• Title, Summary, Keyword: fuzzy logic based control

Search Result 681, Processing Time 0.099 seconds

A Development of a Real-time, Traffic Adaptive Control Scheme Through VIDs. (영상검지기를 이용한 실시간 교통신호 감응제어)

  • 김성호
    • Journal of Korean Society of Transportation
    • /
    • v.14 no.2
    • /
    • pp.89-118
    • /
    • 1996
  • The development and implementation of a real-time, traffic adaptive control scheme based on fuzzy logic through Video Image Detector systems (VIDs) is presented. Through VIDs based image processing, fuzzy logic can be used for a real-time traffic adaptive signal control scheme. Fuzzy control logic allows linguistic and inexact traffic data to be manipulated as a useful tool in designing signal timing plans. The fuzzy logic has the ability to comprehend linguistic instructions and to generate control strategy based on a priori verbal communication. The implementation of fuzzy logic controller for a traffic network is introduced. Comparisons are made between implementations of the fuzzy logic controller and the actuated controller in an isolated intersection. The results obtained from the application of the fuzzy logic controller are also compared with those corresponding to a pretimed controller for the coordinated intersections. Simulation results from the comparisons indicate the performance of the system is between under the fuzzy logic controller. Integration of the aforementioned schemes into and ATMS framework will lead to real-time adjustment of the traffic control signals, resulting in significant reduction in traffic congestion.

  • PDF

A New Approach to Adaptive Damping Control for Statistic VAR Compensators Based on Fuzzy Logic

  • Sedaghati, Alireza
    • 제어로봇시스템학회:학술대회논문집
    • /
    • /
    • pp.825-829
    • /
    • 2005
  • This paper presents an approach for designing a fuzzy logic-based adaptive SVC damping In controller for damping low frequency power oscillations. Power systems are often subject to low Frequency electro-mechanical oscillations resulting from electrical disturbances. Generally, power system stabilizers are designed to provide damping against this kind of oscillations. Another means to achieve damping is to design supplementary damping controllers that are equipped with SVC. Various approaches are available for designing such controllers, many of which are based on the concepts of damping torque and others which treat the damping controller design as a generic control problem and apply various control theories on it. In our proposed approach, linear optimal controllers are designed and then a fuzzy logic tuning mechanism is constructed to generate a single control signal. The controller uses the system operating condition and a fuzzy logic signal tuner to blend the control signals generated by two linear controllers, which are designed using an optimal control method. First, we design damping controllers for the two extreme conditions; the control action for intermediate conditions is determined by the fuzzy logic tuner. The more the operating condition belongs to one of the two fuzzy sets, the stronger the contribution of the control signal from that set in the output signal. Simulation studies done on a one-machine infinite-bus and a four-machine two-area test system, show that the proposed fuzzy adaptive damping SVC controller effectively enhances the damping of low frequency oscillations.

  • PDF

Comparison of MPPT Based on Fuzzy Logic Controls for PMSG

  • Putri, Adinda Ihsani;Choi, Jaeho
    • Proceedings of the KIPE Conference
    • /
    • /
    • pp.285-286
    • /
    • 2011
  • Maximum Power Point Tracker (MPPT) is the big issue in generating power based on Wind Energy Conversion System. In case of unknown turbine characteristic, it is useful to implement MPPT based on fuzzy logic control. This kind of control is able to find the value of duty cycle to meet maximum power point at particular wind speed. There are many methods to develop MPPT based fuzzy logic controls. In this paper, two of the methods are compared both at low and high fluctuating wind speed.

  • PDF

Logic-based Fuzzy Neural Networks based on Fuzzy Granulation

  • Kwak, Keun-Chang;Kim, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
    • /
    • /
    • pp.1510-1515
    • /
    • 2005
  • This paper is concerned with a Logic-based Fuzzy Neural Networks (LFNN) with the aid of fuzzy granulation. As the underlying design tool guiding the development of the proposed LFNN, we concentrate on the context-based fuzzy clustering which builds information granules in the form of linguistic contexts as well as OR fuzzy neuron which is logic-driven processing unit realizing the composition operations of T-norm and S-norm. The design process comprises several main phases such as (a) defining context fuzzy sets in the output space, (b) completing context-based fuzzy clustering in each context, (c) aggregating OR fuzzy neuron into linguistic models, and (c) optimizing connections linking information granules and fuzzy neurons in the input and output spaces. The experimental examples are tested through two-dimensional nonlinear function. The obtained results reveal that the proposed model yields better performance in comparison with conventional linguistic model and other approaches.

