective decisions based on objective information.

  2. Fuzzy logic for plant-wide control of biological wastewater treatment process including greenhouse gas emissions.

    Science.gov (United States)

    Santín, I; Barbu, M; Pedret, C; Vilanova, R

    2018-06-01

    The application of control strategies is increasingly used in wastewater treatment plants with the aim of improving effluent quality and reducing operating costs. Due to concerns about the progressive growth of greenhouse gas emissions (GHG), these are also currently being evaluated in wastewater treatment plants. The present article proposes a fuzzy controller for plant-wide control of the biological wastewater treatment process. Its design is based on 14 inputs and 6 outputs in order to reduce GHG emissions, nutrient concentration in the effluent and operational costs. The article explains and shows the effect of each one of the inputs and outputs of the fuzzy controller, as well as the relationship between them. Benchmark Simulation Model no 2 Gas is used for testing the proposed control strategy. The results of simulation results show that the fuzzy controller is able to reduce GHG emissions while improving, at the same time, the common criteria of effluent quality and operational costs. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  3. Voltage Stability Control of Electrical Network Using Intelligent Load Shedding Strategy Based on Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Houda Jouini

    2010-01-01

    Full Text Available As a perspective to ensure the power system stability and to avoid the vulnerability leading to the blackouts, several preventive and curative means are adopted. In order to avoid the voltage collapse, load shedding schemes represent a suitable action to maintain the power system service quality and to control its vulnerability. In this paper, we try to propose an intelligent load shedding strategy as a new approach based on fuzzy controllers. This strategy was founded on the calculation of generated power sensitivity degree related to those injected at different network buses. During the fault phase, fuzzy controller algorithms generate monitor vectors ensuring a precalculated load shedding ratio in the purpose to reestablish the power balance and conduct the network to a new steady state.

  4. Analysis of a DVR with Molten Carbonate Fuel Cell and Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    J. Chakravorty

    2018-04-01

    Full Text Available As power demand constantly (and rapidly increases and with the introduction of many sophisticated electronic devices, power quality issues are becoming a major problem for the power sector. In this context, issues of power quality, voltage swells and sags have become rather common. Custom power devices are generally used to solve this problem. A dynamic voltage restorer (DVR is the most efficient and effective modern custom power device used in power distribution networks. In this paper a new DVR model is presented. The proposed DVR has a molten carbonate fuel cell (MCFC as its DC source of supply with an ultra-capacitor along with a fuzzy controller as its controlling unit. The complete model is implemented in MATLAB/SIMULINK and the output of the proposed model is compared with conventional DVR model with a simple DC voltage source and a capacitor with the same fuzzy controller

  5. Fifty years of fuzzy logic and its applications

    CERN Document Server

    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...

  6. Multi-objective design of fuzzy logic controller in supply chain

    Science.gov (United States)

    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.

  7. Fuzzy Logic and Intelligent Technologies in Nuclear Science

    International Nuclear Information System (INIS)

    Da Ruan

    1998-01-01

    FLINS is the acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science. The main task for FLINS is to solve intricate problems pertaining to the nuclear environment by using modern technologies as additional tools and to bridge the gap between novel technologies and the industrial nuclear world. In 1997, major efforts went to the specific prototyping of Fuzzy Logic Control of SCK-CEN's BR1 research Reactor. Progress and achievements are reported

  8. Designing a Fuzzy Logic Controller to Enhance Directional Stability of Vehicles under Difficult Maneuvers

    OpenAIRE

    Mehrdad N. Khajavi; Golamhassan Paygane; Ali Hakima

    2009-01-01

    Vehicle which are turning or maneuvering at high speeds are susceptible to sliding and subsequently deviate from desired path. In this paper the dynamics governing the Yaw/Roll behavior of a vehicle has been simulated. Two different simulations have been used one for the real vehicle, for which a fuzzy controller is designed to increase its directional stability property. The other simulation is for a hypothetical vehicle with much higher tire cornering stiffness which is ca...

  9. Bayesian fuzzy logic-based estimation of electron cyclotron heating (ECH) power deposition in MHD control systems

    Energy Technology Data Exchange (ETDEWEB)

    Davoudi, Mehdi, E-mail: mehdi.davoudi@polimi.it [Department of Electrical and Computer Engineering, Buein Zahra Technical University, Buein Zahra, Qazvin (Iran, Islamic Republic of); Davoudi, Mohsen, E-mail: davoudi@eng.ikiu.ac.ir [Department of Electrical Engineering, Imam Khomeini International University, Qazvin, 34148-96818 (Iran, Islamic Republic of)

    2017-06-15

    Highlights: • A couple of algorithms to diagnose if Electron Cyclotron Heating (ECH) power is deposited properly on the expected deposition minor radius are proposed. • The algorithms are based on Bayesian theory and Fuzzy logic. • The algorithms are tested on the off-line experimental data acquired from Frascati Tokamak Upgrade (FTU), Frascati, Italy. • Uncertainties and evidences derived from the combination of online information formed by the measured diagnostic data and the prior information are also estimated. - Abstract: In the thermonuclear fusion systems, the new plasma control systems use some measured on-line information acquired from different sensors and prior information obtained by predictive plasma models in order to stabilize magnetic hydro dynamics (MHD) activity in a tokamak. Suppression of plasma instabilities is a key issue to improve the confinement time of controlled thermonuclear fusion with tokamaks. This paper proposes a couple of algorithms based on Bayesian theory and Fuzzy logic to diagnose if Electron Cyclotron Heating (ECH) power is deposited properly on the expected deposition minor radius (r{sub DEP}). Both algorithms also estimate uncertainties and evidences derived from the combination of the online information formed by the measured diagnostic data and the prior information. The algorithms have been employed on a set of off-line ECE channels data which have been acquired from the experimental shot number 21364 at Frascati Tokamak Upgrade (FTU), Frascati, Italy.

  10. Development of an object-oriented software based on fuzzy-logic for controlling temperatures in PAC experiments

    International Nuclear Information System (INIS)

    Lapolli, Andre L.; Yamagishi, Sueli; Domienikan, Claudio; Schoueri, Roberto M.; Carbonari, Artur W.; Saxena, Rajendra N.

    2009-01-01

    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, Δtemp) 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)

  11. Development of an object-oriented software based on fuzzy-logic for controlling temperatures in PAC experiments

    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)

  12. Stability Augmentation of a Grid-Connected Wind Farm by Fuzzy-Logic-Controlled DFIG-Based Wind Turbines

    Directory of Open Access Journals (Sweden)

    Md. Rifat Hazari

    2017-12-01

    Full Text Available Wind farm (WF grid codes require wind generators to have low voltage ride through (LVRT capability, which means that normal power production should be resumed quickly once the nominal grid voltage has been recovered. However, WFs with fixed-speed wind turbines with squirrel cage induction generators (FSWT-SCIGs have failed to fulfill the LVRT requirement, which has a significant impact on power system stability. On the other hand, variable-speed wind turbines with doubly fed induction generators (VSWT-DFIGs have sufficient LVRT augmentation capability and can control the active and reactive power delivered to the grid. However, the DFIG is more expensive than the SCIG due to its AC/DC/AC converter. Therefore, the combined use of SCIGs and DFIGs in a WF could be an effective solution. The design of the rotor-side converter (RSC controller is crucial because the RSC controller contributes to the system stability. The cascaded control strategy based on four conventional PI controllers is widely used to control the RSC of the DFIG, which can inject only a small amount of reactive power during fault conditions. Therefore, the conventional strategy can stabilize the lower rating of the SCIG. In the present paper, a new control strategy based on fuzzy logic is proposed in the RSC controller of the DFIG in order to enhance the LVRT capability of the SCIG in a WF. The proposed fuzzy logic controller (FLC is used to control the reactive power delivered to the grid during fault conditions. Moreover, reactive power injection can be increased in the proposed control strategy. Extensive simulations executed in the PSCAD/EMTDC environment for both the proposed and conventional PI controllers of the RSC of the DFIG reveal that the proposed control strategy can stabilize the higher rating of the SCIG.

  13. Fuzzy logic applications in engineering science

    CERN Document Server

    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.

  14. Fuzzy-Logic-Based Gain-Scheduling Control for State-of-Charge Balance of Distributed Energy Storage Systems for DC Microgrids

    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...

  15. Redundant sensor validation by using fuzzy logic

    International Nuclear Information System (INIS)

    Holbert, K.E.; Heger, A.S.; Alang-Rashid, N.K.

    1994-01-01

    This research is motivated by the need to relax the strict boundary of numeric-based signal validation. To this end, the use of fuzzy logic for redundant sensor validation is introduced. Since signal validation employs both numbers and qualitative statements, fuzzy logic provides a pathway for transforming human abstractions into the numerical domain and thus coupling both sources of information. With this transformation, linguistically expressed analysis principles can be coded into a classification rule-base for signal failure detection and identification

  16. Towards the future of fuzzy logic

    CERN Document Server

    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 ...

  17. Development of Real Time Implementation of 5/5 Rule based Fuzzy Logic Controller Shunt Active Power Filter for Power Quality Improvement

    Science.gov (United States)

    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.

  18. Dual mode linguistic hedge fuzzy logic controller for an isolated wind-diesel hybrid power system with superconducting magnetic energy storage unit

    International Nuclear Information System (INIS)

    Thameem Ansari, M.Md.; Velusami, S.

    2010-01-01

    A design of dual mode linguistic hedge fuzzy logic controller for an isolated wind-diesel hybrid power system with superconducting magnetic energy storage unit is proposed in this paper. The design methodology of dual mode linguistic hedge fuzzy logic controller is a hybrid model based on the concepts of linguistic hedges and hybrid genetic algorithm-simulated annealing algorithms. The linguistic hedge operators are used to adjust the shape of the system membership functions dynamically and can speed up the control result to fit the system demand. The hybrid genetic algorithm-simulated annealing algorithm is adopted to search the optimal linguistic hedge combination in the linguistic hedge module. Dual mode concept is also incorporated in the proposed controller because it can improve the system performance. The system with the proposed controller was simulated and the frequency deviation resulting from a step load disturbance is presented. The comparison of the proportional plus integral controller, fuzzy logic controller and the proposed dual mode linguistic hedge fuzzy logic controller shows that, with the application of the proposed controller, the system performance is improved significantly. The proposed controller is also found to be less sensitive to the changes in the parameters of the system and also robust under different operating modes of the hybrid power system.

  19. Control of wastewater N2O emissions by balancing the microbial communities using a fuzzy-logic approach

    DEFF Research Database (Denmark)

    Boiocchi, Riccardo; Gernaey, Krist; Sin, Gürkan

    2016-01-01

    (approximately 35%). On the other side, this reduction of N2O was accompanied by an increase in the aeration costs. Moreover, a plant performance evaluation under dynamic disturbances shows that the effluent quality is compromised due to higher requirements of organic carbon by denitrifying heterotrophs....... The controller can therefore be considered effective for the reduction of N2O production by AOB but would need to be coupled with a secondary control strategy ensuring a complete oxidation of the nitrogen oxides by heterotrophs to have a good effluent quality.......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...

  20. Systematic design of membership functions for fuzzy-logic control: A case study on one-stage partial nitritation/anammox treatment systems.

    Science.gov (United States)

    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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Fuzzy logic an introductory course for engineering students

    CERN Document Server

    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.  

  2. Design of Two Feeder Three Phase Four Wire Distribution System Utilizing Multi Converter UPQC with Fuzzy Logic Controller

    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.

  3. Coordinated Voltage Control in Distribution Network with the Presence of DGs and Variable Loads Using Pareto and Fuzzy Logic

    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.

  4. 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.

  5. Self-tuning fuzzy logic nuclear reactor controller[Proceedings of the 2nd International FLINS Workshop (Mol, Belgium, September 25-27, 1996)

    Energy Technology Data Exchange (ETDEWEB)

    Sharif Heger, A; Alang-Rashid, N K

    1996-07-01

    We present a method for self-tuning of fuzzy logic controllers based on the estimation of the optimum value of the centroids of its output fuzzy set. The method can be implemented on-line and does not require modification of membership functions and control rules. The main features of this method are: the rules are left intact to retain the operator's expertise in the FLC rule base, and the parameters that require any adjustment are identifiable in advance and their number is kept at a minimum. Therefore, the use of this method preserves the control statements in the original form. Results of simulation and actual tests show that this tuning method improves the performance of fuzzy logic controllers in following the desired reactor power level trajectories. In addition, this method demonstrates a similar improvement for power up and power down experiments, based on both simulation and actual case studies. For these experiments, the control rules for the fuzzy logic controller were derived from control statements that expressed the relationships between error, rate of error change, and duration of direction of control rod movements.

  6. Fuzzy logic guided inverse treatment planning

    International Nuclear Information System (INIS)

    Yan Hui; Yin Fangfang; Guan Huaiqun; Kim, Jae Ho

    2003-01-01

    A fuzzy logic technique was applied to optimize the weighting factors in the objective function of an inverse treatment planning system for intensity-modulated radiation therapy (IMRT). Based on this technique, the optimization of weighting factors is guided by the fuzzy rules while the intensity spectrum is optimized by a fast-monotonic-descent method. The resultant fuzzy logic guided inverse planning system is capable of finding the optimal combination of weighting factors for different anatomical structures involved in treatment planning. This system was tested using one simulated (but clinically relevant) case and one clinical case. The results indicate that the optimal balance between the target dose and the critical organ dose is achieved by a refined combination of weighting factors. With the help of fuzzy inference, the efficiency and effectiveness of inverse planning for IMRT are substantially improved

  7. Safety critical application of fuzzy control

    International Nuclear Information System (INIS)

    Schildt, G.H.

    1995-01-01

    After an introduction into safety terms a short description of fuzzy logic will be given. Especially, for safety critical applications of fuzzy controllers a possible controller structure will be described. The following items will be discussed: Configuration of fuzzy controllers, design aspects like fuzzfiication, inference strategies, defuzzification and types of membership functions. As an example a typical fuzzy rule set will be presented. Especially, real-time behaviour a fuzzy controllers is mentioned. An example of fuzzy controlling for temperature control purpose within a nuclear reactor together with membership functions and inference strategy of such a fuzzy controller will be presented. (author). 4 refs, 17 figs

  8. 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.

  9. Answer Sets in a Fuzzy Equilibrium Logic

    Science.gov (United States)

    Schockaert, Steven; Janssen, Jeroen; Vermeir, Dirk; de Cock, Martine

    Since its introduction, answer set programming has been generalized in many directions, to cater to the needs of real-world applications. As one of the most general “classical” approaches, answer sets of arbitrary propositional theories can be defined as models in the equilibrium logic of Pearce. Fuzzy answer set programming, on the other hand, extends answer set programming with the capability of modeling continuous systems. In this paper, we combine the expressiveness of both approaches, and define answer sets of arbitrary fuzzy propositional theories as models in a fuzzification of equilibrium logic. We show that the resulting notion of answer set is compatible with existing definitions, when the syntactic restrictions of the corresponding approaches are met. We furthermore locate the complexity of the main reasoning tasks at the second level of the polynomial hierarchy. Finally, as an illustration of its modeling power, we show how fuzzy equilibrium logic can be used to find strong Nash equilibria.

  10. A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems

    Directory of Open Access Journals (Sweden)

    Yiming Jiang

    2016-01-01

    Full Text Available Over the last few decades, the intelligent control methods such as fuzzy logic control (FLC and neural network (NN control have been successfully used in various applications. The rapid development of digital computer based control systems requires control signals to be calculated in a digital or discrete-time form. In this background, the intelligent control methods developed for discrete-time systems have drawn great attentions. This survey aims to present a summary of the state of the art of the design of FLC and NN-based intelligent control for discrete-time systems. For discrete-time FLC systems, numerous remarkable design approaches are introduced and a series of efficient methods to deal with the robustness, stability, and time delay of FLC discrete-time systems are recommended. Techniques for NN-based intelligent control for discrete-time systems, such as adaptive methods and adaptive dynamic programming approaches, are also reviewed. Overall, this paper is devoted to make a brief summary for recent progresses in FLC and NN-based intelligent control design for discrete-time systems as well as to present our thoughts and considerations of recent trends and potential research directions in this area.

  11. speed control of dc motor on load using fuzzy logic controller

    African Journals Online (AJOL)

    HP

    STUDY OF EMERGENCY LUBE OIL PUMP MOTOR OF H25 HITACHI. TURBINE GENERATOR ... with a reference, and if there is an offset, the controller takes action to ... magnetic flux of the air-gap that exists in the motor provided the field is ... Figure 3: Block Diagram of Field-Controlled DC Motor for Driving Lube Oil Pump.

  12. Fuzzy Reasoning Based on First-Order Modal Logic,

    NARCIS (Netherlands)

    Zhang, Xiaoru; Zhang, Z.; Sui, Y.; Huang, Z.

    2008-01-01

    As an extension of traditional modal logics, this paper proposes a fuzzy first-order modal logic based on believable degree, and gives out a description of the fuzzy first-order modal logic based on constant domain semantics. In order to make the reasoning procedure between the fuzzy assertions

  13. 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.

  14. Optimal Design and Tuning of PID-Type Interval Type-2 Fuzzy Logic Controllers for Delta Parallel Robots

    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.

  15. A logical approach to fuzzy truth hedges

    Czech Academy of Sciences Publication Activity Database

    Esteva, F.; Godo, L.; Noguera, Carles

    2013-01-01

    Roč. 232, č. 1 (2013), s. 366-385 ISSN 0020-0255 Institutional support: RVO:67985556 Keywords : Mathematical fuzzy logic * Standard completeness * Truth hedges Subject RIV: BA - General Mathematics Impact factor: 3.893, year: 2013 http://library.utia.cas.cz/separaty/2016/MTR/noguera-0469148.pdf

  16. 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.

  17. Automating Software Development Process using Fuzzy Logic

    NARCIS (Netherlands)

    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

  18. THE FUZZY LOGIC BASED POWER INJECTION INTO ROTOR CIRCUIT FOR INSTANTANEOUS HIGH TORQUE AND SPEED CONTROL IN INDUCTION MACHINES

    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.

  19. Designing a model for selection of air pollution control equipment using fuzzy logic

    Directory of Open Access Journals (Sweden)

    F. Golbabaei

    2014-07-01

    Conclusion: Finally, the proposed model that is based on the Fuzzy Analytic Hierarchy Process indicates that the Baghouse Technique is the most appropriate technique for the purpose of dust filtration in major sources of air pollution spread in Shargh Cement Company.

  20. Fuzzy logic and neural networks basic concepts & application

    CERN Document Server

    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

  1. Investigation on Fuzzy Logic Based Centralized Control in Four-Port SEPIC/ZETA Bidirectional Converter for Photovoltaic Applications

    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.

  2. 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.

  3. Fuzzy logic: A "simple" solution for complexities in neurosciences?

    Science.gov (United States)

    Godil, Saniya Siraj; Shamim, Muhammad Shahzad; Enam, Syed Ather; Qidwai, Uvais

    2011-02-26

    Fuzzy logic is a multi-valued logic which is similar to human thinking and interpretation. It has the potential of combining human heuristics into computer-assisted decision making, which is applicable to individual patients as it takes into account all the factors and complexities of individuals. Fuzzy logic has been applied in all disciplines of medicine in some form and recently its applicability in neurosciences has also gained momentum. This review focuses on the use of this concept in various branches of neurosciences including basic neuroscience, neurology, neurosurgery, psychiatry and psychology. The applicability of fuzzy logic is not limited to research related to neuroanatomy, imaging nerve fibers and understanding neurophysiology, but it is also a sensitive and specific tool for interpretation of EEGs, EMGs and MRIs and an effective controller device in intensive care units. It has been used for risk stratification of stroke, diagnosis of different psychiatric illnesses and even planning neurosurgical procedures. In the future, fuzzy logic has the potential of becoming the basis of all clinical decision making and our understanding of neurosciences.

