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Fuzzy Logic Controllers in Practice (Digest No. 1996/200), IEE Colloquium on

Date 15 Nov 1996

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Displaying Results 1 - 10 of 10
  • Distributed fuzzy logic for building management systems using local operating networks

    Page(s): 6/1 - 6/4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (212 KB)  

    This paper describes the development of an experimental distributed fuzzy control system for heating and ventilation (HVAC) systems within a building. Each local control loop is affected by a number of local variables, as well as information from neighboring controllers. By including this additional information it is hoped that a more equal allocation of resources can be achieved View full abstract»

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  • Educational developments in the teaching of fuzzy logic

    Page(s): 8/1 - 8/2
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (192 KB)  

    This paper describes on-going collaborative research being undertaken between Bytronic International Ltd., Sutton Coldfield, UK and Coventry University, UK in the development of a range of fuzzy control teaching products. The product range includes software, hardware and course material and is aimed at the requirements of industrial training colleges and academic establishment. In developing the fuzzy logic teaching aids, emphasis is placed on student interaction with the application of a 'hands-on' approach under a realistic simulation environment. The latest version of the fuzzy logic teaching aid, Fuzzy Control Package, is currently in the stages of undergoing field trial evaluation in a number of courses in the UK. Feedback from these courses shall be incorporated into the final product. A key feature is graphical visualisation View full abstract»

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  • On-line adaptive fuzzy control of a cryostat

    Page(s): 3/1 - 3/5
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (248 KB)  

    One of the reasons for the current interest in fuzzy control is the successful application of simple rule-based controllers in many diverse fields. However, relatively few adaptive neuro-fuzzy schemes have been tested on practical problems. Moreover, many strategies based on neuro-fuzzy techniques are not suitable for dedicated implementation, since they use some form of optimisation (e.g. recursive least squares or direct search techniques) to select the required control action or for training. To fill this void, the performance of an adaptive fuzzy control scheme, which combines a simple fuzzy identification algorithm with the feedback error learning method, is assessed by using it to control the temperature in a liquid helium cryostat. Results from the practical experiments are presented in this paper View full abstract»

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  • A fuzzy systems toolbox for use with MATLAB

    Page(s): 9/1 - 9/4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (240 KB)  

    In this short note, a collection of MATLABTM M-files covering concepts within the field of fuzzy set theory is described. The areas covered are: fuzzy or multivalued logic; the calculus of fuzzy quantities; fuzzy control; approximate reasoning; possibility theory; and neuro-fuzzy systems View full abstract»

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  • Fuzzy logic control of depth of anaesthesia using auditory evoked responses

    Page(s): 4/1 - 4/6
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (344 KB)  

    Describes the structure of a real-time control system based on fuzzy logic for the control of depth of anaesthesia (DOA) using the drug propofol. The system uses a fuzzy-neural system for monitoring the depth of anaesthesia based on the auditory evoked response (AER) signals. The control system is based on measuring the auditory evoked response signals using a DSP signal processing chip hosted in a PC where the analysis is carried out. Based on the monitored level of DOA the amount of drug infused to the patient is determined by a rule-based fuzzy logic controller. The patient is represented on a different PC where pre-recorded AER signals are stored and selected according to the infused drug View full abstract»

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  • Fuzzy control application in power plants

    Page(s): 1/1 - 1/2
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (112 KB)  

    The application to a unit-type power plant is presented with some simulation results of load sheddings. To improve the quality of the electrical energy, expressed in frequency and voltage, the capability of power plants to perform large and rapid load variations is required. The unit power station shows by such load changes a highly nonlinear behaviour. The use of a fuzzy controller as a nonlinear one to dominate these large and fast load variations necessitates the consideration of additional information in the form of process variables and linguistic knowledge to characterize the nonlinearity of the controlled process. On the basis of the different operating modes and control requirements, the control structure with fuzzy logic is carried out View full abstract»

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  • Traffic responsive signal control using fuzzy logic-a practical modular approach

    Page(s): 5/1 - 5/4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (268 KB)  

    In recent years fuzzy logic has been used to address a number of issues in traffic engineering. This paper presents an application designed to meet the demands of a traffic responsive signal control system operating at a single intersection. Fuzzy logic techniques are incorporated into a modular system within which they provide effective support for the overall control method. This system reflects two fundamental aspects of traffic responsive signal control-the observation of the on-going traffic situation around the intersection, and the control of the traffic signals in a manner appropriate to the observed situation. Fuzzy logic provides a bridge between both of these essential functions by converting the large quantities of raw data emanating from the junction approaches into meaningful and succinct measurements relating to each signal group (or phase) which permit the control logic to make both second-by-second and cycle-by-cycle decisions about the apportionment of green time. The modular nature of this system allows it to be combined directly with the logic of conventional traffic responsive signal controllers View full abstract»

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  • Fuzzy logic controller for the whole body NMR imaging system

    Page(s): 2/1 - 2/4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (264 KB)  

    Nuclear magnetic resonance imaging (NMR imaging) machines provide pictorial anatomical information about the physiological state of internal organs without the use of X-rays, and of all imaging methods, gives the most sensitive discrimination between healthy and diseased tissue. The resolution of whole body NMR imaging is limited by the accuracy and stability of the field gradient (FG) system. This paper considers the application of real-time fuzzy logic control to a field gradient system using a floating point digital signal processor (TMS320C40) to increase image resolution View full abstract»

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