48,468 research outputs found

    Fuzzy Inference System for VOLT/VAR control in distribution substations in isolated power systems

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    This paper presents a fuzzy inference system for voltage/reactive power control in distribution substations. The purpose is go forward to automation distribution and its implementation in isolated power systems where control capabilities are limited and it is common using the same applications as in continental power systems. This means that lot of functionalities do not apply and computational burden generates high response times. A fuzzy controller, with logic guidelines embedded based upon heuristic rules resulting from operators at dispatch control center past experience, has been designed. Working as an on-line tool, it has been tested under real conditions and it has managed the operation during a whole day in a distribution substation. Within the limits of control capabilities of the system, the controller maintained successfully an acceptable voltage profile, power factor values over 0,98 and it has ostensibly improved the performance given by an optimal power flow based automation system

    Rancang Bangun Farming Box Dengan Pengaturan Suhu Menggunakan Fuzzy Logic Controller

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    Implementation of control systems has been carried out in many fields of science. One of it applications is in the agriculture fields. In this research we implemented a control system on farming in a box. Farming in a box is a system that uses old shipping containers for the purpose of growing plants in any environment. Inside shipping containers is fully assembled hydroponic pipe with air temperature control. In this research was built a little farming box from acryclic to imitate a shipping container. Main focus of this research is design an air temperature control using fuzzy logic controller. Fuzzy logic controller was choosen because many existing farming box use on off controller. In some application, fuzzy logic controller has better performance than on off controller. Farming box temperature is controlled by blowing cool air using an electric fan. In this case, cool air is produced by cold side of peltier. Electric fan speed is controlled by pulse width modulation signal (PWM) that generated from microcontroller. Air temperature data feedback is obtained from DHT 11 sensor that installed in a acrylic box. Sensor is physically connected with microcontroller and Fuzzy logic controller is embedded in microcontroller as an algorithm. Fuzzy logic controller was design with error temperature and error difference as an input, and duty cycle of PWM signal as output. Fuzzy logic controller system performs to reduce the temperature from 31,6 ° C to set poin 28° C in 71 seconds. Steady state error obtained by 1.28% and better than uncontrolled system that obtain steady state error 7,14%

    Fuzzy logic-based automotive airbag control system.

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    Fuzzy Logic implementation is becoming increasingly important, and finding applications in diverse areas of current interest, such as control, pattern recognition, robotics, and other decision making applications. Fuzzy decision process offer a significant advantage over crisp decision process which is the ability to process different levels of truth instead of only 1 or 0 levels. Fuzzy Logic does not require precise inputs, it is inherently robust, and can process any reasonable number of inputs but system complexity increases rapidly with more inputs and outputs. Distributed processors would probably be easier to implement. Simple, plain-language IF X AND Y THEN Z rules are used to describe the desired system response in terms of linguistic variables rather than mathematical formulas. The number of these is dependent on the number of inputs, outputs, and the designer\u27s control response goals. The new Motorola 68HC12 MCU has an embedded fuzzy logic instruction set. Using this instruction set, we can implement complex fuzzy logic systems using only a few hundred bytes of ROM that cycle compute in less than a millisecond. Considering the fact that the fuzzy logic instruction set of the 68HC 12, enables the use of fuzzy logic in mass-market high-speed applications, such as car engine control, anti-skid brakes, traction control, inter-vehicle dynamics control, hard disk drive control, servo motor control, and cellular phones. This thesis deals with the design of Automotive Airbag Control System a using Fuzzy Logic based decision structure and implementation using the 68HC12 microcontroller.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1999 .M52. Source: Masters Abstracts International, Volume: 39-02, page: 0566. Adviser: J. J. Soltis. Thesis (M.A.Sc.)--University of Windsor (Canada), 2000

    FPGA implementation of embedded fuzzy controllers for robotic applications

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    Fuzzy-logic-based inference techniques provide efficient solutions for control problems in classical and emerging applications. However, the lack of specific design tools and systematic approaches for hardware implementation of complex fuzzy controllers limits the applicability of these techniques in modern microelectronics products. This paper discusses a design strategy that eases the implementation of embedded fuzzy controllers as systems on programmable chips. The development of the controllers is carried out by means of a reconfigurable platform based on field-programmable gate arrays. This platform combines specific hardware to implement fuzzy inference modules with a general-purpose processor, thus allowing the realization of hybrid hardware/soffivare solutions. As happens to the components of the processing system, the specific fuzzy elements are conceived as configurable intellectual property modules in order to accelerate the controller design cycle. The design methodology and tool chain presented in this paper have been applied to the realization of a control system for solving the navigation tasks of an autonomous vehicle

