• Title/Summary/Keyword: Hybrid Network

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Hybrid Intelligent Control for Speed Sensorless of SPMSM Drive (SPMSM 드라이브의 속도 센서리스를 위한 하이브리드 지능제어)

  • Lee Jung-Chul;Lee Hong-Gyun;Chung Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.10
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    • pp.690-696
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    • 2004
  • This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

Optimal Allocation Method of Hybrid Active Power Filters in Active Distribution Networks Based on Differential Evolution Algorithm

  • Chen, Yougen;Chen, Weiwei;Yang, Renli;Li, Zhiyong
    • Journal of Power Electronics
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    • v.19 no.5
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    • pp.1289-1302
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    • 2019
  • In this paper, an optimal allocation method of a hybrid active power filter in an active distribution network is designed based on the differential evolution algorithm to resolve the harmonic generation problem when a distributed generation system is connected to the grid. A distributed generation system model in the calculation of power flow is established. An improved back/forward sweep algorithm and a decoupling algorithm are proposed for fundamental power flow and harmonic power flow. On this basis, a multi-objective optimization allocation model of the location and capacity of a hybrid filter in an active distribution network is built, and an optimal allocation scheme of the hybrid active power filter based on the differential evolution algorithm is proposed. To verify the effect of the harmonic suppression of the designed scheme, simulation analysis in an IEEE-33 nodes model and an experimental analysis on a test platform of a microgrid are adopted.

Hybrid position/force controller design of the robot manipulator using neural network (신경 회로망을 이용한 로보트 매니퓰레이터의 Hybrid 위치/힘 제어기의 설계)

  • 조현찬;전홍태;이홍기
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10a
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    • pp.24-29
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    • 1990
  • In this paper ,ie propose a hybrid position/force controller of a robot manipulator using double-layer neural network. Each layer is constructed from inverse dynamics and Jacobian transpose matrix, respectively. The weighting value of each neuron is trained by using a feedback force as an error signal. If the neural networks are sufficiently trained it does not require the feedback-loop with error signals. The effectiveness of the proposed hybrid position/force controller is demonstrated by computer simulation using a PUMA 560 manipulator.

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Sliding mode control based on neural network for the vibration reduction of flexible structures

  • Huang, Yong-An;Deng, Zi-Chen;Li, Wen-Cheng
    • Structural Engineering and Mechanics
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    • v.26 no.4
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    • pp.377-392
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    • 2007
  • A discrete sliding mode control (SMC) method based on hybrid model of neural network and nominal model is proposed to reduce the vibration of flexible structures, which is a robust active controller developed by using a sliding manifold approach. Since the thick boundary layer will reduce the virtue of SMC, the multilayer feed-forward neural network is adopted to model the uncertainty part. The neural network is trained by Levenberg-Marquardt backpropagation. The design objective of the sliding mode surface is based on the quadratic optimal cost function. In course of running, the input signal of SMC come from the hybrid model of the nominal model and the neural network. The simulation shows that the proposed control scheme is very effective for large uncertainty systems.

Robust speed control of DC Motor using Neural network-PID hybrid controller (신경회로망-PID복합형제어기를 이용한 직류 전동기의 강인한 속도제어)

  • Yoo, In-Ho;Oh, Hoon;Cho, Hyun-Sub;Lee, Sung-Soo;Kim, Yong-Wook;Park, Wal-Seo
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.18 no.1
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    • pp.85-89
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    • 2004
  • Robust control for feedback control system is needed according to the highest precision of industrial automation. However, when a neural network feedback control system has an effect of disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem, in this paper, hybrid control method of neural network controller and PID controller is presented. A neural network controller is operated as a main controller, a PID controller is a assistant controller which operates only when some undesirable phenomena occur, e.q., when the error hit the boundary of constraint set. The robust control function of neural network-PID hybrid controller is demonstrated by speed control of Motor.

IDs Assignment of Hybrid Method for Efficient and Secure USN (Ubiquitous Sensor Networks) (효율적인 안전한 유비쿼터스 센서 네트워크를 위한 하이브리드 방식의 아이디 할당)

  • Sung, Soon-Hwa
    • Journal of Internet Computing and Services
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    • v.9 no.6
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    • pp.15-25
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    • 2008
  • Due to the differences between a mobile ad-hoc network and a sensor network, the pre-existing autoconfiguration for a mobile ad-hoc network cannot be simply applied to a sensor network. But. a mechanism is still necessary to assign locally unique addresses to sensor nodes efficiently. This paper proposes a hybrid IDs assignment scheme of local area sensor networks. The IDs assignment scheme of hybrid method combines a proactive IDs assignment with a reactive IDs assignment scheme. The proposed scheme considers efficient communication using reactive IDs assignment, and security for potential attacks using zone-based self-organized clustering with Byzantine Agreement in sensor networks. Thus, this paper has solved the shortage of security due to minimizing network traffic and the problem of repairing the network from the effects of an aberrant node in sensor networks.