  4. Modified Synchronous Reference Frame Based Shunt Active Power Filter with Fuzzy Logic Control Pulse Width Modulation Inverter

    Directory of Open Access Journals (Sweden)

    Suleiman Musa

    2017-05-01

    Full Text Available Harmonic distortion in power networks has greatly reduced power quality and this affects system stability. In order to mitigate this power quality issue, the shunt active power filter (SAPF has been widely applied and it is proven to be the best solution to current harmonics. This paper evaluates the performance of the modified synchronous reference frame extraction (MSRF algorithm with fuzzy logic controller (FLC based current control pulse width modulation (PWM inverter of three-phase three-wire SAPF to mitigate current harmonics. The proposed FLC is designed with a reduced amount of membership functions (MFs and rules, and thus significantly reduces the computational time and memory size. Modeling and simulations of SAPF are carried out using MATLAB/Simulink R2012a with the power system toolbox under steady-state condition, and this is followed with hardware implementation using a TMS320F28335 digital signal processor (DSP, Specrum Digital Inc., Stafford, TX, USA. The results obtained demonstrate a good and satisfactory response to mitigate the harmonics in the system. The total harmonic distortion (THD for the system has been reduced from 25.60% to 0.92% and 1.41% in the simulation study with and without FLC, respectively. Similarly for the experimental study, the SAPF can compensate for the three-phase load current by reducing THD to 5.07% and 7.4% with and without FLC, respectively.

  5. Reference Function Based Spatiotemporal Fuzzy Logic Control Design Using Support Vector Regression Learning

    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.

  6. Hierarchical type-2 fuzzy aggregation of fuzzy controllers

    CERN Document Server

    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.

  7. Fuzzy logic application for extruders replacement problem

    Directory of Open Access Journals (Sweden)

    Edison Conde Perez dos Santos

    2017-03-01

    Full Text Available In a scenario of uncertainty and imprecision, before taking the replacement analysis, a manager needs to consider the uncertain reality of a problem. In this scenario, the fuzzy logic makes an excellent option. Therefore, it is necessary to make a decision based on the fuzzy model. This study is based on the comparison of two methodologies used in the problem of asset replacement. The study, thus, was based on a comparison between two extruders for polypropylene yarn bibliopegy, comparing mainly the costs involved in maintaining the equipment.

  8. IMPLEMENTATION OF FUZZY LOGIC BASED TEMPERATURE ...

    African Journals Online (AJOL)

    transfer function is derived based on process reaction curve obtained from a heat exchanger pilot plant ... The results show that the control performance for a Fuzzy controller is quite similar to ..... Process. Control Instrumentation Technology.

  9. Application of fuzzy logic to social choice theory

    CERN Document Server

    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

  10. Analysis and research on Maximum Power Point Tracking of Photovoltaic Array with Fuzzy Logic Control and Three-point Weight Comparison Method

    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.

  11. 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.

  12. On-line tuning of a fuzzy-logic power system stabilizer

    International Nuclear Information System (INIS)

    Hossein-Zadeh, N.; Kalam, A.

    2002-01-01

    A scheme for on-line tuning of a fuzzy-logic power system stabilizer is presented. firstly, a fuzzy-logic power system stabilizer is developed using speed deviation and accelerating power as the controller input variables. The inference mechanism of fuzzy-logic controller is represented by a decision table, constructed of linguistic IF-THEN rules. The Linguistic rules are available from experts and the design procedure is based on these rules. It assumed that an exact model of the plant is not available and it is difficult to extract the exact parameters of the power plant. Thus, the design procedure can not be based on an exact model. This is an advantage of fuzzy logic that makes the design of a controller possible without knowing the exact model of the plant. Secondly, two scaling parameters are introduced to tune the fuzzy-logic power system stabilizer. These scaling parameters are the outputs of another fuzzy-logic system, which gets the operating conditions of power system as inputs. These mechanism of tuning the fuzzy-logic power system stabilizer makes the fuzzy-logic power system stabilizer adaptive to changes in the operating conditions. Therefore, the degradation of the system response, under a wide range of operating conditions, is less compared to the system response with a fixed-parameter fuzzy-logic power system stabilizer and a conventional (linear) power system stabilizer. The tuned stabilizer has been tested by performing nonlinear simulations using a synchronous machine-infinite bus model. The responses are compared with a fixed parameters fuzzy-logic power system stabilizer and a conventional (linear) power system stabilizer. It is shown that the tuned fuzzy-logic power system stabilizer is superior to both of them

  13. 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.

  14. 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.

  15. IMPLEMENTING FUZZY LOGIC IN DETERMINING SELLING PRICE

    Directory of Open Access Journals (Sweden)

    Danny Prabowo Soetanto

    2000-01-01

    Full Text Available The determination of the price should meet certain criteria, both from the society and the company itself. The combination of various criteria will result in another problem. Fuzzy Logic covers all influencing factors and displays the membership function graphic. Furthermore, by implementing fuzzy rules and fuzzy operator, the right price can be determined which covers all the factors above. The determination of the rules is based on the raw material cost, direct labor cost, distribution cost and the customers' opinion regarding the appropriate price. Then, the model is designed with the help of Matlab software. The result is finally obtained in the form of a model performed by Matlab software. The model displays the output concerning the selling price of the product for each change in the dominant factors.

  16. Bicycle Frame Prediction Techniques with Fuzzy Logic Method

    Directory of Open Access Journals (Sweden)

    Rafiuddin Syam

    2015-03-01

    Full Text Available In general, an appropriate size bike frame would get comfort to the rider while biking. This study aims to predict the simulation system on the bike frame sizes with fuzzy logic. Testing method used is the simulation test. In this study, fuzzy logic will be simulated using Matlab language to test their performance. Mamdani fuzzy logic using 3 variables and 1 output variable intake. Triangle function for the input and output. The controller is designed in the type mamdani with max-min composition and the method deffuzification using center of gravity method. The results showed that height, inseam and Crank Size generating appropriate frame size for the rider associated with comfort. Has a height range between 142 cm and 201 cm. Inseam has a range between 64 cm and 97 cm. Crank has a size range between 175 mm and 180 mm. The simulation results have a range of frame sizes between 13 inches and 22 inches. By using the fuzzy logic can be predicted the size frame of bicycle suitable for the biker.

  17. Bicycle Frame Prediction Techniques with Fuzzy Logic Method

    Directory of Open Access Journals (Sweden)

    Rafiuddin Syam

    2017-03-01

    Full Text Available In general, an appropriate size bike frame would get comfort to the rider while biking. This study aims to predict the simulation system on the bike frame sizes with fuzzy logic. Testing method used is the simulation test. In this study, fuzzy logic will be simulated using Matlab language to test their performance. Mamdani fuzzy logic using 3 variables and 1 output variable intake. Triangle function for the input and output. The controller is designed in the type mamdani with max-min composition and the method deffuzification using center of gravity method. The results showed that height, inseam and Crank Size generating appropriate frame size for the rider associated with comfort. Has a height range between 142 cm and 201 cm. Inseam has a range between 64 cm and 97 cm. Crank has a size range between 175 mm and 180 mm. The simulation results have a range of frame sizes between 13 inches and 22 inches. By using the fuzzy logic can be predicted the size frame of bicycle suitable for the biker.

  18. Use of fuzzy logic in signal processing and validation

    International Nuclear Information System (INIS)

    Heger, A.S.; Alang-Rashid, N.K.; Holbert, K.E.

    1993-01-01

    The advent of fuzzy logic technology has afforded another opportunity to reexamine the signal processing and validation process (SPV). The features offered by fuzzy logic can lend themselves to a more reliable and perhaps fault-tolerant approach to SPV. This is particularly attractive to complex system operations, where optimal control for safe operation depends on reliable input data. The reason for the use of fuzzy logic as the tool for SPV is its ability to transform information from the linguistic domain to a mathematical domain for processing and then transformation of its result back into the linguistic domain for presentation. To ensure the safe and optimal operation of a nuclear plant, for example, reliable and valid data must be available to the human and computer operators. Based on these input data, the operators determine the current state of the power plant and project corrective actions for future states. This determination is based on available data and the conceptual and mathematical models for the plant. A fault-tolerant SPV based on fuzzy logic can help the operators meet the objective of effective, efficient, and safe operation of the nuclear power plant. The ultimate product of this project will be a code that will assist plant operators in making informed decisions under uncertain conditions when conflicting signals may be present

  19. Fuzzy logic model to quantify risk perception

    International Nuclear Information System (INIS)

    Bukh, Julia; Dickstein, Phineas

    2008-01-01

    The aim of this study is a quantification of public risk perception towards the nuclear field so as to be considered in decision making whenever the public involvement is sought. The proposed model includes both qualitative factors such as familiarity and voluntariness and numerical factors influencing risk perception, such as probability of occurrence and severity of consequence. Since part of these factors can be characterized only by qualitative expressions and the determination of them are linked with vagueness, imprecision and uncertainty, the most suitable method for the risk level assessment is Fuzzy Logic, which models qualitative aspects of knowledge and reasoning processes without employing precise quantitative analyses. This work, then, offers a Fuzzy-Logic based mean of representing the risk perception by a single numerical feature, which can be weighted and accounted for in decision making procedures. (author)

  20. Indoor signal attenuation assessment via fuzzy logic

    Directory of Open Access Journals (Sweden)

    Alexandre de Assis Mota

    2011-09-01

    Full Text Available This work focuses on the analysis of signal´s attenuation in indoor environments using a fuzzy logic approach based on the Shadowing Signal Propagation Model (SSPM. The SSPM allows the characterization of the attenuation caused by the environment through the ? parameter present in this model. In addition to this, the Fuzzy Logic provides a form of approximate reasoning that allows the treatment of problems with incomplete, vague and imprecise information. Also, it offers a simple way to obtain a possible solution for a problem using the heuristic knowledge about a particular situation. The results show that the methodology produced satisfactory results, close to the ones yielded by experimental methods.

  1. Stress Testing of an Artificial Pancreas System With Pizza and Exercise Leads to Improvements in the System's Fuzzy Logic Controller.

    Science.gov (United States)

    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.

  2. Fuzzy logic for business, finance, and management

    CERN Document Server

    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

  3. Modeling and Simulation of Control Actuation System with Fuzzy-PID Logic Controlled Brushless Motor Drives for Missiles Glider Applications.

    Science.gov (United States)

    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.

  4. use of fuzzy logic to investigate weather parameter impact

    African Journals Online (AJOL)

    user

    2016-07-03

    Jul 3, 2016 ... developed in the Simulink environment of a MATLAB software. The model ... smoothing, stochastic process, ARMA (autoregressive integrated moving .... 2.3 Building of Fuzzy Logic Simulation Model. The fuzzy model is ...

  5. A PSO-Optimized Fuzzy Logic Control-Based Charging Method for Individual Household Battery Storage Systems within a Community

    Directory of Open Access Journals (Sweden)

    Yu-Shan Cheng

    2018-02-01

    Full Text Available Self-consumption of household photovoltaic (PV storage systems has become profitable for residential owners under the trends of limited feed-in power and decreasing PV feed-in tariffs. For individual PV-storage systems, the challenge mainly lies in managing surplus generation of battery and grid power flow, ideally without relying on error-prone forecasts for both generation and consumption. Considering the large variation in power profiles of different houses in a neighborhood, the strategy is also supposed to be beneficial and applicable for the entire community. In this study, an adaptable battery charging control strategy is designed in order to obtain minimum costs for houses without any meteorological or load forecasts. Based on fuzzy logic control (FLC, battery state-of-charge (SOC and the variation of SOC (∆SOC are taken as input variables to dynamically determine output charging power with minimum costs. The proposed FLC-based algorithm benefits from the charging battery as much as possible during the daytime, and meanwhile properly preserves the capacity at midday when there is high possibility of curtailment loss. In addition, due to distinct power profiles in each individual house, input membership functions of FLC are improved by particle swarm optimization (PSO to achieve better overall performance. A neighborhood with 74 houses in Germany is set up as a scenario for comparison to prior studies. Without forecasts of generation and consumption power, the proposed method leads to minimum costs in 98.6% of houses in the community, and attains the lowest average expenses for a single house each year.

  6. The Type-2 Fuzzy Logic Controller-Based Maximum Power Point Tracking Algorithm and the Quadratic Boost Converter for Pv System

    Science.gov (United States)

    Altin, Necmi

    2018-05-01

    An interval type-2 fuzzy logic controller-based maximum power point tracking algorithm and direct current-direct current (DC-DC) converter topology are proposed for photovoltaic (PV) systems. The proposed maximum power point tracking algorithm is designed based on an interval type-2 fuzzy logic controller that has an ability to handle uncertainties. The change in PV power and the change in PV voltage are determined as inputs of the proposed controller, while the change in duty cycle is determined as the output of the controller. Seven interval type-2 fuzzy sets are determined and used as membership functions for input and output variables. The quadratic boost converter provides high voltage step-up ability without any reduction in performance and stability of the system. The performance of the proposed system is validated through MATLAB/Simulink simulations. It is seen that the proposed system provides high maximum power point tracking speed and accuracy even for fast changing atmospheric conditions and high voltage step-up requirements.

  7. Improvement of Microgrid Dynamic Performance under Fault Circumstances using ANFIS for Fast Varying Solar Radiation and Fuzzy Logic Controller for Wind System

    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.

  8. Fuzzy modeling and control theory and applications

    CERN Document Server

    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.

  9. Full-order Luenberger observer based on fuzzy-logic control for sensorless field-oriented control of a single-sided linear induction motor.

    Science.gov (United States)

    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. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  10. Fuzzy control of small servo motors

    Science.gov (United States)

    Maor, Ron; Jani, Yashvant

    1993-01-01

    To explore the benefits of fuzzy logic and understand the differences between the classical control methods and fuzzy control methods, the Togai InfraLogic applications engineering staff developed and implemented a motor control system for small servo motors. The motor assembly for testing the fuzzy and conventional controllers consist of servo motor RA13M and an encoder with a range of 4096 counts. An interface card was designed and fabricated to interface the motor assembly and encoder to an IBM PC. The fuzzy logic based motor controller was developed using the TILShell and Fuzzy C Development System on an IBM PC. A Proportional-Derivative (PD) type conventional controller was also developed and implemented in the IBM PC to compare the performance with the fuzzy controller. Test cases were defined to include step inputs of 90 and 180 degrees rotation, sine and square wave profiles in 5 to 20 hertz frequency range, as well as ramp inputs. In this paper we describe our approach to develop a fuzzy as well as PH controller, provide details of hardware set-up and test cases, and discuss the performance results. In comparison, the fuzzy logic based controller handles the non-linearities of the motor assembly very well and provides excellent control over a broad range of parameters. Fuzzy technology, as indicated by our results, possesses inherent adaptive features.

  11. 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%

  12. Fuzzy logic controller for the LOLA AO tip-tilt corrector system

    Science.gov (United States)

    Sotelo, Pablo D.; Flores, Ruben; Garfias, Fernando; Cuevas, Salvador

    1998-09-01

    At the INSTITUTO DE ASTRONOMIA we developed an adaptive optics system for the correction of the two first orders of the Zernike polynomials measuring the image controid. Here we discus the two system modalities based in two different control strategies and we present simulations comparing the systems. For the classic control system we present telescope results.

  13. Paraconsistency properties in degree-preserving fuzzy logics

    Czech Academy of Sciences Publication Activity Database

    Ertola, R.; Esteva, F.; Flaminio, T.; Godo, L.; Noguera, Carles

    2015-01-01

    Roč. 19, č. 3 (2015), s. 531-546 ISSN 1432-7643 R&D Projects: GA ČR GAP202/10/1826 Institutional support: RVO:67985556 Keywords : Mathematical fuzzy logic * degree-preserving fuzzy logics * paraconsistent logics * logics of formal inconsistency Subject RIV: BA - General Mathematics Impact factor: 1.630, year: 2015 http://library.utia.cas.cz/separaty/2016/MTR/noguera-0469166.pdf

  14. 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.

  15. MODELLING AND CONTROL OF POWER-SPLIT HYBRID ELECTRIC VEHICLE USING FUZZY LOGIC METHOD

    OpenAIRE

    Mohammadpour, Ebrahim; Khajavi, Mehrdad Nouri

    2014-01-01

    Nowadays, automotive manufactures increasingly have lead to development of hybrid vehicles due to energy consumption growing and increased emissions. the power-split hybrids due to the simultaneous using of speed and torque couplings has integrated advantage of series and parallel hybrid systems and minimize their disadvantages , however the power-split hybrids control strategy is far more complex than other types. Generally the control strategy tries to use the optimize operating point of HE...

  16. Multi-valued and Fuzzy Logic Realization using TaOx Memristive Devices.

    Science.gov (United States)

    Bhattacharjee, Debjyoti; Kim, Wonjoo; Chattopadhyay, Anupam; Waser, Rainer; Rana, Vikas

    2018-01-08

    Among emerging non-volatile storage technologies, redox-based resistive switching Random Access Memory (ReRAM) is a prominent one. The realization of Boolean logic functionalities using ReRAM adds an extra edge to this technology. Recently, 7-state ReRAM devices were used to realize ternary arithmetic circuits, which opens up the computing space beyond traditional binary values. In this manuscript, we report realization of multi-valued and fuzzy logic operators with a representative application using ReRAM devices. Multi-valued logic (MVL), such as Łukasiewicz logic generalizes Boolean logic by allowing more than two truth values. MVL also permits operations on fuzzy sets, where, in contrast to standard crisp logic, an element is permitted to have a degree of membership to a given set. Fuzzy operations generally model human reasoning better than Boolean logic operations, which is predominant in current computing technologies. When the available information for the modelling of a system is imprecise and incomplete, fuzzy logic provides an excellent framework for the system design. Practical applications of fuzzy logic include, industrial control systems, robotics, and in general, design of expert systems through knowledge-based reasoning. Our experimental results show, for the first time, that it is possible to model fuzzy logic natively using multi-state memristive devices.

  17. Development of a system for monitoring and diagnosis using Fuzzy logic in control valves of laboratory test equipment of Experimental Center Aramar

    International Nuclear Information System (INIS)

    Porto Junior, Almir Carlos Soares

    2014-01-01

    The question of components reliability, specifically process control valves, has become an important issue to be investigated in nuclear power plants and other areas such as refinery or offshore oil rig, considering the safety and life extension of the plant. The development of non intrusive monitoring and diagnostic method allows the identification of defects in components of the plant during normal operation. The objective of this dissertation is to present an analysis and diagnosis of control valves of a steam plant part that simulates the secondary circuit of a pressurized water reactor. This installation is part of propulsion equipment testing laboratory of the Brazilian Navy, at Ipero-SP. The methodology for design is based on graphical analysis of two parameters, the valve air pressure actuator and the displacement of the valve plug. These data are extracted by a smart positioner, part of Delta V™ Automation System. An analysis is implemented in detecting anomalies by an approach using Expert Systems by the technique of fuzzy logic. Once the basic measures of control valves are taken, it is possible to detect symptoms of failure, leakage, friction, damage, etc. The monitoring and diagnostic system has been designed in MATLAB® version 2009 th by the complement 'Fuzzy Logic Toolbox'. It is a noninvasive technique. Thus, it is possible to know what is happening with the chosen components, just analyzing the parameters of the valve. The software called ValveLink® (developed by Emerson) receives signals from hardware component (intelligent positioner) installed next to the control valve. These signals (electrical current) are transformed into information which are used input parameters: air pressure valve actuator and valve plug displacement. With the use of fuzzy logic, these parameters are interpreted. They suffer inferences by rules written by experts in valves. After these inferences, the information is processed and sent as output signals

  18. A novel fuzzy-logic control strategy minimizing N2O emissions

    DEFF Research Database (Denmark)

    Boiocchi, Riccardo; Gernaey, Krist; Sin, Gürkan

    2017-01-01

    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...

