• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1527-1539
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• 2015

In this paper the hardware implementation of the direct torque control based on the fuzzy logic technique of induction motor on the Field-Programmable Gate Array (FPGA) is presented. Due to its complexity, the fuzzy logic technique implemented on a digital system like the DSP (Digital Signal Processor) and microcontroller is characterized by a calculating delay. This delay is due to the processing speed which depends on the system complexity. The limitation of these solutions is inevitable. To solve this problem, an alternative digital solution is used, based on the FPGA, which is characterized by a fast processing speed, to take the advantage of the performances of the fuzzy logic technique in spite of its complex computation. The Conventional Direct Torque Control (CDTC) of the induction machine faces problems, like the high stator flux, electromagnetic torque ripples, and stator current distortions. To overcome the CDTC problems many methods are used such as the space vector modulation which is sensitive to the parameters variations of the machine, the increase in the switches inverter number which increases the cost of the inverter, and the artificial intelligence. In this paper an intelligent technique based on the fuzzy logic is used because it is allows controlling the systems without knowing the mathematical model. Also, we use a new method based on the Xilinx system generator for the hardware implementation of Direct Torque Fuzzy Control (DTFC) on the FPGA. The simulation results of the DTFC are compared to those of the CDTC. The comparison results illustrate the reduction in the torque and stator flux ripples of the DTFC and show the Xilinx Virtex V FPGA performances in terms of execution time.

• Proceedings of the KIPE Conference
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• 2015.11a
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• pp.215-216
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• 2015

A suspending force control based on fuzzy logic control is proposed to apply on a novel hybrid bearingless switched reluctance motor(BLSRM) which has separated torque and suspending force pole. In this paper, two fuzzy controller targeted at x-axis direction and y-axis direction are adopted to maintain the shaft at center position, which is very necessary for stable operation of BLSRM. Useing the modified fuzzy logic controller, the suspending system can behave a good performance, and the proposed scheme can be verified by simulation results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.166-171
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• 1996

Generally, when we control the robot, we should calculate exactly Inverse Kinematics. However, Inverse Kinematics calculation is complex and it takes much time for the manipulator to control in real-time. Therefore, the calculation of Inverse Kinematics can result in significant control delay in real time. In this paper, we will present that Inverse Kinematics can be calculated through Fuzzy Logic Mapping, Based on an exact solution through fuzzy reasoning instead of Inverse Kinematics calculation Also, the result provides sufficient precision and transient tracking error can be controlled based on a fuzzy adaptive scheme proposed in this paper. Based on the Denavit-Hartenberg parameters specification, after the Jacobian matrix of arbitrary manipulator is calculated, we will construct Fuzzy Inverse Kinematics Mapping(FIKM) using fuzzy logic and represent a good control efficiency through simulation of 2-DOF manipulator.

• 연구논문집
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• s.23
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• pp.73-80
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• 1993

This study presents an intelligent PID control method based on the fuzzy logic and this method is applied to the active magnetic bearing system. By using an appropriate fuzzy matrix, some changes of values of the three coefficients of the controller are determined during system operation and these lead to the improvement of the transient and steady state behavior of the closed loop system. The presented method is actually a combination of the principles of PID control and fuzzy logic. Since the fuzzy logic using linguistic variables in place of numeric variables has many points of likeness to the human logic, the improvement in performance is notable especially in case of large nonlinearity and uncertainty such as the controller start and the excessive mass unbalance. A set of simulation and experimental results illustrate and considerable improvement in the control performance including small overshoot and small transient currents in magnet coils, while maintaining the overal static and dynamic characteristics near the equilibrium position.

• Journal of KIISE:Information Networking
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• v.31 no.3
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• pp.289-297
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• 2004

State-of-the-art wireless communication networks allow dynamic relocation of mobile terminals. A location management mechanism is required to keep track of a mobile terminal for delivering incoming calls. In this paper, we propose a fuzzy logic-based selective paging method to reduce paging cost. In the proposed fuzzy logic-based location management method, the location update uses the area-based method that uses direction-based together with movement-based methods, and the location search uses the fuzzy logic-based selective paging method based on the mobility information of mobile terminals. A partial candidate paging area is selected by fuzzy control rules, then the fuzzy logic-based selective paging method pages only the cells within the partial candidate paging area. The performance of proposed fuzzy logic-based location management method is to be evaluated by both an analytical model and a simulation, and is compared with those of LA and BVP methods. From these evaluation results, we know that the proposed fuzzy logic-based location management method provide better performance than other location management methods.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.3
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• pp.143-148
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• 2018