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Hybrid MAC Protocol Design for an Underwater Acoustic Network (수중음향통신망을 위한 하이브리드 MAC 프로토콜 설계)

  • Park, Jong-Won;Ko, Hak-Lim;Cho, A-Ra;Yun, Chang-Ho;Choi, Young-Chol;Lim, Yong-Kon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.10
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    • pp.2088-2096
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    • 2009
  • This paper deals with hybrid MAC protocol design for underwater acoustic networks. The proposed MAC protocol has the cluster structure with a master node and slave nodes, and the hybrid network structure that combines a contention free period based on TDMA(Time Division Multiple Access) with a contention period. The suggested MAC protocol has a beacon packet for supervising network, a guard period between time slots for packet collision, time tag for estimation of propagation delay with a master node, the time synchronization of nodes, entering and leaving of network, and the communication method among nodes. In this paper, we adapt the proposed hybrid MAC protocol to AUV network, that is the representative mobile device of underwater acoustic network, and verify this protocol is applicable in real underwater acoustic network environment.

Attitude Control of Helicopter Simulator System using A Hybrid GA-PID WAVENET Controller (Hybrid GA-PID WAVENET 제어기를 이용한 모형 헬리콥터 시스템의 자세 제어)

  • 박두환;지석준;이준탁
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.6
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    • pp.433-439
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    • 2004
  • The Helicopter Simulator System is non-linear and complex. Futhermore, because of absence of its accurate mathematical model, it is difficult to control accurately its attitudes such as elevation angle and azimuth one. Therefore, we proposed a Hybrid GA-PID WAVENET(Genetic Algorithm Proportional Integral Derivative Wavelet Neural Network)control technique to control efficiently these angles. The proposed Hybrid GA-PID WAVENET is made through the following process. First, the WAVENET fundamental functions are defined. And their dilation and translation values are adjusted by GA to construct the optimal WAVENET controller. Secondly, the proportional, integral, and derivative gain coefficients of PR controller are tuned optimally. Finally, WAVENET controller which has a good transient characteristic and GA-PE controller which has a good steady state characteristic is adequately combined in hybrid type. Through the computer simulations, it is proved that the Hybrid GA-PE WAVENET control technique has a more excellent dynamic response than PID control technique and GA-PID one.

Hybrid Model Based Intruder Detection System to Prevent Users from Cyber Attacks

  • Singh, Devendra Kumar;Shrivastava, Manish
    • International Journal of Computer Science & Network Security
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    • v.21 no.4
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    • pp.272-276
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    • 2021
  • Presently, Online / Offline Users are facing cyber attacks every day. These cyber attacks affect user's performance, resources and various daily activities. Due to this critical situation, attention must be given to prevent such users through cyber attacks. The objective of this research paper is to improve the IDS systems by using machine learning approach to develop a hybrid model which controls the cyber attacks. This Hybrid model uses the available KDD 1999 intrusion detection dataset. In first step, Hybrid Model performs feature optimization by reducing the unimportant features of the dataset through decision tree, support vector machine, genetic algorithm, particle swarm optimization and principal component analysis techniques. In second step, Hybrid Model will find out the minimum number of features to point out accurate detection of cyber attacks. This hybrid model was developed by using machine learning algorithms like PSO, GA and ELM, which trained the system with available data to perform the predictions. The Hybrid Model had an accuracy of 99.94%, which states that it may be highly useful to prevent the users from cyber attacks.

Design of the Hybrid Tandem Configuration Automated Guided Vehicle Systems (혼합 직렬형태 자동반송시스템의 설계)

  • 장석화
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.22 no.52
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    • pp.117-139
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    • 1999
  • This paper is concerned about the hybrid tandem configuration as the design of the automated guided vehicle system(AGVs). The hybrid tandem configuration is that the manufacturing system is divided into several non-overlapping zones, workstations of each zone are linked by network configuration including loop. That is, the manufacturing system is divided into several non-overlapping small size networks, and at most two automated guided vehicles can be available in each network. The transit point is located at proper point between adjacent networks. The parts are transported to workstations in other network through the transit points. One of the objective functions in dividing into the hybrid tandem configuration is to minimize the maximum travel time of the divided networks, and other is to minimize the total travel distance of parts moved to workstations in other networks for the next processing. The model formulation is presented, and a numerical example is shown. Also, the performances of system for the hybrid tandem, tandem and network configuration are compared through the simulation. The results of this research will contribute to the development of material handling systems in the manufacturing system. Also, it will be applied in determining the transportation area of transportation vehicles and the number and size of the transportation fleet in the transportation problem of logistics management.

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