  19. Driver's Behavior Modeling Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Sehraneh Ghaemi

    2010-01-01

    Full Text Available In this study, we propose a hierarchical fuzzy system for human in a driver-vehicle-environment system to model takeover by different drivers. The driver's behavior is affected by the environment. The climate, road and car conditions are included in fuzzy modeling. For obtaining fuzzy rules, experts' opinions are benefited by means of questionnaires on effects of parameters such as climate, road and car conditions on driving capabilities. Also the precision, age and driving individuality are used to model the driver's behavior. Three different positions are considered for driving and decision making. A fuzzy model called Model I is presented for modeling the change of steering angle and speed control by considering time distances with existing cars in these three positions, the information about the speed and direction of car, and the steering angle of car. Also we obtained two other models based on fuzzy rules called Model II and Model III by using Sugeno fuzzy inference. Model II and Model III have less linguistic terms than Model I for the steering angle and direction of car. The results of three models are compared for a driver who drives based on driving laws.

  20. Closed Loop Fuzzy Logic Controlled PV Based Cascaded Boost Five-Level Inverter System

    Science.gov (United States)

    Revana, Guruswamy; Kota, Venkata Reddy

    2018-04-01

    Recent developments in intelligent control methods and power electronics have produced PV based DC to AC converters related to AC drives. Cascaded boost converter and inverter find their way in interconnecting PV and Induction Motor. This paper deals with digital simulation and implementation of closed loop controlled five-level inverter based Photo-Voltaic (PV) system. The objective of this work is to reduce the harmonics using Multi Level Inverter based system. The DC output from the PV panel is boosted using cascaded-boost-converters. The DC output of these cascaded boost converters is applied to the bridges of the cascaded inverter. The AC output voltage is obtained by the series cascading of the output voltage of the two inverters. The investigations are done with Induction motor load. Cascaded boost-converter is proposed in the present work to produce the required DC Voltage at the input of the bridge inverter. A simple FLC is applied to CBFLIIM system. The FLC is proposed to reduce the steady state error. The simulation results are compared with the hardware results. The results of the comparison are made to show the improvement in dynamic response in terms of settling time and steady state error. Design procedure and control strategy are presented in detail.

  1. Aeration control by monitoring the microbiological activity using fuzzy logic diagnosis and control. Application to a complete autotrophic nitrogen removal reactor

    DEFF Research Database (Denmark)

    Boiocchi, Riccardo; Mauricio Iglesias, Miguel; Vangsgaard, Anna Katrine

    2015-01-01

    Complete Autotrophic Nitrogen Removal (CANR) is a novel process where ammonia is converted to nitrogen gas by different microbial groups. The performance of the process can be compromised by an unbalanced activity of the biomass caused by disturbances or non-optimal operational conditions...... microbial groups on the other hand, the diagnosis provides information on: nitritation, nitratation, anaerobic ammonium oxidation and overall autotrophic nitrogen removal. These four results give insight into the state of the process and are used as inputs for the controller that manipulates the aeration...... 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...

  2. Fuzzy Logic Based MPPT Controller for a Small Wind Turbine System

    DEFF Research Database (Denmark)

    Petrila, Diana; Blaabjerg, Frede; Muntean, Nicolae

    2012-01-01

    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....../Δω. The change of reference generator current (ΔI*) is the output variable. For small power applications, when the turbine inertia is relatively small, and the wind speed changes continuously, it is important to consider the transients in order to develop an accurate theoretical model and to attain optimal...

  3. New Algorithm for the Smoothing Speed Control of Induction Motor in Electric Car based on Self-Tuning Parameter PID-Fuzzy Logic

    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.

  4. 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.

  5. Fuzzy logic controller for cooperative mobile robotics implemented in leader-follower formation approach

    Directory of Open Access Journals (Sweden)

    Manuel Alejandro Molina-Villa

    2015-01-01

    Full Text Available Este artículo presenta el diseño de un controlador de lógica difusa implementandoel método líder-seguidor para un sistema de robótica cooperativa móvil, que permita a ungrupo de robots establecer y mantener una formación geométrica especifi ca mientras sedesplazan siguiendo una trayectoria de referencia. Como resultado de la investigación, seprobó mediante simulación un sistema de control cooperativo, que permite a un grupo derobots mantener una formación específi ca mientras desarrollan una misión determinada.Este controlador permite evadir obstáculos cambiando la formación o cambiando el líder delgrupo en cualquier momento.

  6. SISTEM PENGEMBANGAN KENDALI FUZZY LOGIC BERBASIS MIKROKONTROLER KELUARGA MCS51 (PetraFuz

    Directory of Open Access Journals (Sweden)

    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

  7. Data-Based Control for Humanoid Robots Using Support Vector Regression, Fuzzy Logic, and Cubature Kalman Filter

    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.

  8. Fuzzy logic system for BBT based fertility prediction | Yazed | Journal ...

    African Journals Online (AJOL)

    ... been obtained with the accuracy of 95 % and 80 respectively. Besides, this prediction system using fuzzy logic could improve the current practice in the FAM technique by integrating it with an Internet of Things (IoT) technology for automatic BBT charting and monitoring. Keywords: family planning; fertility; BBT; fuzzy logic.

  9. Comparison of Anti-Virus Programs using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Vaclav Bezdek

    2013-07-01

    Full Text Available This work follows the previous author´s paper: Possible use of Fuzzy Logic in Database. It tries to show application of Fuzzy Logic in selecting the best anti-virus software based on testing made by AV-Comparatives.

  10. Fuzzy logic, neural networks, and soft computing

    Science.gov (United States)

    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

  11. Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships.

    Science.gov (United States)

    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.

  12. Modelling Of Anticipated Damage Ratio On Breakwaters Using Fuzzy Logic

    Science.gov (United States)

    Mercan, D. E.; Yagci, O.; Kabdasli, S.

    2003-04-01

    In breakwater design the determination of armour unit weight is especially important in terms of the structure's life. In a typical experimental breakwater stability study, different wave series composed of different wave heights; wave period and wave steepness characteristics are applied in order to investigate performance the structure. Using a classical approach, a regression equation is generated for damage ratio as a function of characteristic wave height. The parameters wave period and wave steepness are not considered. In this study, differing from the classical approach using a fuzzy logic, a relationship between damage ratio as a function of mean wave period (T_m), wave steepness (H_s/L_m) and significant wave height (H_s) was further generated. The system's inputs were mean wave period (T_m), wave steepness (H_s/L_m) and significant wave height (H_s). For fuzzification all input variables were divided into three fuzzy subsets, their membership functions were defined using method developed by Mandani (Mandani, 1974) and the rules were written. While for defuzzification the centroid method was used. In order to calibrate and test the generated models an experimental study was conducted. The experiments were performed in a wave flume (24 m long, 1.0 m wide and 1.0 m high) using 20 different irregular wave series (P-M spectrum). Throughout the study, the water depth was 0.6 m and the breakwater cross-sectional slope was 1V/2H. In the armour layer, a type of artificial armour unit known as antifer cubes were used. The results of the established fuzzy logic model and regression equation model was compared with experimental data and it was determined that the established fuzzy logic model gave a more accurate prediction of the damage ratio on this type of breakwater. References Mandani, E.H., "Application of Fuzzy Algorithms for Control of Simple Dynamic Plant", Proc. IEE, vol. 121, no. 12, December 1974.

  13. On the Difference between Traditional and Deductive Fuzzy Logic

    Czech Academy of Sciences Publication Activity Database

    Běhounek, Libor

    2008-01-01

    Roč. 159, č. 10 (2008), s. 1153-1164 ISSN 0165-0114 R&D Projects: GA AV ČR KJB100300502 Institutional research plan: CEZ:AV0Z10300504 Keywords : deductive fuzzy logic * fuzzy elements * gradual sets * entropy of fuzzy sets * aggregation * membership degrees * methodology of fuzzy mathematics Subject RIV: BA - General Mathematics Impact factor: 1.833, year: 2008

  14. A Novel Supercapacitor/Lithium-Ion Hybrid Energy System with a Fuzzy Logic-Controlled Fast Charging and Intelligent Energy Management System

    Directory of Open Access Journals (Sweden)

    Muhammad Adil Khan

    2018-05-01

    Full Text Available The electric powered wheelchair (EPW is an essential assistive tool for people with serious injuries or disability. This manuscript describes the validation of applied research for reducing the charging time of an electric wheelchair using a hybrid electric system (HES composed of a supercapacitor (SC bank and a lithium-ion battery with a fuzzy logic controller (FLC-based fast charging system for Li-ion batteries and a fuzzy logic-based intelligent energy management system (FLIEMS for controlling the power flow within the HES. The fast charging FLC was designed to drive the voltage difference (Vd among the different cells of a multi-cell battery and the cell voltage (Vc of an individual cell. These parameters (voltage difference and cell voltage were used as input voltages to reduce the charge time and activate a bypass equalization (BPE scheme. BPE was introduced in this paper so that the battery operates within the safe voltage range. For SC/Li-ion HES, the FLIEMS presented in this paper controls the bi-directional power flow to smooth the power extracted from Li-ion batteries. Moreover, a dual active bridge isolated bidirectional DC converter (DAB-IBDC was used for power conversion. The DAB-IBDC presented in this paper has the characteristics of galvanic isolation, and high power conversion efficiency compared to the conventional converter circuits due to the reduced reverse power flow and current stresses.

  15. Fuzzy Logic Based The Application of Multi-Microcontroller in Mobile Robot Model

    Directory of Open Access Journals (Sweden)

    Nuryono Satya Widodo

    2009-12-01

    Full Text Available This paper proposed a fuzzy logic based mobile robot as implemented in a multimicrocontroller system. Fuzzy logic controller was developed based on a behavior based approach. The Controller inputs were obtained from seven sonar sensor and three tactile switches. Behavior based approach was implemented in different level priority of behaviors. The behaviors were: obstacle avoidance, wall following and escaping as the emergency behavior. The results show that robot was able to navigate autonomously and avoid the entire obstacle.

  16. Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty

    CERN Document Server

    Starczewski, Janusz T

    2013-01-01

    This book generalizes fuzzy logic systems for different types of uncertainty, including - semantic ambiguity resulting from limited perception or lack of knowledge about exact membership functions - lack of attributes or granularity arising from discretization of real data - imprecise description of membership functions - vagueness perceived as fuzzification of conditional attributes. Consequently, the membership uncertainty can be modeled by combining methods of conventional and type-2 fuzzy logic, rough set theory and possibility theory.            In particular, this book provides a number of formulae for implementing the operation extended on fuzzy-valued fuzzy sets and presents some basic structures of generalized uncertain fuzzy logic systems, as well as introduces several of methods to generate fuzzy membership uncertainty. It is desirable as a reference book for under-graduates in higher education, master and doctor graduates in the courses of computer science, computational intelligence, or...

  17. On logical, algebraic, and probabilistic aspects of fuzzy set theory

    CERN Document Server

    Mesiar, Radko

    2016-01-01

    The book is a collection of contributions by leading experts, developed around traditional themes discussed at the annual Linz Seminars on Fuzzy Set Theory. The different chapters have been written by former PhD students, colleagues, co-authors and friends of Peter Klement, a leading researcher and the organizer of the Linz Seminars on Fuzzy Set Theory. The book also includes advanced findings on topics inspired by Klement’s research activities, concerning copulas, measures and integrals, as well as aggregation problems. Some of the chapters reflect personal views and controversial aspects of traditional topics, while others deal with deep mathematical theories, such as the algebraic and logical foundations of fuzzy set theory and fuzzy logic. Originally thought as an homage to Peter Klement, the book also represents an advanced reference guide to the mathematical theories related to fuzzy logic and fuzzy set theory with the potential to stimulate important discussions on new research directions in the fiel...

  18. A Novel Quantum-Behaved Lightning Search Algorithm Approach to Improve the Fuzzy Logic Speed Controller for an Induction Motor Drive

    Directory of Open Access Journals (Sweden)

    Jamal Abd Ali

    2015-11-01

    Full Text Available This paper presents a novel lightning search algorithm (LSA using quantum mechanics theories to generate a quantum-inspired LSA (QLSA. The QLSA improves the searching of each step leader to obtain the best position for a projectile. To evaluate the reliability and efficiency of the proposed algorithm, the QLSA is tested using eighteen benchmark functions with various characteristics. The QLSA is applied to improve the design of the fuzzy logic controller (FLC for controlling the speed response of the induction motor drive. The proposed algorithm avoids the exhaustive conventional trial-and-error procedure for obtaining membership functions (MFs. The generated adaptive input and output MFs are implemented in the fuzzy speed controller design to formulate the objective functions. Mean absolute error (MAE of the rotor speed is the objective function of optimization controller. An optimal QLSA-based FLC (QLSAF optimization controller is employed to tune and minimize the MAE, thereby improving the performance of the induction motor with the change in speed and mechanical load. To validate the performance of the developed controller, the results obtained with the QLSAF are compared to the results obtained with LSA, the backtracking search algorithm (BSA, the gravitational search algorithm (GSA, the particle swarm optimization (PSO and the proportional integral derivative controllers (PID, respectively. Results show that the QLASF outperforms the other control methods in all of the tested cases in terms of damping capability and transient response under different mechanical loads and speeds.

  19. Petr Hájek on mathematical fuzzy logic

    CERN Document Server

    Montagna, Franco

    2014-01-01

    This volume celebrates the work of Petr Hájek on mathematical fuzzy logic and presents how his efforts have influenced prominent logicians who are continuing his work. The book opens with a discussion on Hájek's contribution to mathematical fuzzy logic and with a scientific biography of him, progresses to include two articles with a foundation flavour, that demonstrate some important aspects of Hájek's production, namely, a paper on the development of fuzzy sets and another paper on some fuzzy versions of set theory and arithmetic. Articles in the volume also focus on the treatment of vague

  20. using fuzzy logic in image processing

    International Nuclear Information System (INIS)

    Ashabrawy, M.A.F.

    2002-01-01

    due to the unavoidable merge between computer and mathematics, the signal processing in general and the processing in particular have greatly improved and advanced. signal processing deals with the processing of any signal data for use by a computer, while image processing deals with all kinds of images (just images). image processing involves the manipulation of image data for better appearance and viewing by people; consequently, it is a rapidly growing and exciting field to be involved in today . this work takes an applications - oriented approach to image processing .the applications; the maps and documents of the first egyptian research reactor (ETRR-1), the x-ray medical images and the fingerprints image. since filters, generally, work continuous ranges rather than discrete values, fuzzy logic techniques are more convenient.thee techniques are powerful in image processing and can deal with one- dimensional, 1-D and two - dimensional images, 2-D images as well

  1. Fruit Sorting Using Fuzzy Logic Techniques

    Science.gov (United States)

    Elamvazuthi, Irraivan; Sinnadurai, Rajendran; Aftab Ahmed Khan, Mohamed Khan; Vasant, Pandian

    2009-08-01

    Fruit and vegetables market is getting highly selective, requiring their suppliers to distribute the goods according to very strict standards of quality and presentation. In the last years, a number of fruit sorting and grading systems have appeared to fulfill the needs of the fruit processing industry. However, most of them are overly complex and too costly for the small and medium scale industry (SMIs) in Malaysia. In order to address these shortcomings, a prototype machine was developed by integrating the fruit sorting, labeling and packing processes. To realise the prototype, many design issues were dealt with. Special attention is paid to the electronic weighing sub-system for measuring weight, and the opto-electronic sub-system for determining the height and width of the fruits. Specifically, this paper discusses the application of fuzzy logic techniques in the sorting process.

  2. A Hedge for Gödel Fuzzy Logic

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr; Harmancová, Dagmar

    2000-01-01

    Roč. 8, č. 4 (2000), s. 495-498 ISSN 0218-4885 Grant - others:COST(XE) Action 15 Institutional research plan: AV0Z1030915 Keywords : fuzzy logic * Gödel logic * intuitionistic logic * hedges Subject RIV: BA - General Mathematics Impact factor: 0.145, year: 2000

  3. Interdisciplinarity, logic of uncertainty and fuzzy logic in primary school

    Directory of Open Access Journals (Sweden)

    Luciana Delli Rocili

    2015-12-01

    Full Text Available On the occasion of the 120th anniversary of Mathesis, this work wants to be a memory, a tribute to two great presidents of Mathesis: Bruno de Finetti and Angelo Fadini. Both have pursued the idea of interdisciplinary teaching and research. Bruno de Finetti, with his books on The invention of truth, (1934, and on Logic and Intuitive Mathematics, (1959, and his very famous "Theory of probability", (1970, shows a rejection of formal education, comfortable, monodisciplinary, made of certainties, and chooses the impervious way of addressing the problems that are to the base of science. Angelo Fadini, with his papers and books on Theory of Fuzzy Sets, shows first in Italy several logical questions which puts as the basis for practical applications in Architecture. This paper is an attempt to experiment, in an interdisciplinary framework, the basic ideas of Bruno de Finetti and Angelo Fadini in primary school, in the belief that in the Primary School are formed ideas and intuitions, while in the secondary school the attention is focused mainly on specific issues of Mathematics. We shows some results of a still ongoing experimentation.   Interdisciplinarietà, logica dell'incerto e logica sfumata nella scuola primaria In occasione dei 120 anni della Mathesis, questo lavoro vuole essere un ricordo, un omaggio a due grandi Presidenti della Mathesis: Bruno de Finetti e Angelo Fadini. Entrambi hanno portato avanti l’idea della interdisciplinarietà nell’insegnamento e nella ricerca. Bruno de Finetti, con la sua “Matematica Logico Intuitiva” del 1959, e la sua “Teoria delle probabilità”, del 1970, e ancora prima, con “L’invenzione della verità”, del 1934, mostra un rifiuto dell’insegnamento formale, comodo, monodisciplinare, fatto di certezze, e sceglie la strada impervia dell’affrontare i problemi che sono alla base della scienza. Angelo Fadini, con la sua Teoria degli Insiemi Sfocati, mostra per primo in Italia varie questioni

  4. Perancangan Kendali Robot pada Smartphone Menggunakan Sensor Accelerometer Berbasis Metode Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Mohamad Agung Prawira Negara

    2017-08-01

    Full Text Available Telecommunications and robotics technology is being developed to assist and facilitate the work of a human. In the field of telecommunications particularly smartphone has reached the planting of operating systems like android until planting sensors such as an accelerometer, gyro, proximity, etc. We would like to take advantage of the accelerometer sensor on a smartphone as robot control. We will compare the use of Sugeno Fuzzy Logic and Mamdani Fuzzy Logic to determine the best control method. The basic components of the robot are the Bluetooth module HC-05 as a medium of communication with the android, arduino as the control system and actuators such as DC motors drive the rear wheels to adjust the speed of the robot, and servo motor drives the front wheels to adjust the degree of turn robot. In robot’s movement test, 4 of 8 trials or approximately 50% stated better Sugeno Fuzzy Logic than Mamdani Fuzzy Logic in terms of linearity. In robot's controller response test, for Sugeno Fuzzy Logic method the average delay is 0.41 seconds, and for Mamdani Fuzzy Logic method the average delay is 10.80 seconds.