    FPGA Implementation of Embedded Fuzzy Controllers for Robotic Applications

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    Fuzzy-logic-based inference techniques provide efficient solutions for control problems in classical and emerging applications. However, the lack of specific design tools and systematic approaches for hardware implementation of complex fuzzy controllers limits the applicability of these techniques in modern microelectronics products. This paper discusses a design strategy that eases the implementation of embedded fuzzy controllers as systems on programmable chips. The development of the controllers is carried out by means of a reconfigurable platform based on field-programmable gate arrays. This platform combines specific hardware to implement fuzzy inference modules with a general-purpose processor, thus allowing the realization of hybrid hardware/software solutions. As happens to the components of the processing system, the specific fuzzy elements are conceived as configurable intellectual property modules in order to accelerate the controller design cycle. The design methodology and tool chain presented in this paper have been applied to the realization of a control system for solving the navigation tasks of an autonomous vehicle. © 2007 IEEE.Ministerio de Educación y Ciencia TEC2005-04359/MIC y DPI2005-02293Junta de Andalucía TIC2006-635 y TEP2006-37

    Adaptive resource allocation algorithms with QoS support based on network conditions using fuzzy logic system for IEEE 802.11n networks / Bakeel Hussein Naji Maqhat

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    In wireless local area network (WLAN), the primary concern is Quality of Service (QoS) support that aims to satisfy the diverse service requirements and to guarantee higher data rates allocation for different service classes. However, IEEE 802.11n standard does not specify a scheduling algorithm to guarantee QoS. The performance benefits of existing solutions in MAC layers often fall short of providing the QoS support, particularly, it is still experiencing additional access latency and bandwidth allocation disorder where errors occur, that leads flows backlogged. The aim of this thesis is to develop a fair and efficient packet scheduling and adaptive bandwidth allocation algorithms to support QoS for a diverse service class for A-MSDU aggregation in IEEE 802.11n network. This thesis presents four main contributions for QoS provisioning that are robust, scalable, and can be successfully implemented in WLAN networks. The first contribution is the AMS scheduling algorithm. The aim is to satisfy QoS requirements for time sensitive applications by exploiting the A-MSDU attributes and adopting the idea of enabling selective retransmission in our scheduling algorithm to obtain aggregation with small size to support time-sensitive applications and enable prioritization according to the QoS requirements of the traffic classes. The second contribution is an efficient bandwidth allocation algorithm for A-MSDU aggregation called Adaptive Scheduling based Embedded Fuzzy (ASEF) system. ASEF system is fully dynamic with fuzzy logic based approach and adaptive deadlinebased scheme for various service class traffics. The algorithm employs fuzzy logic control which is embedded in the scheduler. The function is to control and dynamically update the bandwidth required by the various service classes according to their respective priorities, maximum latency, and throughput

    State-of-the-art in control engineering

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    AbstractThe paper deals with new trends in research, development and applications of advanced control methods and structures based on the principles of optimality, robustness and intelligence. Present trends in the complex process control design demand an increasing degree of integration of numerical mathematics, control engineering methods, new control structures based of distribution, embedded network control structure and new information and communication technologies. Furthermore, increasing problems with interactions, process non-linearities, operating constraints, time delays, uncertainties, and significant dead-times consequently lead to the necessity to develop more sophisticated control strategies. Advanced control methods and new distributed embedded control structures represent the most effective tools for realizing high performance of many technological processes. Main ideas covered in this paper are motivated namely by the development of new advanced control engineering methods (predictive, hybrid predictive, optimal, adaptive, robust, fuzzy logic, and neural network) and new possibilities of their SW and HW realizations and successful implementation in industry

    Impact of Embedded Carbon Fiber Heating Panel on the Structural/Mechanical Performance of Roadway Pavement

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    INE/AUTC 12.3

    Fuzzy Feedback Scheduling of Resource-Constrained Embedded Control Systems

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    The quality of control (QoC) of a resource-constrained embedded control system may be jeopardized in dynamic environments with variable workload. This gives rise to the increasing demand of co-design of control and scheduling. To deal with uncertainties in resource availability, a fuzzy feedback scheduling (FFS) scheme is proposed in this paper. Within the framework of feedback scheduling, the sampling periods of control loops are dynamically adjusted using the fuzzy control technique. The feedback scheduler provides QoC guarantees in dynamic environments through maintaining the CPU utilization at a desired level. The framework and design methodology of the proposed FFS scheme are described in detail. A simplified mobile robot target tracking system is investigated as a case study to demonstrate the effectiveness of the proposed FFS scheme. The scheme is independent of task execution times, robust to measurement noises, and easy to implement, while incurring only a small overhead.Comment: To appear in International Journal of Innovative Computing, Information and Contro
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