In this paper, the optimal fuzzy logic controller(FLC) for a hybrid renewable energy system(HRES) is proposed. Generally, hybrid renewable energy systems can consist of wind power, solar power, fuel cells and storage devices. The proposed FLC can effectively control the entire HRES by determining the output power of the fuel cell or the absorption power of the electrolyzer. In general, fuzzy logic controllers can be optimized by classical optimization algorithms such as genetic algorithms(GA) or particle swarm optimization(PSO). However, these FLC have a disadvantage in that their performance varies greatly depending on the control parameters of the optimization algorithms. Therefore, we propose a method to optimize the fuzzy logic controller using the teaching-learning based optimization(TLBO) algorithm which does not have the control parameters of the algorithm. The TLBO algorithm is an optimization algorithm that mimics the knowledge transfer mechanism in a class. To verify the performance of the proposed algorithm, we modeled the hybrid system using Matlab Tool and compare and analyze the performance with other classical optimization algorithms. The simulation results show that the proposed method shows better performance than the other methods.

• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.95-104
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• 2002

This paper presents some studies on the Internet TCP/IP(Transmission Control Protocol-Internet Protocol) traffic over ATM(Asynchronous Transfer Mode) UBR(Unspecified Bit Rate) and ABR(Available Bit Rate) classes of service. Fuzzy logic prediction has been used to improve the efficiency and fairness of traffic throughput. For TCP/IP over UBR, a novel fuzzy logic based cell dropping scheme is presented. This is referred to as fuzzy logic selective cell drop (FSCD). A key feature of the scheme is its ability to accept or drop a new incoming packet dynamically based on the predicted future buffer condition in the switch. This is achieved by using fuzzy logic prediction for the production of a drop factor. Packet dropping decision is then based on this drop factor and a predefined threshold value. Simulation results show that the proposed scheme significantly improves TCP/IP efficiency and fairness. To study TCP/IP over ABR, we applied the fuzzy logic ABR service buffer management scheme from our previous work to both approximate and exact fair rate computation ER(Explicit cell Rate) switch algorithms. We then compared the performance of the fuzzy logic control with conventional schemes. Simulation results show that on zero TCP packet loss, the fuzzy logic control scheme achieves maximum efficiency and perfect fairness with a smaller buffer size. When mixed with VBR traffic, the fuzzy logic control scheme achieves higher efficiency with lower cell loss.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.80-83
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• 2003

A Genetic algorithm is a searching algorithm that based on the law of the survival of the fittest. Multi-population Genetic Algorithms are a modified form of genetic algorithm. Therefore, experience with fuzzy logic and genetic algorithm has proven to be that a combination of them can efficiently make up for their own deficiency. The Multi-population Genetic Algorithms independently evolve subpopulations. In this paper, we suggest a new coding method that independently evolves subpopulations using the fuzzy logic controller. The fuzzy logic controller has applied two fuzzy logic controllers that are implemented to adaptively adjust the crossover rate and mutation rate during the optimization process. The migration scheme in the multi-population genetic algorithms using fuzzy logic controllers is tested for a function optimization problem, and compared with other group migration schemes, therefore the groups migration scheme is then performed. The results demonstrate that the migration scheme in the multi-population genetic algorithms using fuzzy logic controller has a much better performance.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1687-1692
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• 1991

Burrs, created when metals deform plastically, are by-products of most machining processes. The increasing requirements of precision and reliability in manufacturing processes have led to the development of systems for automated deburring. In this paper the motivations and requirements for automated robotic deburring are discussed. Also, the feasibility of automating the deburring process using fuzzy logic controller is investigated. In implementing the fuzzy logic controller, particular attention is paid to the acoustic emission sensing for the characterization and feedback control of the burr removal process. The results of the experiments reveal the rule based control scheme based on fuzzy logics can be a good alternative to traditional control schemes.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.184-187
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• 1996

In this paper, an algorithm for tuning gains of a PID controller is proposed. The proposed algorithm is composed of two stages. The first is a stage for Lyapunov function-based initial stabilization of an overall system and rough tuning gains of the PID controller. The other is that for fine tuning gains of the PID controller. All tunings are performed by using the well-known fuzzy logic-based tuner. The computer simulations are performed to show the validity of the proposed algorithm and results are presented.