  5. PENGGUNAAN FUZZY LOGIC UNTUK KONTROL PARALLEL CONVERTER DC-DC

    Directory of Open Access Journals (Sweden)

    Bambang Prio Hartono

    2012-09-01

    Full Text Available Abstract: Using system fuzzy logic as control  technology have been used on low load dc-dc converter with combined parallel compiled  dc-dc converter can  obtain big load.   With existence of differrence of component parameter and each parallel compiled converter can obtained different current  and voltage output.  Function of controller  for to do adjustment, so that current which is applied  to  load by each converter  can be obtained  difference error as small as possible or same. The object of research is developing design of large signal dc-dc converter which is  combined with using  FLC so that  obtain  better performance.  To get better performance have been made plant model and simulation with CDE method.  The more systematic  system and design is needed to overcome bigger load  on dc-dc converter, so that parallel  compiled current master slave control system on dc-dc converter with using fuzzy logic  controller is used. Result of  research showed that error or difference of  current  which is applied to load can handled by fuzzy logic  controller.  Technic of current and voltage controller co to do adjustment current and voltage distribution  equally to load.  Distribution of iL1,iL2 and  output voltage Vo on dc-dc  converter with load 2,25 until  7,875 and voltage  100  until 120 volt,  load current beetwen  12 until 48, % relatif  error  Vo  0,4% until  0,9%.

  6. A novel optimized hybrid fuzzy logic intelligent PID controller for an interconnected multi-area power system with physical constraints and boiler dynamics.

    Science.gov (United States)

    Gomaa Haroun, A H; Li, Yin-Ya

    2017-11-01

    In the fast developing world nowadays, load frequency control (LFC) is considered to be a most significant role for providing the power supply with good quality in the power system. To deliver a reliable power, LFC system requires highly competent and intelligent control technique. Hence, in this article, a novel hybrid fuzzy logic intelligent proportional-integral-derivative (FLiPID) controller has been proposed for LFC of interconnected multi-area power systems. A four-area interconnected thermal power system incorporated with physical constraints and boiler dynamics is considered and the adjustable parameters of the FLiPID controller are optimized using particle swarm optimization (PSO) scheme employing an integral square error (ISE) criterion. The proposed method has been established to enhance the power system performances as well as to reduce the oscillations of uncertainties due to variations in the system parameters and load perturbations. The supremacy of the suggested method is demonstrated by comparing the simulation results with some recently reported heuristic methods such as fuzzy logic proportional-integral (FLPI) and intelligent proportional-integral-derivative (PID) controllers for the same electrical power system. the investigations showed that the FLiPID controller provides a better dynamic performance and outperform compared to the other approaches in terms of the settling time, and minimum undershoots of the frequency as well as tie-line power flow deviations following a perturbation, in addition to perform appropriate settlement of integral absolute error (IAE). Finally, the sensitivity analysis of the plant is inspected by varying the system parameters and operating load conditions from their nominal values. It is observed that the suggested controller based optimization algorithm is robust and perform satisfactorily with the variations in operating load condition, system parameters and load pattern. Copyright © 2017 ISA. Published by

  7. Intelligent control-III: fuzzy control system

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    During the last decade or so, fuzzy logic control (FLC) has emerged as one of the most active and fruitful areas of research and development. The applications include industrial process control to medical diagnostic and financial markets. Many consumer products using this technology are available in the market place. FLC is best suited to complex ill-defined processes that can be controlled by a skilled human operator without much knowledge of their underlying dynamics. This lecture will cover the basic architecture and the design methodology of fuzzy logic controllers. FLC will be strongly based on the concepts of fuzzy set theory, introduced in first lecture. Some practical applications will also be discussed and presented. (author)

  8. Control of a mechanical gripper with a fuzzy controller

    International Nuclear Information System (INIS)

    Alberdi, J.; Barcala, J.M.; Gamero, E.; Navarrete, J.J.

    1995-01-01

    A fuzzy logic system is used to control a mechanical gripper. System is based in a NLX230 fuzzy micro controller. Control rules are programmed by a 68020 microprocessor in the micro controller memory. Stress and its derived are used as feedback signals in the control. This system can adapt its effort to the mechanical resistance of the object between the fingers. (Author)

  9. Fuzzy logic type 1 and type 2 based on LabVIEW FPGA

    CERN Document Server

    Ponce-Cruz, Pedro; MacCleery, Brian

    2016-01-01

    This book is a comprehensive introduction to LabVIEW FPGA™, a package allowing the programming of intelligent digital controllers in field programmable gate arrays (FPGAs) using graphical code. It shows how both potential difficulties with understanding and programming in VHDL and the consequent difficulty and slowness of implementation can be sidestepped. The text includes a clear theoretical explanation of fuzzy logic (type 1 and type 2) with case studies that implement the theory and systematically demonstrate the implementation process. It goes on to describe basic and advanced levels of programming LabVIEW FPGA and show how implementation of fuzzy-logic control in FPGAs improves system responses. A complete toolkit for implementing fuzzy controllers in LabVIEW FPGA has been developed with the book so that readers can generate new fuzzy controllers and deploy them immediately. Problems and their solutions allow readers to practice the techniques and to absorb the theoretical ideas as they arise. Fuzzy L...

  10. Compensation of Actuator’s Saturation by Using Fuzzy Logic and Imperialist Competitive Algorithm in a System with PID Controller

    Directory of Open Access Journals (Sweden)

    Abbas Ali Zamani

    2012-07-01

    Full Text Available Physical systems always include constraints and limits. Usually, the limits and constraints, in the control systems, are appeared as temperature and pressure limits or pumps capacity. One of the existing limits in the systems with PID controller is associated with the actuator’s saturation limits. With the saturating of the actuator, the controller’s output and plant’s input will be different and the output signal of controller do not lead the system and their states could not update correctly where this issue makes the system response undesirable. In this paper, by adding a fuzzy compensator that it’s parameters are tuned using imperialist competitive algorithm, the actuator saturation is prevented and the important parameters of the system response, such as setting time and overshoot, are improved.

  11. INDONESIA PUBLIC BANKS PERFORMANCE EVALUATION USING FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Sugiarto Sugiarto

    2016-10-01

    Full Text Available Return on Asset (ROA is a variable that has the greatest ability in predicting public banks stock prices in Indonesia. The coefficient of determination of ROA on public banks stock prices in Indonesia reached 54.8%. ROA has a significant positive influence on public bank stock prices in Indonesia. Fuzzy logic process on the performance of the 15 public banks in Indonesia have been carried out using the data of ROA for the period 2010 up to 2013. Bank reference performance according to ROA is based on Bank Indonesia Letter No. 6 / 23DPNP / 2011. The performance of each bank was analyzed by conventional methods and as a comparison used fuzzy logic. The evaluation with fuzzy logic method able to provide added value to the currently enforced performance evaluation method. There is significant difference in conclusion between the determination of fuzzy logic models and conventional method

  12. Fuzzy Logic and Its Application in Football Team Ranking

    Directory of Open Access Journals (Sweden)

    Wenyi Zeng

    2014-01-01

    some certain rules, we propose four parameters to calculate fuzzy similar matrix, obtain fuzzy equivalence matrix and the ranking result for our numerical example, T7, T3, T1, T9, T10, T8, T11, T12, T2, T6, T5, T4, and investigate four parameters sensitivity analysis. The study shows that our fuzzy logic method is reliable and stable when the parameters change in certain range.

  13. Speed control and generation of electric power of a gas turbine by means of fuzzy-logic; Control de velocidad y de generacion de potencia electrica de una turbina de gas mediante logica difusa

    Energy Technology Data Exchange (ETDEWEB)

    Bahamaca Fernandez, Luis Jonathan

    2000-08-01

    The development of a fuzzy-logic control algorithm is presented. It was developed for the speed and load control of a gas turbine. The speed/load controller of the gas turbine which were conventional Pi's were completely replaced by the fuzzy-logic controllers. The fuzzy controllers correspond to MISO systems that has as input the error an its rate of change and as an output the control signal for the fuel valve. The fuzzy controller provides an algorithm that can turn a strategy of linguistic control (based on knowledge of experts) into a strategy of automatic control. The fuzzy controllers were validated by the development of functional test in a simulation of a nonlinear mathematical gas-turbine model. The controllers were programmed in C language in PC. Simulation test for the speed regulation and load tracking were used for the controller validation. The fuzzy controller had a good performance because the minimized the signal error produced by the set of programmed system perturbations (due to control actions). Besides, they had a better reference tracking then PI controllers. Consequently, the proposed fuzzy controllers have a better performance than the conventional control system. [Spanish] En este trabajo de tesis se presenta el diseno, programacion y evaluacion de un algoritmo de control basado en logica difusa para el control de velocidad y generacion de potencia electrica de una turbina de gas. En el esquema de control velocidad/carga de la turbina de gas, se sustituyeron completamente los dos controladores convencionales del tipo PI por controladores difusos, teniendo asi un control digital directo. Los controladores difusos corresponden a sistemas MISO que utilizan como variables de entrada el error y la derivada del error, y como variable de salida la senal de control a la valvula de combustible. De esta forma, un controlador difuso provee un algoritmo que puede convertir una estrategia de control linguistico (basado en conocimiento de expertos

  14. Fuzzy logic based ELF magnetic field estimation in substations

    International Nuclear Information System (INIS)

    Kosalay, I.

    2008-01-01

    This paper examines estimation of the extremely low frequency magnetic fields (MF) in the power substation. First, the results of the previous relevant research studies and the MF measurements in a sample power substation are presented. Then, a fuzzy logic model based on the geometric definitions in order to estimate the MF distribution is explained. Visual software, which has a three-dimensional screening unit, based on the fuzzy logic technique, has been developed. (authors)

  15. Implementation of Real-Time Machining Process Control Based on Fuzzy Logic in a New STEP-NC Compatible System

    Directory of Open Access Journals (Sweden)

    Po Hu

    2016-01-01

    Full Text Available Implementing real-time machining process control at shop floor has great significance on raising the efficiency and quality of product manufacturing. A framework and implementation methods of real-time machining process control based on STEP-NC are presented in this paper. Data model compatible with ISO 14649 standard is built to transfer high-level real-time machining process control information between CAPP systems and CNC systems, in which EXPRESS language is used to define new STEP-NC entities. Methods for implementing real-time machining process control at shop floor are studied and realized on an open STEP-NC controller, which is developed using object-oriented, multithread, and shared memory technologies conjunctively. Cutting force at specific direction of machining feature in side mill is chosen to be controlled object, and a fuzzy control algorithm with self-adjusting factor is designed and embedded in the software CNC kernel of STEP-NC controller. Experiments are carried out to verify the proposed framework, STEP-NC data model, and implementation methods for real-time machining process control. The results of experiments prove that real-time machining process control tasks can be interpreted and executed correctly by the STEP-NC controller at shop floor, in which actual cutting force is kept around ideal value, whether axial cutting depth changes suddenly or continuously.

  16. Qualitative assessment of environmental impacts through fuzzy logic

    International Nuclear Information System (INIS)

    Peche G, Roberto

    2008-01-01

    The vagueness of many concepts usually utilized in environmental impact studies, along with frequent lack of quantitative information, suggests that fuzzy logic can be applied to carry out qualitative assessment of such impacts. This paper proposes a method for valuing environmental impacts caused by projects, based on fuzzy sets theory and methods of approximate reasoning. First, impacts must be described by a set of features. A linguistic variable is assigned to each feature, whose values are fuzzy sets. A fuzzy evaluation of environmental impacts is achieved using rule based fuzzy inference and the estimated fuzzy value of each feature. Generalized modus ponens has been the inference method. Finally, a crisp value of impact is attained by aggregation and defuzzification of all fuzzy results

  17. Single Stage String Inverter for Gridconnected Photovoltaic System with Modified Perturb and Observe (P&O Fuzzy Logic Control(FLC-based MPPT Technique

    Directory of Open Access Journals (Sweden)

    S.Z.Mohammad Noor

    2016-06-01

    Full Text Available This paper presents an implementation of Single-phase Single stage String inverter for Grid connected Photovoltaic (PV system. The proposed system uses Modified Perturb and Observe (P&O algorithm implemented using Fuzzy Logic Control (FLC as Maximum Power Point Tracking (MPPT. The inverter is designed for 340W system using two series of STP170s24/Ac PV modules. The MPPT unit keeps tracking the maximum power from the PV array by changing the modulation index and the phase angle of inverter’s output voltage. The simulation model is developed using Matlab/Simulink to evaluate the performance of the converter. Selected experimental results are also presented in this paper.

  18. Intelligent tuning of vibration mitigation process for single link manipulator using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Ahmed A. Ali

    2017-08-01

    Full Text Available In this work, active vibration mitigation for smart single link manipulator is presented. Two piezoelectric transducers were utilized to act as actuator and sensor respectively. Classical Proportional (P controller was tested numerically and experimentally. The comparison between measured results showed good agreement. The proposed work includes the introducing of fuzzy logic for tuning controller's gain within finite element method. Classical Proportional-Integral (PI, Fuzzy-P and Fuzzy-PI controllers were totally integrated as a series of [IF-Then] states and solved numerically by using Finite Element (FE solver (ANSYS. Proposed method will pave the way on solving the tuning process totally within single FE solver with high efficiency. Proposed method satisfied mitigation in the overall free response with about 52% and 74% of the manipulator settling time when Fuzzy-P and Fuzzy-PI controllers were activated respectively. This contribution can be utilized for many other applications related to fuzzy topics.

  19. Fuzzy Logic Approach to Diagnosis of Feedwater Heater Performance Degradation

    International Nuclear Information System (INIS)

    Kang, Yeon Kwan; Kim, Hyeon Min; Heo, Gyun Young; Sang, Seok Yoon

    2014-01-01

    Since failure in, damage to, and performance degradation of power generation components in operation under harsh environment of high pressure and high temperature may cause both economic and human loss at power plants, highly reliable operation and control of these components are necessary. Therefore, a systematic method of diagnosing the condition of these components in its early stages is required. There have been many researches related to the diagnosis of these components, but our group developed an approach using a regression model and diagnosis table, specializing in diagnosis relating to thermal efficiency degradation of power plant. However, there was a difficulty in applying the method using the regression model to power plants with different operating conditions because the model was sensitive to value. In case of the method that uses diagnosis table, it was difficult to find the level at which each performance degradation factor had an effect on the components. Therefore, fuzzy logic was introduced in order to diagnose performance degradation using both qualitative and quantitative results obtained from the components' operation data. The model makes performance degradation assessment using various performance degradation variables according to the input rule constructed based on fuzzy logic. The purpose of the model is to help the operator diagnose performance degradation of components of power plants. This paper makes an analysis of power plant feedwater heater by using fuzzy logic. Feedwater heater is one of the core components that regulate life-cycle of a power plant. Performance degradation has a direct effect on power generation efficiency. It is not easy to observe performance degradation of feedwater heater. However, on the other hand, troubles such as tube leakage may bring simultaneous damage to the tube bundle and therefore it is the object of concern in economic aspect. This study explains the process of diagnosing and verifying typical

  20. Fuzzy Logic Approach to Diagnosis of Feedwater Heater Performance Degradation

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Yeon Kwan; Kim, Hyeon Min; Heo, Gyun Young [Kyung Hee University, Yongin (Korea, Republic of); Sang, Seok Yoon [Engineering and Technical Center, Korea Hydro, Daejeon (Korea, Republic of)

    2014-08-15

    Since failure in, damage to, and performance degradation of power generation components in operation under harsh environment of high pressure and high temperature may cause both economic and human loss at power plants, highly reliable operation and control of these components are necessary. Therefore, a systematic method of diagnosing the condition of these components in its early stages is required. There have been many researches related to the diagnosis of these components, but our group developed an approach using a regression model and diagnosis table, specializing in diagnosis relating to thermal efficiency degradation of power plant. However, there was a difficulty in applying the method using the regression model to power plants with different operating conditions because the model was sensitive to value. In case of the method that uses diagnosis table, it was difficult to find the level at which each performance degradation factor had an effect on the components. Therefore, fuzzy logic was introduced in order to diagnose performance degradation using both qualitative and quantitative results obtained from the components' operation data. The model makes performance degradation assessment using various performance degradation variables according to the input rule constructed based on fuzzy logic. The purpose of the model is to help the operator diagnose performance degradation of components of power plants. This paper makes an analysis of power plant feedwater heater by using fuzzy logic. Feedwater heater is one of the core components that regulate life-cycle of a power plant. Performance degradation has a direct effect on power generation efficiency. It is not easy to observe performance degradation of feedwater heater. However, on the other hand, troubles such as tube leakage may bring simultaneous damage to the tube bundle and therefore it is the object of concern in economic aspect. This study explains the process of diagnosing and verifying typical

  1. A Note on the Notion of Truth in Fuzzy Logic

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr; Shepherdson, J.

    2001-01-01

    Roč. 109, 1-2 (2001), s. 65-69 ISSN 0168-0072 Institutional research plan: AV0Z1030915 Keywords : many-valued logic * fuzzy logic Subject RIV: BA - General Mathematics Impact factor: 0.519, year: 2001

  2. Expanding Basic Fuzzy Logic with Truth Constants for Component Delimiters

    Czech Academy of Sciences Publication Activity Database

    Haniková, Zuzana

    2012-01-01

    Roč. 197, 16 June (2012), s. 95-107 ISSN 0165-0114 R&D Projects: GA ČR GEICC/08/E018 Institutional research plan: CEZ:AV0Z10300504 Keywords : mathematics * non-classical logics * algebra * basic fuzzy logic BL * propositional constants Subject RIV: BA - General Mathematics Impact factor: 1.749, year: 2012

  3. RANCANG BANGUN FERMENTOR YOGURT DENGAN SISTEM KONTROL LOGIKA FUZZY MENGGUNAKAN MIKROKONTROLER ATMEGA32 (Yogurt Fermenter Design with Fuzzy Logic Control System Using Microcontroller ATMega32

    Directory of Open Access Journals (Sweden)

    Dimas Firmanda Al Riza

    2015-02-01

    settling time selama 1 jam 20 menit dan rata-rata error sebesar -0,36 oC. Proses fermentasi selama 16 jam menggunakan fermentor dengan kontroler fuzzy menghasilkan yogurt dengan pH sebesar 3,66, jumlah mikroba Lactobacillus sp. sebanyak 4,85 x 108cfu/mL, dan Streptococcus sp. sebanyak 1,34 x 10 6 cfu/mL. Kata kunci: Fermentasi, yogurt, susu sapi, fuzzy, kontrol suhu

  4. Conventional control and fuzzy control of a dc-dc converter for machine drive

    Energy Technology Data Exchange (ETDEWEB)

    Radoi, C.; Florescu, A. [Department of Power Electronics `Politecnica` University Bucharest (Romania)

    1997-12-31

    Fuzzy logic or fuzzy set theory is recently getting increasing emphasis in process control applications. The paper describes an application of fuzzy logic in speed control system that uses a dc-dc converter. The fuzzy control is used to linearize the family of external characteristics of the converter in discontinuous-conduction mode occurring at light load and/or high speed. In order to compare the conventional control with the fuzzy logic control, algorithms have been developed in detail and verified by Microsoft Excel simulation. The simulation study indicates that fuzzy control is a good alternative for conventional control methods, being used particularly in non-linear complex systems ill defined or totally unknown. Where the mathematical model exists, it is useful. The applications of fuzzy set theory in power electronics are almost entirely new; fuzzy logic seems to have a lot of premises in the large industrial control field. (orig.) 2 refs.

  5. Using a coupled inductor controlled by fuzzy logic to improve the efficiency of a Buck converter in a PV system

    Directory of Open Access Journals (Sweden)

    Abouchabana Nabil

    2017-01-01

    Full Text Available Photovoltaic generators (PVG produce a variable power according to the solar radiation (G and temperature (T. This variation affects the sizing of the components of DC / DC converters, powered by such PVG, and make it difficult. The effects may differ from one component to another. The main and critical one is presented by the inductor, the element that stores the energy during sampled periods. We propose in this work an auto-adaptation of these inductor values to maintain optimal performance of the power yield of these converters. Our idea is to replace the inductor by a coupled inductor where this adjustment is made by the addition of an adjustable electric field in the magnetic core. Low current intensities come from the PVG supply the second inductor of the coupled inductor through a circuit controlled by a fuzzy controller (FC. The whole system is modeled and simulated under MATLAB/SIMULINK for the control part of the system and under PSPICE for the power part of the system. The obtained results show good performances of the proposed converter over the standard one.