  • PDF

Design of Vectored Sum Defuzzification Based Fuzzy Logic System for Hovering Control of Quad-Copter

  • Yoo, Hyun-Ho;Choi, Byung-Jae
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • v.16 no.4
    • /
    • pp.318-322
    • /
    • 2016
  • A quad-copter or quad rotor system is an unmanned flying machine having four engines, which their thrust force is produced by four propellers. Its stable control is very important and has widely been studied. It is a typical example of a nonlinear system. So, it is difficult to get a desired control performance by conventional control algorithms. In this paper, we propose the design of a vectored sum defuzzification based fuzzy logic system for the hovering control of a quad-copter. We first summarize its dynamics and introduce a vectored sum defuzzification scheme. And then we design a vectored sum defuzzification based fuzzy logic system. for the hovering control of the quad-copter. Finally, in order to check the feasibility of the proposed system we present some simulation examples.

Optimal Fuzzy Control of Parallel Hybrid Electric Vehicles

  • Farrokhi, M.;Mohebbi, M.
    • 제어로봇시스템학회:학술대회논문집
    • /
    • /
    • pp.910-914
    • /
    • 2005
  • In this paper an optimal method based on fuzzy logic for controlling parallel hybrid electric vehicles is presented. In parallel hybrid electric vehicles the required torque for deriving and operating the on-board accessories is generated by a combination of internal-combustion engine and an electric motor. The powersharing between the internal combustion engine and the electric motor is the key point for efficient driving. This is a highly nonlinear and time varying plant and its control strategy will be implemented with the use of fuzzy logic controller. The fuzzy logic controller will be designed based on the state of charge of batteries and the desired torque for driving. The output of controller controls the throttle of the combustion engine. The main contribution of this paper is the development of an optimal control based on fuzzy logic, which maximizes the output torque of the vehicle while minimizing fuel consumed by the combustion engine.

  • PDF

Modeling of vision based robot formation control using fuzzy logic controller and extended Kalman filter

  • Rusdinar, Angga;Kim, Sung-Shin
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • v.12 no.3
    • /
    • pp.238-244
    • /
    • 2012
  • A modeling of vision based robot formation control system using fuzzy logic controller and extended Kalman filter is presented in this paper. The main problems affecting formation controls using fuzzy logic controller and vision based robots are: a robot's position in a formation need to be maintained, how to develop the membership function in order to obtain the optimal fuzzy system control that has the ability to do the formation control and the noise coming from camera process changes the position of references view. In order to handle these problems, we propose a fuzzy logic controller system equipped with a dynamic output membership function that controls the speed of the robot wheels to handle the maintenance position in formation. The output membership function changes over time based on changes in input at time t-1 to t. The noises appearing in image processing change the virtual target point positions are handled by Extended Kalman filter. The virtual target positions are established in order to define the formations. The virtual target point positions can be changed at any time in accordance with the desired formation. These algorithms have been validated through simulation. The simulations confirm that the follower robots reach their target point in a short time and are able to maintain their position in the formation although the noises change the target point positions.

Design of fuzzy logic Run-by-Run controller for rapid thermal precessing system (고속 열처리공정 시스템의 퍼지 Run-by-Run 제어기 설계)

  • Lee, Seok-Joo;Woo, Kwang-Bang
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.6 no.1
    • /
    • pp.104-111
    • /
    • 2000
  • A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

  • PDF

Design of Adaptive Fuzzy Control for High Performance of PMSM Drive (PMSM 드라이브의 고성능 제어를 위한 적응 퍼지제어기의 설계)

  • 정동화;이홍균;이정철
    • The Transactions of the Korean Institute of Electrical Engineers B
    • /
    • v.53 no.2
    • /
    • pp.107-113
    • /
    • 2004
  • This paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of permanent magnet synchronous motor(PMSM) drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. The operation of the direct fuzzy controller and the fuzzy logic based adaptation mechanism is studied. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive fuzzy controller is evaluated by simulation for various operating conditions. The validity of the proposed adaptive fuzzy controller is confirmed by performance results for PMSM drive system.

Remote Fuzzy Logic Control of Networked Control system in Profibus-DP

  • Lee, Kyung-Chang;Lee, Suk
    • 제어로봇시스템학회:학술대회논문집
    • /
    • /
    • pp.133.2-133
    • /
    • 2001
  • This paper focuses on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several independent, but interacting processes running on two separate stations. By using this NCS, the network delay is analyzed to find the cause of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controllers performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice for NCS due to its robustness against parameter uncertainty.

  • PDF