  6. Using a coupled inductor controlled by fuzzy logic to improve the efficiency of a Buck converter in a PV system

    Science.gov (United States)

    Abouchabana, Nabil; Haddadi, Mourad; Rabhi, Abdelhamid; El Hajjaji, Ahmed

    2017-11-01

    Photovoltaic generators (PVG) produce a variable power according to the solar radiation (G) and temperature (T). This variation affects the sizing of the components of DC / DC converters, powered by such PVG, and make it difficult. The effects may differ from one component to another. The main and critical one is presented by the inductor, the element that stores the energy during sampled periods. We propose in this work an auto-adaptation of these inductor values to maintain optimal performance of the power yield of these converters. Our idea is to replace the inductor by a coupled inductor where this adjustment is made by the addition of an adjustable electric field in the magnetic core. Low current intensities come from the PVG supply the second inductor of the coupled inductor through a circuit controlled by a fuzzy controller (FC). The whole system is modeled and simulated under MATLAB/SIMULINK for the control part of the system and under PSPICE for the power part of the system. The obtained results show good performances of the proposed converter over the standard one.

  7. Improvements to Earthquake Location with a Fuzzy Logic Approach

    Science.gov (United States)

    Gökalp, Hüseyin

    2018-01-01

    In this study, improvements to the earthquake location method were investigated using a fuzzy logic approach proposed by Lin and Sanford (Bull Seismol Soc Am 91:82-93, 2001). The method has certain advantages compared to the inverse methods in terms of eliminating the uncertainties of arrival times and reading errors. In this study, adopting this approach, epicentral locations were determined based on the results of a fuzzy logic space concerning the uncertainties in the velocity models. To map the uncertainties in arrival times into the fuzzy logic space, a trapezoidal membership function was constructed by directly using the travel time difference between the two stations for the P- and S-arrival times instead of the P- and S-wave models to eliminate the need for obtaining information concerning the velocity structure of the study area. The results showed that this method worked most effectively when earthquakes occurred away from a network or when the arrival time data contained phase reading errors. In this study, to resolve the problems related to determining the epicentral locations of the events, a forward modeling method like the grid search technique was used by applying different logical operations (i.e., intersection, union, and their combination) with a fuzzy logic approach. The locations of the events were depended on results of fuzzy logic outputs in fuzzy logic space by searching in a gridded region. The process of location determination with the defuzzification of only the grid points with the membership value of 1 obtained by normalizing all the maximum fuzzy output values of the highest values resulted in more reliable epicentral locations for the earthquakes than the other approaches. In addition, throughout the process, the center-of-gravity method was used as a defuzzification operation.

  8. Fuzzy logic and neural networks in artificial intelligence and pattern recognition

    Science.gov (United States)

    Sanchez, Elie

    1991-10-01

    With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

  9. Why fuzzy controllers should be fuzzy

    International Nuclear Information System (INIS)

    Nowe, A.

    1996-01-01

    Fuzzy controllers are usually looked at as crisp valued mappings especially when artificial intelligence learning techniques are used to build up the controller. By doing so the semantics of a fuzzy conclusion being a fuzzy restriction on the viable control actions is non-existing. In this paper the authors criticise from an approximation point of view using a fuzzy controller to express a crisp mapping does not seem the right way to go. Secondly it is illustrated that interesting information is contained in a fuzzy conclusion when indeed this conclusion is considered as a fuzzy restriction. This information turns out to be very valuable when viability problems are concerned, i.e. problems where the objective is to keep a system within predefined boundaries

  10. Fuzzy Logic Based Autonomous Parallel Parking System with Kalman Filtering

    Science.gov (United States)

    Panomruttanarug, Benjamas; Higuchi, Kohji

    This paper presents an emulation of fuzzy logic control schemes for an autonomous parallel parking system in a backward maneuver. There are four infrared sensors sending the distance data to a microcontroller for generating an obstacle-free parking path. Two of them mounted on the front and rear wheels on the parking side are used as the inputs to the fuzzy rules to calculate a proper steering angle while backing. The other two attached to the front and rear ends serve for avoiding collision with other cars along the parking space. At the end of parking processes, the vehicle will be in line with other parked cars and positioned in the middle of the free space. Fuzzy rules are designed based upon a wall following process. Performance of the infrared sensors is improved using Kalman filtering. The design method needs extra information from ultrasonic sensors. Starting from modeling the ultrasonic sensor in 1-D state space forms, one makes use of the infrared sensor as a measurement to update the predicted values. Experimental results demonstrate the effectiveness of sensor improvement.

  11. Path Planning for Unmanned Underwater Vehicle in 3D Space with Obstacles Using Spline-Imperialist Competitive Algorithm and Optimal Interval Type-2 Fuzzy Logic Controller

    Directory of Open Access Journals (Sweden)

    Ehsan Zakeri

    Full Text Available Abstract In this research, generation of a short and smooth path in three-dimensional space with obstacles for guiding an Unmanned Underwater Vehicle (UUV without collision is investigated. This is done by utilizing spline technique, in which the spline control points positions are determined by Imperialist Competitive Algorithm (ICA in three-dimensional space such that the shortest possible path from the starting point to the target point without colliding with obstacles is achieved. Furthermore, for guiding the UUV in the generated path, an Interval Type-2 Fuzzy Logic Controller (IT2FLC, the coefficients of which are optimized by considering an objective function that includes quadratic terms of the input forces and state error of the system, is used. Selecting such objective function reduces the control error and also the force applied to the UUV, which consequently leads to reduction of energy consumption. Therefore, by using a special method, desired signals of UUV state are obtained from generated three-dimensional optimal path such that tracking these signals by the controller leads to the tracking of this path by UUV. In this paper, the dynamical model of the UUV, entitled as "mUUV-WJ-1" , is derived and its hydrodynamic coefficients are calculated by CFD in order to be used in the simulations. For simulation by the method presented in this study, three environments with different obstacles are intended in order to check the performance of the IT2FLC controller in generating optimal paths for guiding the UUV. In this article, in addition to ICA, Particle Swarm Optimization (PSO and Artificial Bee Colony (ABC are also used for generation of the paths and the results are compared with each other. The results show the appropriate performance of ICA rather than ABC and PSO. Moreover, to evaluate the performance of the IT2FLC, optimal Type-1 Fuzzy Logic Controller (T1FLC and Proportional Integrator Differentiator (PID controller are designed

  12. Position controller for the arm of a neutron diffractometer using fuzzy logic; Controlador de posicion del brazo del difractometro de neutrones utilizando logica difusa

    Energy Technology Data Exchange (ETDEWEB)

    Ayala P, G F [Instituto Nacional de Investigaciones Nucleares, Mexico City (Mexico)

    1994-12-31

    The neutron diffractometer is an important instrument coupled to one of the radial outlets of the TRIGA-3-Salazar Reactor and is used mainly to analyze textures and crystal lattices. One of its main components is the velocity analysis goniometer which controls in a tangential way the movements of the sensor requiring for this a resolution of a hundredth of degree, but at the same time wide displacements are required. It is necessary to design and construct a system on the basis of a micro controller which control the long movements in a rapid way and with the needed accuracy. In this work, a proposition is presented: to replace the A.C. motor with a D.C. motor with a wide range of velocity and supplied with a card (DAC) to control the velocity by means of digital data. Moreover, a programmed micro controller with an algorithm based on fuzzy logic receiving data in BCD will be use. The use of micro controller will allow to set free the personal computer of the position of the goniometer; nevertheless, the system will report to the P C and its control program about the present position of the goniometer and the time when the desired position is reached. It is also consider that the user will be away from the system (a minimum of 15 meters) in order to avoid the zone with a high intensity of background radiation. (Author).

  13. Fuzzy Control of Robotic Arm

    Science.gov (United States)

    Lin, Kyaw Kyaw; Soe, Aung Kyaw; Thu, Theint Theint

    2008-10-01

    This research work investigates a Self-Tuning Proportional Derivative (PD) type Fuzzy Logic Controller (STPDFLC) for a two link robot system. The proposed scheme adjusts on-line the output Scaling Factor (SF) by fuzzy rules according to the current trend of the robot. The rule base for tuning the output scaling factor is defined on the error (e) and change in error (de). The scheme is also based on the fact that the controller always tries to manipulate the process input. The rules are in the familiar if-then format. All membership functions for controller inputs (e and de) and controller output (UN) are defined on the common interval [-1,1]; whereas the membership functions for the gain updating factor (α) is defined on [0,1]. There are various methods to calculate the crisp output of the system. Center of Gravity (COG) method is used in this application due to better results it gives. Performances of the proposed STPDFLC are compared with those of their corresponding PD-type conventional Fuzzy Logic Controller (PDFLC). The proposed scheme shows a remarkably improved performance over its conventional counterpart especially under parameters variation (payload). The two-link results of analysis are simulated. These simulation results are illustrated by using MATLAB® programming.

  14. System control fuzzy neural sewage pumping stations using genetic algorithms

    Directory of Open Access Journals (Sweden)

    Владлен Николаевич Кузнецов

    2015-06-01

    Full Text Available It is considered the system of management of sewage pumping station with regulators based on a neuron network with fuzzy logic. Linguistic rules for the controller based on fuzzy logic, maintaining the level of effluent in the receiving tank within the prescribed limits are developed. The use of genetic algorithms for neuron network training is shown.

  15. Three-Dimensional Crane Modelling and Control Using Euler-Lagrange State-Space Approach and Anti-Swing Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Aksjonov Andrei

    2015-12-01

    Full Text Available The mathematical model of the three-dimensional crane using the Euler-Lagrange approach is derived. A state-space representation of the derived model is proposed and explored in the Simulink® environment and on the laboratory stand. The obtained control design was simulated, analyzed and compared with existing encoder-based system provided by the three-dimensional (3D Crane manufacturer Inteco®. As well, an anti-swing fuzzy logic control has been developed, simulated, and analyzed. Obtained control algorithm is compared with the existing anti-swing proportional-integral controller designed by the 3D crane manufacturer Inteco®. 5-degree of freedom (5DOF control schemes are designed, examined and compared with the various load masses. The topicality of the problem is due to the wide usage of gantry cranes in industry. The solution is proposed for the future research in sensorless and intelligent control of complex motor driven application.

  16. Using an adaptive fuzzy-logic system to optimize the performances and the reduction of chattering phenomenon in the control of induction motor

    Directory of Open Access Journals (Sweden)

    Barazane Linda

    2009-01-01

    Full Text Available Neural networks and fuzzy inference systems are becoming well recognized tools of designing an identifier/controller capable of perceiving the operating environment and imitating a human operator with high performance. Also, by combining these two features, more versatile and robust models, called 'neuro-fuzzy' architectures have been developed. The motivation behind the use of neuro-fuzzy approaches is based on the complexity of real life systems, ambiguities on sensory information or time-varying nature of the system under investigation. In this way, the present contribution concerns the application of neuro-fuzzy approach in order to perform the responses of the speed regulation and to reduce the chattering phenomenon introduced by sliding mode control, which is very harmful to the actuators in our case and may excite the unmodeled dynamics of the system. The type of the neuro-fuzzy system used here is called:' adaptive neuro fuzzy inference controller (ANFIS'. This neuro-fuzzy is destined to replace the speed fuzzy sliding mode controller after its training process. Simulation results reveal some very interesting features. .

  17. A Fuzzy-Logic Generalization of a Data Mining Approach

    Czech Academy of Sciences Publication Activity Database

    Holeňa, Martin

    2001-01-01

    Roč. 11, č. 6 (2001), s. 595-610 ISSN 1210-0552. [SOFSEM 2001 Workshop on Soft Computing. Piešťany, 29.11.2001-30.11.2001] R&D Projects: GA AV ČR IAA1030004 Institutional research plan: AV0Z1030915 Keywords : data analysis * vague hypotheses * vague significante level * fuzzy prediacate calculus * basic fuzzy logic * generalized quantifiers * method GUHA Subject RIV: BA - General Mathematics

  18. Improving the performance of the Egyptian second testing nuclear research reactor using interval type-2 fuzzy logic controller tuned by modified biogeography-based optimization

    Energy Technology Data Exchange (ETDEWEB)

    Sayed, M.M., E-mail: M.M.Sayed@ieee.org; Saad, M.S.; Emara, H.M.; Abou El-Zahab, E.E.

    2013-09-15

    Highlights: • A modified version of the BBO was proposed. • A novel method for interval type-2 FLC design tuned by MBBO was proposed. • The performance of the ETRR-2 was improved by using IT2FLC tuned by MBBO. -- Abstract: Power stabilization is a critical issue in nuclear reactors. The conventional proportional derivative (PD) controller is currently used in the Egyptian second testing research reactor (ETRR-2). In this paper, we propose a modified biogeography-based optimization (MBBO) algorithm to design the interval type-2 fuzzy logic controller (IT2FLC) to improve the performance of the Egyptian second testing research reactor (ETRR-2). Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. A modified version of the BBO is applied to design the IT2FLC to get the optimal parameters of the membership functions of the controller. We test the optimal IT2FLC obtained by modified biogeography-based optimization (MBBO) using the integral square error (ISE) and is compared with the currently used PD controller.

  19. On Witnessed Models in Fuzzy Logic III - Witnessed Gödel Logics

    Czech Academy of Sciences Publication Activity Database

    Hájek, Petr

    2010-01-01

    Roč. 56, č. 2 (2010), s. 171-174 ISSN 0942-5616 R&D Projects: GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504 Keywords : mathematical fuzzy logic * Gödel logic * witnessed models * arithmetical complexity Subject RIV: BA - General Mathematics Impact factor: 0.361, year: 2010

  20. Towards rational closure for fuzzy logic: The case of propositional Godel logic

    CSIR Research Space (South Africa)

    Casini, G

    2013-12-01

    Full Text Available In the field of non-monotonic logics, the notion of rational closure is acknowledged as a landmark and we are going to see whether such a construction can be adopted in the context of mathematical fuzzy logic, a so far (apparently) unexplored...

  1. Application of fuzzy control in cooling systems save energy design

    Energy Technology Data Exchange (ETDEWEB)

    Chen, M.L.; Liang, H.Y. [Chienkuo Technology Univ., Changhua, Taiwan (China). Dept. of Electrical Engineering

    2005-07-01

    A fuzzy logic programmable logic controller (PLC) was used to control the cooling systems of frigorific equipment. Frigorific equipment is used to move unwanted heat outside of building in order to control indoor temperatures. The aim of the fuzzy logic PLC was to improve the energy efficiency of the cooling system. Control of the cooling pump and cooling tower in the system was based on the water temperature of the condenser during frigorific system operation. A human computer design for the cooling system control was used to set speeds and to automate and adjust the motor according to the fuzzy logic controller. It was concluded that if fuzzy logic controllers are used with all components of frigorific equipment, energy efficiency will be significantly increased. 5 refs., 3 tabs., 9 figs.

  2. Fuzzy Control Teaching Models

    Directory of Open Access Journals (Sweden)

    Klaus-Dietrich Kramer

    2016-05-01

    Full Text Available Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tune the system behavior. In order to support the development process a graphical user interface is needed to display the fuzzy terms under real time conditions, especially with a debug system and trace functionality. The experiences with such a programming tool, the Fuzzy Control Design Tool (FHFCE Tool, and four fuzzy teaching models will be presented in this paper. The methodical and didactical objective in the utilization of these teaching models is to develop solution strategies using Computational Intelligence (CI applications for Fuzzy Controllers in order to analyze different algorithms of inference or defuzzyfication and to verify and tune those systems efficiently.

  3. Complexity of Some Language Fragments of Fuzzy Logics

    Czech Academy of Sciences Publication Activity Database

    Haniková, Zuzana

    2017-01-01

    Roč. 21, č. 1 (2017), s. 69-77 ISSN 1432-7643 R&D Projects: GA ČR GAP202/11/1632 Institutional support: RVO:67985807 Keywords : fuzzy logic * propositional logic * language fragment * implicational fragment * commutative semigroup * equational theory * computational complexity Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.472, year: 2016

  4. A real time fuzzy logic power management strategy for a fuel cell vehicle

    International Nuclear Information System (INIS)

    Hemi, Hanane; Ghouili, Jamel; Cheriti, Ahmed

    2014-01-01

    Highlights: • We present a real time fuzzy logic power management strategy. • This strategy is applied to hybrid electric vehicle dynamic model. • Three configurations evaluated during a drive cycle. • The hydrogen consumption is analysed for the three configurations. - Abstract: This paper presents real time fuzzy logic controller (FLC) approach used to design a power management strategy for a hybrid electric vehicle and to protect the battery from overcharging during the repetitive braking energy accumulation. The fuel cell (FC) and battery (B)/supercapacitor (SC) are the primary and secondary power sources, respectively. This paper analyzes and evaluates the performance of the three configurations, FC/B, FC/SC and FC/B/SC during real time driving conditions and unknown driving cycle. The MATLAB/Simulink and SimPowerSystems software packages are used to model the electrical and mechanical elements of hybrid vehicles and implement a fuzzy logic strategy

  5. Construction of a fuzzy and all Boolean logic gates based on DNA

    DEFF Research Database (Denmark)

    M. Zadegan, Reza; Jepsen, Mette D E; Hildebrandt, Lasse

    2015-01-01

    to the operation of the six Boolean logic gates AND, NAND, OR, NOR, XOR, and XNOR. The logic gate complex is shown to work also when implemented in a three-dimensional DNA origami box structure, where it controlled the position of the lid in a closed or open position. Implementation of multiple microRNA sensitive...... DNA locks on one DNA origami box structure enabled fuzzy logical operation that allows biosensing of complex molecular signals. Integrating logic gates with DNA origami systems opens a vast avenue to applications in the fields of nanomedicine for diagnostics and therapeutics....

  6. Fuzzy Adaptation Algorithms’ Control for Robot Manipulators with Uncertainty Modelling Errors

    Directory of Open Access Journals (Sweden)

    Yongqing Fan

    2018-01-01

    Full Text Available A novel fuzzy control scheme with adaptation algorithms is developed for robot manipulators’ system. At the beginning, one adjustable parameter is introduced in the fuzzy logic system, the robot manipulators system with uncertain nonlinear terms as the master device and a reference model dynamic system as the slave robot system. To overcome the limitations such as online learning computation burden and logic structure in conventional fuzzy logic systems, a parameter should be used in fuzzy logic system, which composes fuzzy logic system with updated parameter laws, and can be formed for a new fashioned adaptation algorithms controller. The error closed-loop dynamical system can be stabilized based on Lyapunov analysis, the number of online learning computation burdens can be reduced greatly, and the different kinds of fuzzy logic systems with fuzzy rules or without any fuzzy rules are also suited. Finally, effectiveness of the proposed approach has been shown in simulation example.

  7. A practical introduction to fuzzy logic using LISP

    CERN Document Server

    Argüelles Mendez, Luis

    2016-01-01

    This book makes use of the LISP programming language to provide readers with the necessary background to understand and use fuzzy logic to solve simple to medium-complexity real-world problems. It introduces the basics of LISP required to use a Fuzzy LISP programming toolbox, which was specifically implemented by the author to “teach” the theory behind fuzzy logic and at the same time equip readers to use their newly-acquired knowledge to build fuzzy models of increasing complexity. The book fills an important gap in the literature, providing readers with a practice-oriented reference guide to fuzzy logic that offers more complexity than popular books yet is more accessible than other mathematical treatises on the topic. As such, students in first-year university courses with a basic tertiary mathematical background and no previous experience with programming should be able to easily follow the content. The book is intended for students and professionals in the fields of computer science and engineering, ...

  8. FUZZY SLIDING MODE CONTROLLER FOR DOUBLY FED ...

    African Journals Online (AJOL)

    2010-12-31

    Dec 31, 2010 ... against internal and external perturbations, but the FSMC is superior to ... controller, doubly fed induction motor, fuzzy logic control. 1. ... capabilities in accounting for modeling imprecision and bounded disturbances. It ..... To show the effect of the parameters uncertainties, we have simulated the system with.

  9. A Real-Time Simulink Interfaced Fast-Charging Methodology of Lithium-Ion Batteries under Temperature Feedback with Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    Muhammad Umair Ali

    2018-05-01

    Full Text Available The lithium-ion battery has high energy and power density, long life cycle, low toxicity, low discharge rate, more reliability, and better efficiency compared to other batteries. On the other hand, the issue of a reduction in charging time of the lithium-ion battery is still a bottleneck for the commercialization of electric vehicles (EVs. Therefore, an approach to charge lithium-ion batteries at a faster rate is needed. This paper proposes an efficient, real-time, fast-charging methodology of lithium-ion batteries. Fuzzy logic was adopted to drive the charging current trajectory. A temperature control unit was also implemented to evade the effects of fast charging on the aging mechanism. The proposed method of charging also protects the battery from overvoltage and overheating. Extensive testing and comprehensive analysis were conducted to examine the proposed charging technique. The results show that the proposed charging strategy favors a full battery recharging in 9.76% less time than the conventional constant-current–constant-voltage (CC/CV method. The strategy charges the battery at a 99.26% state of charge (SOC without significant degradation. The entire scheme was implemented in real time, using Arduino interfaced with MATLABTM Simulink. This decrease in charging time assists in the fast charging of cell phones and notebooks and in the large-scale deployment of EVs.

  10. A Fuzzy Control Course on the TED Server

    DEFF Research Database (Denmark)

    Dotoli, Mariagrazia; Jantzen, Jan

    1999-01-01

    , an educational server that serves as a learning central for students and professionals working with fuzzy logic. Through the server, TED offers an online course on fuzzy control. The course concerns automatic control of an inverted pendulum, with a focus on rule based control by means of fuzzy logic. A ball......The Training and Education Committee (TED) is a committee under ERUDIT, a Network of Excellence for fuzzy technology and uncertainty in Europe. The main objective of TED is to improve the training and educational possibilities for the nodes of ERUDIT. Since early 1999, TED has set up the TED server...

  11. Enhancing transparent fuzzy controllers through temporal concepts : an application to computer games

    NARCIS (Netherlands)

    Acampora, G.; Loia, V.; Vitiello, A.

    2010-01-01

    In the last years, FML (Fuzzy Markup Language) is emerging as one of the most efficient and useful language to define a fuzzy control thanks to its capability of modeling Fuzzy Logic Controllers in a human-readable and hardware independent way, i.e. the so-called Transparent Fuzzy Controllers

  12. Normal Forms for Fuzzy Logics: A Proof-Theoretic Approach

    Czech Academy of Sciences Publication Activity Database

    Cintula, Petr; Metcalfe, G.

    2007-01-01

    Roč. 46, č. 5-6 (2007), s. 347-363 ISSN 1432-0665 R&D Projects: GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10300504 Keywords : fuzzy logic * normal form * proof theory * hypersequents Subject RIV: BA - General Mathematics Impact factor: 0.620, year: 2007

  13. System for corrosion monitoring in pipeline applying fuzzy logic mathematics

    Science.gov (United States)

    Kuzyakov, O. N.; Kolosova, A. L.; Andreeva, M. A.

    2018-05-01

    A list of factors influencing corrosion rate on the external side of underground pipeline is determined. Principles of constructing a corrosion monitoring system are described; the system performance algorithm and program are elaborated. A comparative analysis of methods for calculating corrosion rate is undertaken. Fuzzy logic mathematics is applied to reduce calculations while considering a wider range of corrosion factors.

  14. modelling room cooling capacity with fuzzy logic procedure

    African Journals Online (AJOL)

    The primary aim of this study is to develop a model for estimation of the cooling requirement of residential rooms. Fuzzy logic was employed to model four input variables (window area (m2), roof area (m2), external wall area (m2) and internal load (Watt). The algorithm of the inference engine applied sets of 81 linguistic ...

  15. Application of ANN and fuzzy logic algorithms for streamflow ...

    Indian Academy of Sciences (India)

    The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years ...

  16. An Innovative Fuzzy-Logic-Based Methodology for Trend Identification

    International Nuclear Information System (INIS)

    Wang Xin; Tsoukalas, Lefteri H.; Wei, Thomas Y.C.; Reifman, Jaques

    2001-01-01

    A new fuzzy-logic-based methodology for on-line signal trend identification is introduced. The methodology may be used for detecting the onset of nuclear power plant (NPP) transients at the earliest possible time and could be of great benefit to diagnostic, maintenance, and performance-monitoring programs. Although signal trend identification is complicated by the presence of noise, fuzzy methods can help capture important features of on-line signals, integrate the information included in these features, and classify incoming NPP signals into increasing, decreasing, and steady-state trend categories. A computer program named PROTREN is developed and tested for the purpose of verifying this methodology using NPP and simulation data. The results indicate that the new fuzzy-logic-based methodology is capable of detecting transients accurately, it identifies trends reliably and does not misinterpret a steady-state signal as a transient one

  17. Study on Design of Control Module and Fuzzy Control System

    International Nuclear Information System (INIS)

    Lee, Chang Kyu; Sohn, Chang Ho; Kim, Jung Seon; Kim, Min Kyu

    2005-01-01

    Performance of control unit is improved by introduction of fuzzy control theory and compensation for input of control unit as FLC(Fuzzy Logic Controller). Here, FLC drives thermal control system by linguistic rule-base. Hence, In case of using compensative PID control unit, it doesn't need to revise or compensate for PID control unit. Consequently, this study shows proof that control system which implements H/W module and then uses fuzzy algorism in this system is stable and has reliable performance

  18. Fuzzy-Genetic Optimal Control for Four Degreeof Freedom Robotic Arm Movement

    OpenAIRE

    V. K. Banga; R. Kumar; Y. Singh

    2009-01-01

    In this paper, we present optimal control for movement and trajectory planning for four degrees-of-freedom robot using Fuzzy Logic (FL) and Genetic Algorithms (GAs). We have evaluated using Fuzzy Logic (FL) and Genetic Algorithms (GAs) for four degree-of-freedom (4 DOF) robotics arm, Uncertainties like; Movement, Friction and Settling Time in robotic arm movement have been compensated using Fuzzy logic and Genetic Algorithms. The development of a fuzzy genetic optimizatio...

  19. Stock and option portfolio using fuzzy logic approach

    Science.gov (United States)

    Sumarti, Novriana; Wahyudi, Nanang

    2014-03-01

    Fuzzy Logic in decision-making process has been widely implemented in various problems in industries. It is the theory of imprecision and uncertainty that was not based on probability theory. Fuzzy Logic adds values of degree between absolute true and absolute false. It starts with and builds on a set of human language rules supplied by the user. The fuzzy systems convert these rules to their mathematical equivalents. This could simplify the job of the system designer and the computer, and results in much more accurate representations of the way systems behave in the real world. In this paper we examine the decision making process of stock and option trading by the usage of MACD (Moving Average Convergence Divergence) technical analysis and Option Pricing with Fuzzy Logic approach. MACD technical analysis is for the prediction of the trends of underlying stock prices, such as bearish (going downward), bullish (going upward), and sideways. By using Fuzzy C-Means technique and Mamdani Fuzzy Inference System, we define the decision output where the value of MACD is high then decision is "Strong Sell", and the value of MACD is Low then the decision is "Strong Buy". We also implement the fuzzification of the Black-Scholes option-pricing formula. The stock and options methods are implemented on a portfolio of one stock and its options. Even though the values of input data, such as interest rates, stock price and its volatility, cannot be obtain accurately, these fuzzy methods can give a belief degree of the calculated the Black-Scholes formula so we can make the decision on option trading. The results show the good capability of the methods in the prediction of stock price trends. The performance of the simulated portfolio for a particular period of time also shows good return.

  20. Consumer Behavior Modeling: Fuzzy Logic Model for Air Purifiers Choosing

    Directory of Open Access Journals (Sweden)

    Oleksandr Dorokhov

    2017-12-01

    Full Text Available At the beginning, the article briefly describes the features of the marketing complex household goods. Also provides an overview of some aspects of the market for indoor air purifiers. The specific subject of the study was the process of consumer choice of household appliances for cleaning air in living quarters. The aim of the study was to substantiate and develop a computer model for evaluating by the potential buyers devices for air purification in conditions of vagueness and ambiguity of their consumer preferences. Accordingly, the main consumer criteria are identified, substantiated and described when buyers choose air purifiers. As methods of research, approaches based on fuzzy logic, fuzzy sets theory and fuzzy modeling were chosen. It was hypothesized that the fuzzy-multiple model allows rather accurately reflect consumer preferences and potential consumer choice in conditions of insufficient and undetermined information. Further, a computer model for estimating the consumer qualities of air cleaners by customers is developed. A proposed approach based on the application of fuzzy logic theory and practical modeling in the specialized computer software MATLAB. In this model, the necessary membership functions and their terms are constructed, as well as a set of rules for fuzzy inference to make decisions on the estimation of a specific air purifier. A numerical example of a comparative evaluation of air cleaners presented on the Ukrainian market is made and is given. Numerical simulation results confirmed the applicability of the proposed approach and the correctness of the hypothesis advanced about the possibility of modeling consumer behavior using fuzzy logic. The analysis of the obtained results is carried out and the prospects of application, development, and improvement of the developed model and the proposed approach are determined.

  1. Process optimization of citric acid production from aspergillus niger using fuzzy logic design

    International Nuclear Information System (INIS)

    Ali, S.; Haq, I.U.

    2014-01-01

    The inherent non-linearity of citric acid fermentation from Aspergillus niger renders its control difficult, so there is a need to fine-tune the bioreactor performance for maximum production of citric acid in batch culture. For this, fuzzy logic is becoming a popular tool to handle non-linearity of a batch process. The present manuscript deals with fuzzy logic control of citric acid accretion by A. niger in a stirred tank reactor using blackstrap sugarcane molasses as a basal fermentation medium. The customary batches were termed as 'control' while those under fuzzy logic were 'experimental'. The performance of fuzzy logic control of stirred tank reactor was found to be very encouraging for enhanced production of citric acid. The comparison of kinetic parameters showed improved citrate synthase ability of experimental culture (Yp/x = 7.042 g/g). When the culture grown on 150 g/l carbohydrates was monitored for Qp, Qs and Yp/s, there was significant enhancement in these variables over the control. Specific productivity of culture (qp = 0.070 g/g cells/h) was several fold increased. The enthalpy (HD = 70.5 kJ/mol) and entropy of activation (S = -144 J/mol/K) of enzyme for citric acid biosynthesis, free energies for transition state formation and substrate binding for sucrose hydrolysis of experimental were substantially improved. (author)

  2. Development of a fuzzy logic method to build objective functions in optimization problems: application to BWR fuel lattice design

    International Nuclear Information System (INIS)

    Martin-del-Campo, C.; Francois, J.L.; Barragan, A.M.; Palomera, M.A.

    2005-01-01

    In this paper we develop a methodology based on the use of the Fuzzy Logic technique to build multi-objective functions to be used in optimization processes applied to in-core nuclear fuel management. As an example, we selected the problem of determining optimal radial fuel enrichment and gadolinia distributions in a typical 'Boiling Water Reactor (BWR)' fuel lattice. The methodology is based on the use of the mathematical capability of Fuzzy Logic to model nonlinear functions of arbitrary complexity. The utility of Fuzzy Logic is to map an input space into an output space, and the primary mechanism for doing this is a list of if-then statements called rules. The rules refer to variables and adjectives that describe those variables and, the Fuzzy Logic technique interprets the values in the input vectors and, based on the set of rules assigns values to the output vector. The methodology was developed for the radial optimization of a BWR lattice where the optimization algorithm employed is Tabu Search. The global objective is to find the optimal distribution of enrichments and burnable poison concentrations in a 10*10 BWR lattice. In order to do that, a fuzzy control inference system was developed using the Fuzzy Logic Toolbox of Matlab and it has been linked to the Tabu Search optimization process. Results show that Tabu Search combined with Fuzzy Logic performs very well, obtaining lattices with optimal fuel utilization. (authors)

  3. Fuzzy logic: A “simple” solution for complexities in neurosciences?

    Science.gov (United States)

    Godil, Saniya Siraj; Shamim, Muhammad Shahzad; Enam, Syed Ather; Qidwai, Uvais

    2011-01-01

    Background: Fuzzy logic is a multi-valued logic which is similar to human thinking and interpretation. It has the potential of combining human heuristics into computer-assisted decision making, which is applicable to individual patients as it takes into account all the factors and complexities of individuals. Fuzzy logic has been applied in all disciplines of medicine in some form and recently its applicability in neurosciences has also gained momentum. Methods: This review focuses on the use of this concept in various branches of neurosciences including basic neuroscience, neurology, neurosurgery, psychiatry and psychology. Results: The applicability of fuzzy logic is not limited to research related to neuroanatomy, imaging nerve fibers and understanding neurophysiology, but it is also a sensitive and specific tool for interpretation of EEGs, EMGs and MRIs and an effective controller device in intensive care units. It has been used for risk stratification of stroke, diagnosis of different psychiatric illnesses and even planning neurosurgical procedures. Conclusions: In the future, fuzzy logic has the potential of becoming the basis of all clinical decision making and our understanding of neurosciences. PMID:21541006

  4. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  5. Modelling for Temperature Non-Isothermal Continuous Stirred Tank Reactor Using Fuzzy Logic

    OpenAIRE

    Nasser Mohamed Ramli; Mohamad Syafiq Mohamad

    2017-01-01

    Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of...

  6. LA LÓGICA DIFUSA COMPENSATORIA / THE COMPENSATORY FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Jesús Cejas-Montero

    2011-06-01

    Full Text Available

    La Lógica Difusa Compensatoria es un modelo lógico que permite la modelación simultánea de los procesos deductivos y de toma de decisiones. Sus características más importantes son: la flexibilidad, la tolerancia con la imprecisión, la capacidad para moldear problemas no-lineales y su fundamento en el lenguaje de sentido común. El artículo pretende llevar a la comunidad académico-empresarial las ideas fundamentales de la Lógica Difusa Compensatoria, ilustrándola en sus posibles campos de aplicación para lograr la competitividad de una organización.

    Abstract

    The Compensatory Fuzzy Logic is a logical model that allows the simultaneous modeling of the deductive and decision-making processes. The most important characteristics of Compensatory Fuzzy Logic are: the flexibility, the tolerance with the inaccuracy, the capacity to model no-lineal problems and its foundation in the language of common sense. The article seeks to bring the basic ideas of the Compensatory Fuzzy Logic to the academic–managerial community, illustrating it in its possible fields of application, in order to achieve the competitiveness of an organization.

  7. Edge detection methods based on generalized type-2 fuzzy logic

    CERN Document Server

    Gonzalez, Claudia I; Castro, Juan R; Castillo, Oscar

    2017-01-01

    In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gra-dient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel operator; in the third approach the me-thodology based on Sobel operator and GT2 FSs is improved to be applied on color images. In the fourth approach, we proposed a novel edge detec-tion method where, a digital image is converted a generalized type-2 fuzzy image. In this book it is also included a comparative study of type-1, inter-val type-2 and generalized type-2 fuzzy systems as tools to enhance edge detection in digital images when used in conjunction with the morphologi-cal gradient and the Sobel operator. The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format. Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preproc...

  8. Robust Fuzzy Controllers Using FPGAs

    Science.gov (United States)

    Monroe, Author Gene S., Jr.

    2007-01-01

    Electro-mechanical device controllers typically come in one of three forms, proportional (P), Proportional Derivative (PD), and Proportional Integral Derivative (PID). Two methods of control are discussed in this paper; they are (1) the classical technique that requires an in-depth mathematical use of poles and zeros, and (2) the fuzzy logic (FL) technique that is similar to the way humans think and make decisions. FL controllers are used in multiple industries; examples include control engineering, computer vision, pattern recognition, statistics, and data analysis. Presented is a study on the development of a PD motor controller written in very high speed hardware description language (VHDL), and implemented in FL. Four distinct abstractions compose the FL controller, they are the fuzzifier, the rule-base, the fuzzy inference system (FIS), and the defuzzifier. FL is similar to, but different from, Boolean logic; where the output value may be equal to 0 or 1, but it could also be equal to any decimal value between them. This controller is unique because of its VHDL implementation, which uses integer mathematics. To compensate for VHDL's inability to synthesis floating point numbers, a scale factor equal to 10(sup (N/4) is utilized; where N is equal to data word size. The scaling factor shifts the decimal digits to the left of the decimal point for increased precision. PD controllers are ideal for use with servo motors, where position control is effective. This paper discusses control methods for motion-base platforms where a constant velocity equivalent to a spectral resolution of 0.25 cm(exp -1) is required; however, the control capability of this controller extends to various other platforms.

  9. Mapping Shape Geometry And Emotions Using Fuzzy Logic

    DEFF Research Database (Denmark)

    Achiche, Sofiane; Ahmed, Saeema

    2008-01-01

    An important aspect of artifact/product design is defining the aesthetic and emotional value. The success of a product is not only dependent on its functionality but also on the emotional value that it creates to its user. However, if several designers are faced with a task to create an object...... that would evoke a certain emotion (aggressive, soft, heavy, friendly, etc.), each would most likely interpret the emotion with a different set of geometric features and shapes. In this paper the authors propose an approach to formalize the relationship between geometric information of a 3D object...... 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...

  10. Risk evaluation in Columbian electricity market using fuzzy logic

    International Nuclear Information System (INIS)

    Medina, S.; Moreno, J.

    2007-01-01

    This article proposes a model based on Fuzzy Logic to evaluate the market risk that a trading agent faces in the electric power negotiation in Colombia, as part of a general model of negotiation. The proposed model considers single external factors as regulatory changes, social and political issues, and the condition of the national transmission net. Variables of the market associated to these risk factors were selected and some graphic and statistical analyses were made in order to check their relationship with the electricity prices and to determine why the experts consider these factors in their analyses. According to the obtained results a Mamdani Fuzzy Inference System which contains the expert knowledge was developed and it is presented in a fuzzy cognitive map. (author)

  11. Use of Fuzzy Logic Systems for Assessment of Primary Faults

    Science.gov (United States)

    Petrović, Ivica; Jozsa, Lajos; Baus, Zoran

    2015-09-01

    In electric power systems, grid elements are often subjected to very complex and demanding disturbances or dangerous operating conditions. Determining initial fault or cause of those states is a difficult task. When fault occurs, often it is an imperative to disconnect affected grid element from the grid. This paper contains an overview of possibilities for using fuzzy logic in an assessment of primary faults in the transmission grid. The tool for this task is SCADA system, which is based on information of currents, voltages, events of protection devices and status of circuit breakers in the grid. The function model described with the membership function and fuzzy logic systems will be presented in the paper. For input data, diagnostics system uses information of protection devices tripping, states of circuit breakers and measurements of currents and voltages before and after faults.

  12. IDENTIFIKASI SINYAL ECG IRAMA MYOCARDIAL ISCHEMIA DENGAN PENDEKATAN FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Azhar A N

    2009-07-01

    Full Text Available The heart is one of vital organs in human body. Incidence of heart disease can be fatal for the patient. Myocardial ischemia, the disease that is often suffered by the human, is a disease due to clogged heart arteries blood vessels. One of the ways to detect this disease is by reading the graph output of electrocardiogram (ECG signal. ECG signal represents the condition and activity of the heart. Specialized knowledge, accuration and expertise are required to read ECG graph. To help expert or doctor, expert system based on artificial intelligent, such as Fuzzy Logic approach, can be applied to improve diagnostic accuracy and thoroughness. Fuzzy logic can be applied because of it flexibility to understand the linguistic variables used in identifying myocardial ischemia disease.

  13. Classification of Children Intelligence with Fuzzy Logic Method

    Science.gov (United States)

    Syahminan; ika Hidayati, Permata

    2018-04-01

    Intelligence of children s An Important Thing To Know The Parents Early on. Typing Can be done With a Child’s intelligence Grouping Dominant Characteristics Of each Type of Intelligence. To Make it easier for Parents in Determining The type of Children’s intelligence And How to Overcome them, for It Created A Classification System Intelligence Grouping Children By Using Fuzzy logic method For determination Of a Child’s degree of intelligence type. From the analysis We concluded that The presence of Intelligence Classification systems Pendulum Children With Fuzzy Logic Method Of determining The type of The Child’s intelligence Can be Done in a way That is easier And The results More accurate Conclusions Than Manual tests.

  14. Monitoring nuclear reactor systems using neural networks and fuzzy logic

    International Nuclear Information System (INIS)

    Ikonomopoulos, A.; Tsoukalas, L.H.; Uhrig, R.E.; Mullens, J.A.

    1991-01-01

    A new approach is presented that demonstrates the potential of trained artificial neural networks (ANNs) as generators of membership functions for the purpose of monitoring nuclear reactor systems. ANN's provide a complex-to-simple mapping of reactor parameters in a process analogous to that of measurement. Through such ''virtual measurements'' the value of parameters with operational significance, e.g., control-valve-disk-position, valve-line-up or performance can be determined. In the methodology presented the output of a virtual measuring device is a set of membership functions which independently represent different states of the system. Utilizing a fuzzy logic representation offers the advantage of describing the state of the system in a condensed form, developed through linguistic descriptions and convenient for application in monitoring, diagnostics and generally control algorithms. The developed methodology is applied to the problem of measuring the disk position of the secondary flow control valve of an experimental reactor using data obtained during a start-up. The enhanced noise tolerance of the methodology is clearly demonstrated as well as a method for selecting the actual output. The results suggest that it is possible to construct virtual measuring devices through artificial neural networks mapping dynamic time series to a set of membership functions and thus enhance the capability of monitoring systems. 8 refs., 11 figs., 1 tab

  15. Monitoring nuclear reactor systems using neural networks and fuzzy logic

    International Nuclear Information System (INIS)

    Ikonomopoulos, A.; Tsoukalas, L.H.; Uhrig, R.E.; Mullens, J.A.

    1992-01-01

    A new approach is presented that demonstrates the potential of trained artificial neural networks (ANNs) as generators of membership functions for the purpose of monitoring nuclear reactor systems. ANN's provide a complex-to-simple mapping of reactor parameters in a process analogous to that of measurement. Through such virtual measurements the value of parameters with operational significance, e.g., control-valve-disk-position, valve-line-up-or performance can be determined. In the methodology presented the output of virtual measuring device is a set of membership functions which independently represent different states of the system. Utilizing a fuzzy logic representation offers the advantage of describing the state of the system in a condensed form, developed through linguistic descriptions and convenient for application in monitoring, diagnostics and generally control algorithms. The developed methodology is applied to the problem of measuring the disk position of the secondary flow control is clearly demonstrated as well as a method for selecting the actual output. The results suggest that it is possible to construct virtual measuring devices through artificial neural networks mapping dynamic time series to a set of membership functions and thus enhance the capability of monitoring systems

  16. A Fuzzy Logic System to Analyze a Student's Lifestyle

    OpenAIRE

    Ghosh, Sourish; Boob, Aaditya Sanjay; Nikhil, Nishant; Vysyaraju, Nayan Raju; Kumar, Ankit

    2016-01-01

    A college student's life can be primarily categorized into domains such as education, health, social and other activities which may include daily chores and travelling time. Time management is crucial for every student. A self realisation of one's daily time expenditure in various domains is therefore essential to maximize one's effective output. This paper presents how a mobile application using Fuzzy Logic and Global Positioning System (GPS) analyzes a student's lifestyle and provides recom...

  17. Optimization of heat pump using fuzzy logic and genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Sahin, Arzu Sencan [Sueleyman Demirel University, Technology Faculty, Isparta (Turkey); Kilic, Bayram; Kilic, Ulas [Bucak Emin Guelmez Vocational School, Mehmet Akif Ersoy University, Bucak (Turkey)

    2011-12-15

    Heat pumps offer economical alternatives of recovering heat from different sources for use in various industrial, commercial and residential applications. In this study, single-stage air-source vapor compression heat pump system has been optimized using genetic algorithm (GA) and fuzzy logic (FL). The necessary thermodynamic properties for optimization were calculated by FL. Thermodynamic properties obtained with FL were compared with actual results. Then, the optimum working conditions of heat pump system were determined by the GA. (orig.)

  18. Implement Fuzzy Logic to Optimize Electronic Business Success

    OpenAIRE

    Fahim Akhter

    2016-01-01

    Customers are realizing the importance and benefits of shopping online such as convenience, comparison, product research, larger selection, and lower prices. The dynamic nature of e-commerce evokes online businesses to make alterations in their business processes and decisions making to satisfy customers’ needs. Online businesses are adopting Business Intelligence (BI) tools and systems with the collaboration of fuzzy logic system to forecast the future of the e-commerce. With the aid of BI, ...

  19. A New Fuzzy Harmony Search Algorithm Using Fuzzy Logic for Dynamic Parameter Adaptation

    Directory of Open Access Journals (Sweden)

    Cinthia Peraza

    2016-10-01

    Full Text Available In this paper, a new fuzzy harmony search algorithm (FHS for solving optimization problems is presented. FHS is based on a recent method using fuzzy logic for dynamic adaptation of the harmony memory accepting (HMR and pitch adjustment (PArate parameters that improve the convergence rate of traditional harmony search algorithm (HS. The objective of the method is to dynamically adjust the parameters in the range from 0.7 to 1. The impact of using fixed parameters in the harmony search algorithm is discussed and a strategy for efficiently tuning these parameters using fuzzy logic is presented. The FHS algorithm was successfully applied to different benchmarking optimization problems. The results of simulation and comparison studies demonstrate the effectiveness and efficiency of the proposed approach.

  20. Model Reduction of Fuzzy Logic Systems

    Directory of Open Access Journals (Sweden)

    Zhandong Yu

    2014-01-01

    Full Text Available This paper deals with the problem of ℒ2-ℒ∞ model reduction for continuous-time nonlinear uncertain systems. The approach of the construction of a reduced-order model is presented for high-order nonlinear uncertain systems described by the T-S fuzzy systems, which not only approximates the original high-order system well with an ℒ2-ℒ∞ error performance level γ but also translates it into a linear lower-dimensional system. Then, the model approximation is converted into a convex optimization problem by using a linearization procedure. Finally, a numerical example is presented to show the effectiveness of the proposed method.

  1. Analysis of Learning Development With Sugeno Fuzzy Logic And Clustering

    Directory of Open Access Journals (Sweden)

    Maulana Erwin Saputra

    2017-06-01

    Full Text Available In the first journal, I made this attempt to analyze things that affect the achievement of students in each school of course vary. Because students are one of the goals of achieving the goals of successful educational organizations. The mental influence of students’ emotions and behaviors themselves in relation to learning performance. Fuzzy logic can be used in various fields as well as Clustering for grouping, as in Learning Development analyzes. The process will be performed on students based on the symptoms that exist. In this research will use fuzzy logic and clustering. Fuzzy is an uncertain logic but its excess is capable in the process of language reasoning so that in its design is not required complicated mathematical equations. However Clustering method is K-Means method is method where data analysis is broken down by group k (k = 1,2,3, .. k. To know the optimal number of Performance group. The results of the research is with a questionnaire entered into matlab will produce a value that means in generating the graph. And simplify the school in seeing Student performance in the learning process by using certain criteria. So from the system that obtained the results for a decision-making required by the school.

  2. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Directory of Open Access Journals (Sweden)

    Minh Vu Trieu

    2017-03-01

    Full Text Available This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS, Brazilian tensile strength (BTS, rock brittleness index (BI, the distance between planes of weakness (DPW, and the alpha angle (Alpha between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP. Four (4 statistical regression models (two linear and two nonlinear are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2 of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  3. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Science.gov (United States)

    Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

    2017-03-01

    This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  4. Using Fuzzy Logic to Increase the Accuracy of E-Commerce Risk Assessment Based on an Expert System

    Directory of Open Access Journals (Sweden)

    H. Beheshti

    2017-12-01

    Full Text Available Strong adaptive control can be exercised even without access to accurate data inputs. Such control is possible through fuzzy mathematics, which is a meta-collection of Boolean logic principles that imply relative accuracy. Fuzzy mathematics find applications in e-commerce, where different risk analysis methods are available for risk assessment and estimation. Such approaches can be quantitative or qualitative, depending on the type of examined data. Quantitative methods are grounded in statistics, whereas qualitative methods are based on expert judgments and fuzzy set theory. Given that qualitative methods are very subjective and deal with vague or inaccurate data, fuzzy logic can be used to extract useful information from data inaccuracies. In this study, a model based on the opinions of e-commerce security experts was designed and implemented by using fuzzy expert systems and MATLAB. A case study was conducted to validate the effectiveness of the Model.

  5. Fuzzy-logic based learning style prediction in e-learning using web ...

    Indian Academy of Sciences (India)

    tion, especially in web environments and proposes to use Fuzzy rules to handle the uncertainty in .... learning in safe and supportive environment ... working of the proposed Fuzzy-logic based learning style prediction in e-learning. Section 4.

  6. An Extension of the Fuzzy Possibilistic Clustering Algorithm Using Type-2 Fuzzy Logic Techniques

    Directory of Open Access Journals (Sweden)

    Elid Rubio

    2017-01-01

    Full Text Available In this work an extension of the Fuzzy Possibilistic C-Means (FPCM algorithm using Type-2 Fuzzy Logic Techniques is presented, and this is done in order to improve the efficiency of FPCM algorithm. With the purpose of observing the performance of the proposal against the Interval Type-2 Fuzzy C-Means algorithm, several experiments were made using both algorithms with well-known datasets, such as Wine, WDBC, Iris Flower, Ionosphere, Abalone, and Cover type. In addition some experiments were performed using another set of test images to observe the behavior of both of the above-mentioned algorithms in image preprocessing. Some comparisons are performed between the proposed algorithm and the Interval Type-2 Fuzzy C-Means (IT2FCM algorithm to observe if the proposed approach has better performance than this algorithm.

  7. Challenges And Results of the Applications of Fuzzy Logic in the Classification of Rich Galaxy Clusters

    Science.gov (United States)

    Girola Schneider, R.

    2017-07-01

    The fuzzy logic is a branch of the artificial intelligence founded on the concept that everything is a matter of degree. It intends to create mathematical approximations on the resolution of certain types of problems. In addition, it aims to produce exact results obtained from imprecise data, for which it is particularly useful for electronic and computer applications. This enables it to handle vague or unspecific information when certain parts of a system are unknown or ambiguous and, therefore, they cannot be measured in a reliable manner. Also, when the variation of a variable can produce an alteration on the others The main focus of this paper is to prove the importance of these techniques formulated from a theoretical analysis on its application on ambiguous situations in the field of the rich clusters of galaxies. The purpose is to show its applicability in the several classification systems proposed for the rich clusters, which are based on criteria such as the level of richness of the cluster, the distribution of the brightest galaxies, whether there are signs of type-cD galaxies or not or the existence of sub-clusters. Fuzzy logic enables the researcher to work with "imprecise" information implementing fuzzy sets and combining rules to define actions. The control systems based on fuzzy logic join input variables that are defined in terms of fuzzy sets through rule groups that produce one or several output values of the system under study. From this context, the application of the fuzzy logic's techniques approximates the solution of the mathematical models in abstractions about the rich galaxy cluster classification of physical properties in order to solve the obscurities that must be confronted by an investigation group in order to make a decision.

  8. On fuzzy control of water desalination plants

    Energy Technology Data Exchange (ETDEWEB)

    Titli, A. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Jamshidi, M. [New Mexico Univ., Albuquerque, NM (United States); Olafsson, F. [Institute of Technology, Norway (Norway)

    1995-12-31

    In this report we have chosen a sub-system of an MSF water desalination plant, the brine heater, for analysis, synthesis, and simulation. This system has been modelled and implemented on computer. A fuzzy logic controller (FLC) for the top brine temperature control loop has been designed and implemented on the computer. The performance of the proposed FLC is compared with three other conventional control strategies: PID, cascade and disturbance rejection control. One major concern on FLC`s has been the lack of stability criteria. An up to-date survey of stability of fuzzy control systems is given. We have shown stability of the proposed FLC using the Sinusoidal Input Describing Functions (SIDF) method. The potential applications of fuzzy controllers for complex and large-scale systems through hierarchy of rule sets and hybridization with conventional approaches are also investigated. (authors)

  9. On fuzzy control of water desalination plants

    Energy Technology Data Exchange (ETDEWEB)

    Titli, A [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Jamshidi, M [New Mexico Univ., Albuquerque, NM (United States); Olafsson, F [Institute of Technology, Norway (Norway)

    1996-12-31

    In this report we have chosen a sub-system of an MSF water desalination plant, the brine heater, for analysis, synthesis, and simulation. This system has been modelled and implemented on computer. A fuzzy logic controller (FLC) for the top brine temperature control loop has been designed and implemented on the computer. The performance of the proposed FLC is compared with three other conventional control strategies: PID, cascade and disturbance rejection control. One major concern on FLC`s has been the lack of stability criteria. An up to-date survey of stability of fuzzy control systems is given. We have shown stability of the proposed FLC using the Sinusoidal Input Describing Functions (SIDF) method. The potential applications of fuzzy controllers for complex and large-scale systems through hierarchy of rule sets and hybridization with conventional approaches are also investigated. (authors)

  10. The foundations of fuzzy control

    CERN Document Server

    Lewis, Harold W

    1997-01-01

    Harold Lewis applied a cross-disciplinary approach in his highly accessible discussion of fuzzy control concepts. With the aid of fifty-seven illustrations, he thoroughly presents a unique mathematical formalism to explain the workings of the fuzzy inference engine and a novel test plant used in the research. Additionally, the text posits a new viewpoint on why fuzzy control is more popular in some countries than in others. A direct and original view of Japanese thinking on fuzzy control methods, based on the author's personal knowledge of - and association with - Japanese fuzzy research, is also included.

  11. Research on fault diagnosis of nuclear power plants based on genetic algorithms and fuzzy logic

    International Nuclear Information System (INIS)

    Zhou Yangping; Zhao Bingquan

    2001-01-01

    Based on genetic algorithms and fuzzy logic and using expert knowledge, mini-knowledge tree model and standard signals from simulator, a new fuzzy-genetic method is developed to fault diagnosis in nuclear power plants. A new replacement method of genetic algorithms is adopted. Fuzzy logic is used to calculate the fitness of the strings in genetic algorithms. Experiments on the simulator show it can deal with the uncertainty and the fuzzy factor

  12. Computational intelligence synergies of fuzzy logic, neural networks and evolutionary computing

    CERN Document Server

    Siddique, Nazmul

    2013-01-01

    Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: Covers all the aspect

  13. Self tuning fuzzy PID type load and frequency controller

    International Nuclear Information System (INIS)

    Yesil, E.; Guezelkaya, M.; Eksin, I.

    2004-01-01

    In this paper, a self tuning fuzzy PID type controller is proposed for solving the load frequency control (LFC) problem. The fuzzy PID type controller is constructed as a set of control rules, and the control signal is directly deduced from the knowledge base and the fuzzy inference. Moreover, there exists a self tuning mechanism that adjusts the input scaling factor corresponding to the derivative coefficient and the output scaling factor corresponding to the integral coefficient of the PID type fuzzy logic controller in an on-line manner. The self tuning mechanism depends on the peak observer idea, and this idea is modified and adapted to the LFC problem. A two area interconnected system is assumed for demonstrations. The proposed self tuning fuzzy PID type controller has been compared with the fuzzy PID type controller without a self tuning mechanism and the conventional integral controller through some performance indices

  14. Fuzzy knowledge base construction through belief networks based on Lukasiewicz logic

    Science.gov (United States)

    Lara-Rosano, Felipe

    1992-01-01

    In this paper, a procedure is proposed to build a fuzzy knowledge base founded on fuzzy belief networks and Lukasiewicz logic. Fuzzy procedures are developed to do the following: to assess the belief values of a consequent, in terms of the belief values of its logical antecedents and the belief value of the corresponding logical function; and to update belief values when new evidence is available.

  15. Comparison of fuzzy logic and neural network in maximum power point tracker for PV systems

    Energy Technology Data Exchange (ETDEWEB)

    Ben Salah, Chokri; Ouali, Mohamed [Research Unit on Intelligent Control, Optimization, Design and Optimization of Complex Systems (ICOS), Department of Electrical Engineering, National School of Engineers of Sfax, BP. W, 3038, Sfax (Tunisia)

    2011-01-15

    This paper proposes two methods of maximum power point tracking using a fuzzy logic and a neural network controllers for photovoltaic systems. The two maximum power point tracking controllers receive solar radiation and photovoltaic cell temperature as inputs, and estimated the optimum duty cycle corresponding to maximum power as output. The approach is validated on a 100 Wp PVP (two parallels SM50-H panel) connected to a 24 V dc load. The new method gives a good maximum power operation of any photovoltaic array under different conditions such as changing solar radiation and PV cell temperature. From the simulation and experimental results, the fuzzy logic controller can deliver more power than the neural network controller and can give more power than other different methods in literature. (author)

  16. Fuzzy control. Fundamentals, stability and design of fuzzy controllers

    Energy Technology Data Exchange (ETDEWEB)

    Michels, K. [Fichtner GmbH und Co. KG, Stuttgart (Germany); Klawonn, F. [Fachhochschule Braunschweig/Wolfenbuettel (Germany). Fachbereich Informatik; Kruse, R. [Magdeburg Univ. (Germany). Fakultaet Informatik, Abt. Wiss.- und Sprachverarbeitung; Nuernberger, A. (eds.) [California Univ., Berkeley, CA (United States). Computer Science Division

    2006-07-01

    The book provides a critical discussion of fuzzy controllers from the perspective of classical control theory. Special emphases are placed on topics that are of importance for industrial applications, like (self-) tuning of fuzzy controllers, optimisation and stability analysis. The book is written as a textbook for graduate students as well as a comprehensive reference book about fuzzy control for researchers and application engineers. Starting with a detailed introduction to fuzzy systems and control theory the reader is guided to up-to-date research results. (orig.)

  17. Noise-based logic: Binary, multi-valued, or fuzzy, with optional superposition of logic states

    Energy Technology Data Exchange (ETDEWEB)

    Kish, Laszlo B. [Texas A and M University, Department of Electrical and Computer Engineering, College Station, TX 77843-3128 (United States)], E-mail: laszlo.kish@ece.tamu.edu

    2009-03-02

    A new type of deterministic (non-probabilistic) computer logic system inspired by the stochasticity of brain signals is shown. The distinct values are represented by independent stochastic processes: independent voltage (or current) noises. The orthogonality of these processes provides a natural way to construct binary or multi-valued logic circuitry with arbitrary number N of logic values by using analog circuitry. Moreover, the logic values on a single wire can be made a (weighted) superposition of the N distinct logic values. Fuzzy logic is also naturally represented by a two-component superposition within the binary case (N=2). Error propagation and accumulation are suppressed. Other relevant advantages are reduced energy dissipation and leakage current problems, and robustness against circuit noise and background noises such as 1/f, Johnson, shot and crosstalk noise. Variability problems are also non-existent because the logic value is an AC signal. A similar logic system can be built with orthogonal sinusoidal signals (different frequency or orthogonal phase) however that has an extra 1/N type slowdown compared to the noise-based logic system with increasing number of N furthermore it is less robust against time delay effects than the noise-based counterpart.

  18. Noise-based logic: Binary, multi-valued, or fuzzy, with optional superposition of logic states

    International Nuclear Information System (INIS)

    Kish, Laszlo B.

    2009-01-01

    A new type of deterministic (non-probabilistic) computer logic system inspired by the stochasticity of brain signals is shown. The distinct values are represented by independent stochastic processes: independent voltage (or current) noises. The orthogonality of these processes provides a natural way to construct binary or multi-valued logic circuitry with arbitrary number N of logic values by using analog circuitry. Moreover, the logic values on a single wire can be made a (weighted) superposition of the N distinct logic values. Fuzzy logic is also naturally represented by a two-component superposition within the binary case (N=2). Error propagation and accumulation are suppressed. Other relevant advantages are reduced energy dissipation and leakage current problems, and robustness against circuit noise and background noises such as 1/f, Johnson, shot and crosstalk noise. Variability problems are also non-existent because the logic value is an AC signal. A similar logic system can be built with orthogonal sinusoidal signals (different frequency or orthogonal phase) however that has an extra 1/N type slowdown compared to the noise-based logic system with increasing number of N furthermore it is less robust against time delay effects than the noise-based counterpart

  19. Noise-based logic: Binary, multi-valued, or fuzzy, with optional superposition of logic states

    Science.gov (United States)

    Kish, Laszlo B.

    2009-03-01

    A new type of deterministic (non-probabilistic) computer logic system inspired by the stochasticity of brain signals is shown. The distinct values are represented by independent stochastic processes: independent voltage (or current) noises. The orthogonality of these processes provides a natural way to construct binary or multi-valued logic circuitry with arbitrary number N of logic values by using analog circuitry. Moreover, the logic values on a single wire can be made a (weighted) superposition of the N distinct logic values. Fuzzy logic is also naturally represented by a two-component superposition within the binary case ( N=2). Error propagation and accumulation are suppressed. Other relevant advantages are reduced energy dissipation and leakage current problems, and robustness against circuit noise and background noises such as 1/f, Johnson, shot and crosstalk noise. Variability problems are also non-existent because the logic value is an AC signal. A similar logic system can be built with orthogonal sinusoidal signals (different frequency or orthogonal phase) however that has an extra 1/N type slowdown compared to the noise-based logic system with increasing number of N furthermore it is less robust against time delay effects than the noise-based counterpart.

  20. Application of fuzzy logic to determine the odour intensity of model gas mixtures using electronic nose

    Science.gov (United States)

    Szulczyński, Bartosz; Gębicki, Jacek; Namieśnik, Jacek

    2018-01-01

    The paper presents the possibility of application of fuzzy logic to determine the odour intensity of model, ternary gas mixtures (α-pinene, toluene and triethylamine) using electronic nose prototype. The results obtained using fuzzy logic algorithms were compared with the values obtained using multiple linear regression (MLR) model and sensory analysis. As the results of the studies, it was found the electronic nose prototype along with the fuzzy logic pattern recognition system can be successfully used to estimate the odour intensity of tested gas mixtures. The correctness of the results obtained using fuzzy logic was equal to 68%.

  1. Geo-Spatial Tactical Decision Aid Systems: Fuzzy Logic for Supporting Decision Making

    National Research Council Canada - National Science Library

    Grasso, Raffaele; Giannecchini, Simone

    2006-01-01

    .... This paper describes a tactical decision aid system based on fuzzy logic reasoning for data fusion and on current Open Geospatial Consortium specifications for interoperability, data dissemination...

  2. Neuro fuzzy control of the FES assisted freely swinging leg of paraplegic subjects

    NARCIS (Netherlands)

    van der Spek, J.H.; Velthuis, W.J.R.; Veltink, Petrus H.; de Vries, Theodorus J.A.

    1996-01-01

    The authors designed a neuro fuzzy control strategy for control of cyclical leg movements of paraplegic subjects. The cyclical leg movements were specified by three `swing phase objectives', characteristic of natural human gait. The neuro fuzzy controller is a combination of a fuzzy logic controller

  3. Development of a system for monitoring and diagnosis using Fuzzy logic in control valves of laboratory test equipment of Experimental Center Aramar; Desenvolvimento de um sistema de monitoracao e diagnostico utilizando logica Fuzzy aplicado a valvulas de controle de processo do CEA - Centro Experimental Aramar

    Energy Technology Data Exchange (ETDEWEB)

    Porto Junior, Almir Carlos Soares

    2014-07-01

    The question of components reliability, specifically process control valves, has become an important issue to be investigated in nuclear power plants and other areas such as refinery or offshore oil rig, considering the safety and life extension of the plant. The development of non intrusive monitoring and diagnostic method allows the identification of defects in components of the plant during normal operation. The objective of this dissertation is to present an analysis and diagnosis of control valves of a steam plant part that simulates the secondary circuit of a pressurized water reactor. This installation is part of propulsion equipment testing laboratory of the Brazilian Navy, at Ipero-SP. The methodology for design is based on graphical analysis of two parameters, the valve air pressure actuator and the displacement of the valve plug. These data are extracted by a smart positioner, part of Delta V™ Automation System. An analysis is implemented in detecting anomalies by an approach using Expert Systems by the technique of fuzzy logic. Once the basic measures of control valves are taken, it is possible to detect symptoms of failure, leakage, friction, damage, etc. The monitoring and diagnostic system has been designed in MATLAB® version 2009{sup th} by the complement 'Fuzzy Logic Toolbox'. It is a noninvasive technique. Thus, it is possible to know what is happening with the chosen components, just analyzing the parameters of the valve. The software called ValveLink® (developed by Emerson) receives signals from hardware component (intelligent positioner) installed next to the control valve. These signals (electrical current) are transformed into information which are used input parameters: air pressure valve actuator and valve plug displacement. With the use of fuzzy logic, these parameters are interpreted. They suffer inferences by rules written by experts in valves. After these inferences, the information is processed and sent as output signals

  4. MANUAL LOGIC CONTROLLER (MLC)

    OpenAIRE

    Claude Ziad Bayeh

    2015-01-01

    The “Manual Logic Controller” also called MLC, is an electronic circuit invented and designed by the author in 2008, in order to replace the well known PLC (Programmable Logic Controller) in many applications for its advantages and its low cost of fabrication. The function of the MLC is somewhat similar to the well known PLC, but instead of doing it by inserting a written program into the PLC using a computer or specific software inside the PLC, it will be manually programmed in a manner to h...

  5. Fractional variational problems and particle in cell gyrokinetic simulations with fuzzy logic approach for tokamaks

    Directory of Open Access Journals (Sweden)

    Rastović Danilo

    2009-01-01

    Full Text Available In earlier Rastovic's papers [1] and [2], the effort was given to analyze the stochastic control of tokamaks. In this paper, the deterministic control of tokamak turbulence is investigated via fractional variational calculus, particle in cell simulations, and fuzzy logic methods. Fractional integrals can be considered as approximations of integrals on fractals. The turbulent media could be of the fractal structure and the corresponding equations should be changed to include the fractal features of the media.

  6. A Temporal Fuzzy Logic Formalism for Knowledge Based Systems

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2012-11-01

    Full Text Available This paper shows that the influence of knowledge on new forms of work organisation can be described as mutual relationships. Different changes in work organisation also have a strong influence on the increasing importance of knowledge of different individual and collective actors in working situations. After that, we characterize a piece of basic formal system, an Extended Fuzzy Logic System (EFLS with temporal attributes, to conceptualize future DKMSs based on human imprecise for distributed just in time decisions. The approximate reasoning is perceived as a derivation of new formulas with the corresponding temporal attributes, within a fuzzy theory defined by the fuzzy set of special axioms. In a management application, the reasoning is evolutionary because of unexpected events which may change the state of the DKMS. In this kind of situations it is necessary to elaborate certain mechanisms in order to maintain the coherence of the obtained conclusions, to figure out their degree of reliability and the time domain for which these are true. These last aspects stand as possible further directions of development at a basic logic level for future technologies that must automate knowledge organizational processes.

  7. French speaking meetings on fuzzy logic and its applications

    International Nuclear Information System (INIS)

    2000-01-01

    The LFA conferences are devoted to the presentation of the most recent works about the fuzzy sets theory and its possible applications to fuzzy control, classification, pattern recognition, data processing, decision making, reasoning, image processing and interpretation, fusion of informations, artificial intelligence and information management systems. Among the 39 articles reported in this book, one concerns the processing of NMR images in nuclear medicine and has been selected for Inis. (J.S.)

  8. Fuzzy Logic-Based Histogram Equalization for Image Contrast Enhancement

    Directory of Open Access Journals (Sweden)

    V. Magudeeswaran

    2013-01-01

    Full Text Available Fuzzy logic-based histogram equalization (FHE is proposed for image contrast enhancement. The FHE consists of two stages. First, fuzzy histogram is computed based on fuzzy set theory to handle the inexactness of gray level values in a better way compared to classical crisp histograms. In the second stage, the fuzzy histogram is divided into two subhistograms based on the median value of the original image and then equalizes them independently to preserve image brightness. The qualitative and quantitative analyses of proposed FHE algorithm are evaluated using two well-known parameters like average information contents (AIC and natural image quality evaluator (NIQE index for various images. From the qualitative and quantitative measures, it is interesting to see that this proposed method provides optimum results by giving better contrast enhancement and preserving the local information of the original image. Experimental result shows that the proposed method can effectively and significantly eliminate washed-out appearance and adverse artifacts induced by several existing methods. The proposed method has been tested using several images and gives better visual quality as compared to the conventional methods.

  9. Simulation Study of IMC and Fuzzy Controller for HVAC System

    Directory of Open Access Journals (Sweden)

    Umamaheshwari

    2009-06-01

    Full Text Available This paper presents how the fuzzy logic controller is used to solve the control problems of complex and non linear process and show that it is more robust and their performance are less sensitive to parametric variations than conventional controllers. These systems will yield a linear response when compared to ordinary controllers. The main advantage of Fuzzy control over conventional controllers is regulation can be done without over shoot.

  10. Development of erosion risk map using fuzzy logic approach

    Directory of Open Access Journals (Sweden)

    Fauzi Manyuk

    2017-01-01

    Full Text Available Erosion-hazard assessment is an important aspect in the management of a river basin such as Siak River Basin, Riau Province, Indonesia. This study presents an application of fuzzy logic approach to develop erosion risk map based on geographic information system. Fuzzy logic is a computing approach based on “degrees of truth” rather than the usual “true or false” (1 or 0 Boolean logic on which the modern computer is based. The results of the erosion risk map were verified by using field measurements. The verification result shows that the parameter of soil-erodibility (K indicates a good agreement with field measurement data. The classification of soil-erodibility (K as the result of validation were: very low (0.0–0.1, medium (0.21-0.32, high (0.44-0.55 and very high (0.56-0.64. The results obtained from this study show that the erosion risk map of Siak River Basin were dominantly classified as medium level which cover about 68.54%. The other classifications were high and very low erosion level which cover about 28.84% and 2.61% respectively.

  11. Fuzzy logic of quasi-truth an algebraic treatment

    CERN Document Server

    Di Nola, Antonio; Turunen, Esko

    2016-01-01

    This book presents the first algebraic treatment of quasi-truth fuzzy logic and covers the algebraic foundations of many-valued logic. It offers a comprehensive account of basic techniques and reports on important results showing the pivotal role played by perfect many-valued algebras (MV-algebras). It is well known that the first-order predicate Łukasiewicz logic is not complete with respect to the canonical set of truth values. However, it is complete with respect to all linearly ordered MV –algebras. As there are no simple linearly ordered MV-algebras in this case, infinitesimal elements of an MV-algebra are allowed to be truth values. The book presents perfect algebras as an interesting subclass of local MV-algebras and provides readers with the necessary knowledge and tools for formalizing the fuzzy concept of quasi true and quasi false. All basic concepts are introduced in detail to promote a better understanding of the more complex ones. It is an advanced and inspiring reference-guide for graduate s...

  12. Application of fuzzy logic in multicomponent analysis by optodes.

    Science.gov (United States)

    Wollenweber, M; Polster, J; Becker, T; Schmidt, H L

    1997-01-01

    Fuzzy logic can be a useful tool for the determination of substrate concentrations applying optode arrays in combination with flow injection analysis, UV-VIS spectroscopy and kinetics. The transient diffuse reflectance spectra in the visible wavelength region from four optodes were evaluated to carry out the simultaneous determination of artificial mixtures of ampicillin and penicillin. The discrimination of the samples was achieved by changing the composition of the receptor gel and working pH. Different algorithms of pre-processing were applied on the data to reduce the spectral information to a few analytic-specific variables. These variables were used to develop the fuzzy model. After calibration the model was validated by an independent test data set.

  13. A fuzzy logic based navigation for mobile robot

    International Nuclear Information System (INIS)

    Adel Ali S Al-Jumaily; Shamsudin M Amin; Mohamed Khalil

    1998-01-01

    The main issue of intelligent robot is how to reach its goal safely in real time when it moves in unknown environment. The navigational planning is becoming the central issue in development of real-time autonomous mobile robots. Behaviour based robots have been successful in reacting with dynamic environment but still there are some complexity and challenging problems. Fuzzy based behaviours present as powerful method to solve the real time reactive navigation problems in unknown environment. We shall classify the navigation generation methods, five some characteristics of these methods, explain why fuzzy logic is suitable for the navigation of mobile robot and automated guided vehicle, and describe a reactive navigation that is flexible to react through their behaviours to the change of the environment. Some simulation results will be presented to show the navigation of the robot. (Author)

  14. Development of Fuzzy Logic and Soft Computing Methodologies

    Science.gov (United States)

    Zadeh, L. A.; Yager, R.

    1999-01-01

    Our earlier research on computing with words (CW) has led to a new direction in fuzzy logic which points to a major enlargement of the role of natural languages in information processing, decision analysis and control. This direction is based on the methodology of computing with words and embodies a new theory which is referred to as the computational theory of perceptions (CTP). An important feature of this theory is that it can be added to any existing theory - especially to probability theory, decision analysis, and control - and enhance the ability of the theory to deal with real-world problems in which the decision-relevant information is a mixture of measurements and perceptions. The new direction is centered on an old concept - the concept of a perception - a concept which plays a central role in human cognition. The ability to reason with perceptions perceptions of time, distance, force, direction, shape, intent, likelihood, truth and other attributes of physical and mental objects - underlies the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Everyday examples of such tasks are parking a car, driving in city traffic, cooking a meal, playing golf and summarizing a story. Perceptions are intrinsically imprecise. Imprecision of perceptions reflects the finite ability of sensory organs and ultimately, the brain, to resolve detail and store information. More concretely, perceptions are both fuzzy and granular, or, for short, f-granular. Perceptions are f-granular in the sense that: (a) the boundaries of perceived classes are not sharply defined; and (b) the elements of classes are grouped into granules, with a granule being a clump of elements drawn together by indistinguishability, similarity. proximity or functionality. F-granularity of perceptions may be viewed as a human way of achieving data compression. In large measure, scientific progress has been, and continues to be

  15. Fuzzy multivariable control of domestic heat pumps

    International Nuclear Information System (INIS)

    Underwood, C.P.

    2015-01-01

    Poor control has been identified as one of the reasons why recent field trials of domestic heat pumps in the UK have produced disappointing results. Most of the technology in use today uses a thermostatically-controlled fixed speed compressor with a mechanical expansion device. This article investigates improved control of these heat pumps through the design and evaluation of a new multivariable fuzzy logic control system utilising a variable speed compressor drive with capacity control linked through to evaporator superheat control. A new dynamic thermal model of a domestic heat pump validated using experimental data forms the basis of the work. The proposed control system is evaluated using median and extreme daily heating demand profiles for a typical UK house compared with a basic thermostatically-controlled alternative. Results show good tracking of the heating temperature and superheat control variables, reduced cycling and an improvement in performance averaging 20%. - Highlights: • A new dynamic model of a domestic heat pump is developed and validated. • A new multivariable fuzzy logic heat pump control system is developed/reported. • The fuzzy controller regulates both plant capacity and evaporator superheat degree. • Thermal buffer storage is also considered as well as compressor cycling. • The new controller shows good variable tracking and a reduction in energy of 20%.

  16. A Comparison of Fuzzy and Annotated Logic Programming

    Czech Academy of Sciences Publication Activity Database

    Krajči, S.; Lencses, R.; Vojtáš, Peter

    2004-01-01

    Roč. 144, - (2004), s. 173-192 ISSN 0165-0114 R&D Projects: GA ČR GA201/00/1489 Grant - others:VEGA(SK) 1/7557/20; VEGA(SK) 1/7555/20; VEGA(SK) 1/0385/03 Institutional research plan: CEZ:AV0Z1030915 Keywords : fuzzy logic programming * generalized annotated programs * declarative and procedural semantics * continuous semantics and computable fixpoint * soundness and completeness Subject RIV: BA - General Mathematics Impact factor: 0.734, year: 2004

  17. Fuzzy logic for risk assessment in auditing

    OpenAIRE

    Antunes, Jerônimo

    2006-01-01

    A avaliação dos riscos de que os controles internos de uma entidade possam falhar constitui-se em significativo desafio para os auditores independentes de demonstrações contábeis. As metodologias de trabalho empregadas para tal finalidade, normalmente, utilizam a lógica clássica, ou também denominada binária, presumindo que os fatores de riscos estão presentes, ou não, em um determinado tipo de processo de controle. O objetivo deste trabalho foi conceber um modelo de avaliação de risco dos co...

  18. A Note on Axiomatizations of Pavelka-style Complete Fuzzy Logics

    Czech Academy of Sciences Publication Activity Database

    Cintula, Petr

    2016-01-01

    Roč. 292, 1 June (2016), s. 160-174 ISSN 0165-0114 R&D Projects: GA ČR GAP202/10/1826 Institutional support: RVO:67985807 Keywords : mathematical fuzzy logic * Pavelka-style completeness * MTL logic * Lukasiewicz logics * Product Logic * truth constants * Monteiro–Baaz delta Subject RIV: BA - General Mathematics Impact factor: 2.718, year: 2016

  19. Navigasi Berbasis Behavior dan Fuzzy Logic pada Simulasi Robot Bergerak Otonom

    Directory of Open Access Journals (Sweden)

    Rendyansyah

    2016-03-01

    Full Text Available Mobile robot is the robotic mechanism that is able to moved automatically. The movement of the robot automatically require a navigation system. Navigation is a method for determining the robot motion. In this study, using a method developed robot navigation behavior with fuzzy logic. The behavior of the robot is divided into several modules, such as walking, avoid obstacles, to follow walls, corridors and conditions of u-shape. In this research designed mobile robot simulation in a visual programming. Robot is equipped with seven distance sensor and divided into several groups to test the behavior that is designed, so that the behavior of the robot generate speed and steering control. Based on experiments that have been conducted shows that mobile robot simulation can run smooth on many conditions. This proves that the implementation of the formation of behavior and fuzzy logic techniques on the robot working well

  20. Fuzzy Control of a Lead Acid Battery Charger

    Directory of Open Access Journals (Sweden)

    A. DAOUD

    2005-03-01

    Full Text Available In this paper, an alternative battery charging control technique based on fuzzy logic for photovoltaic (PV applications is presented. A PV module is connected to a buck type DC/DC power converter and a microcontroller based unit is used to control the lead acid battery charging voltage. The fuzzy control is used due to the simplicity of implementation, robustness and independence from the complex mathematical representation of the battery. The usefulness of this control method is confirmed by experiments.