• Title/Summary/Keyword: Input/Output algorithm

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Input-output linearization of nonlinear systems via dynamic feedback (비선형 시스템의 동적 궤한 입출력 선형화)

  • 김용민;이홍기;전홍태
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.4
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    • pp.40-57
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    • 1998
  • The dynamic feedback is well-known to be much more powerful tool compensating the ononlinearity in nonlinear control system than the static one. In this paepr we consider the input-output linearization problem via a regular dynamic feedback which is to make linear the input-dependent part of the output sufficient conditions for the existence of such a regular dynamic feedback control law, after defining the structure algorithm for a dynamic feedback.

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A Clustering Algorithm using Self-Organizing Feature Maps (자기 조직화 신경망을 이용한 클러스터링 알고리듬)

  • Lee, Jong-Sub;Kang, Maing-Kyu
    • Journal of Korean Institute of Industrial Engineers
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    • v.31 no.3
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    • pp.257-264
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    • 2005
  • This paper suggests a heuristic algorithm for the clustering problem. Clustering involves grouping similar objects into a cluster. Clustering is used in a wide variety of fields including data mining, marketing, and biology. Until now there are a lot of approaches using Self-Organizing Feature Maps(SOFMs). But they have problems with a small output-layer nodes and initial weight. For example, one of them is a one-dimension map of k output-layer nodes, if they want to make k clusters. This approach has problems to classify elaboratively. This paper suggests one-dimensional output-layer nodes in SOFMs. The number of output-layer nodes is more than those of clusters intended to find and the order of output-layer nodes is ascending in the sum of the output-layer node's weight. We can find input data in SOFMs output node and classify input data in output nodes using Euclidean distance. We use the well known IRIS data as an experimental data. Unsupervised clustering of IRIS data typically results in 15 - 17 clustering error. However, the proposed algorithm has only six clustering errors.

Performance analysis of a loss priority control scheme in an input and output queueing ATM switch (입출력 단에 버퍼를 가지는 ATM 교환기의 손실우선순위 제어의 성능 분석)

  • 이재용
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.6
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    • pp.1148-1159
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    • 1997
  • In the broadband integrated service digital networks (B-ISDN), ATM switches hould be abld to accommodate diverse types of applications ith different traffic characteristics and quality ddo services (QOS). Thus, in order to increase the utilization of switches and satisfy the QOS's of each traffic type, some types of priority control schemes are needed in ATM switches. In this paper, a nonblocking input and output queueing ATm switch with capacity C is considered in which two classes of traffics with different loss probability constraints are admitted. 'Partial push-out' algorithm is suggested as a loss priority control schemes, and the performance of this algorithm is analyzed when this is adopted in input buffers of the switch. The quque length distribution of input buffers and loss probabilities of each traffic are obtained using a matrix-geometric solution method. Numerical analysis and simulation indicate that the utilization of the switch with partial push-out algorithm satisfying the QOS's of each traffic is much higher than that of the switch without control. Also, the required buffer size is reduced while satisfying the same QOS's.

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A Study on Minimization Algorithm for ESOP of Multiple - Valued Function (다치 논리 함수의 ESOP 최소화 알고리즘에 관한 연구)

  • Song, Hong-Bok
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.7
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    • pp.1851-1864
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    • 1997
  • This paper presents an algorithm simplifying the ESOP function by several rules. The algorithm is repeatedly performing operations based on the state of each terms by the product transformation operation of two functions and thus it is simplifying the ESOP function through the reduction of the product terms. Through the minimization of the product terms of the multi-valued input binary multi-output function, an optimization of the input has been done using EXOR PLA with input decoder. The algorithm when applied to four valued arithmetic circuit has been used for a EXOR logic circuit design and the two bits input decoder has been used for a EXOR-PLA design. It has been found from a computer simulation(IBM PC486) that the suggested algorithm can reduce the product terms of the output function remarkably regardless of the number of input variables when the variable AND-EXOR PLA is applied to the poperation circuit.

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A Learning Algorithm for Optimal Fuzzy Control Rules (최적의 퍼지제어규칙을 얻기위한 퍼지학습법)

  • Chung, Byeong-Mook
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.2
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    • pp.399-407
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    • 1996
  • A fuzzy learning algorithm to get the optimal fuzzy rules is presented in this paper. The algorithm introduces a reference model to generate a desired output and a performance index funtion instead of the performance index table. The performance index funtion is a cost function based on the error and error-rate between the reference and plant output. The cost function is minimized by a gradient method and the control input is also updated. In this case, the control rules which generate the desired response can be obtained by changing the portion of the error-rate in the cost funtion. In SISO(Single-Input Single- Output)plant, only by the learning delay, it is possible to experss the plant model and to get the desired control rules. In the long run, this algorithm gives us the good control rules with a minimal amount of prior informaiton about the environment.

A Study on Dynamic Modeling of Photovoltaic Power Generator Systems using Probability and Statistics Theories (확률 및 통계이론 기반 태양광 발전 시스템의 동적 모델링에 관한 연구)

  • Cho, Hyun-Cheol
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.7
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    • pp.1007-1013
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    • 2012
  • Modeling of photovoltaic power systems is significant to analytically predict its dynamics in practical applications. This paper presents a novel modeling algorithm of such system by using probability and statistic theories. We first establish a linear model basically composed of Fourier parameter sets for mapping the input/output variable of photovoltaic systems. The proposed model includes solar irradiation and ambient temperature of photovoltaic modules as an input vector and the inverter power output is estimated sequentially. We deal with these measurements as random variables and derive a parameter learning algorithm of the model in terms of statistics. Our learning algorithm requires computation of an expectation and joint expectation against solar irradiation and ambient temperature, which are analytically solved from the integral calculus. For testing the proposed modeling algorithm, we utilize realistic measurement data sets obtained from the Seokwang Solar power plant in Youngcheon, Korea. We demonstrate reliability and superiority of the proposed photovoltaic system model by observing error signals between a practical system output and its estimation.

A Scheduling Algorithm for Input-Queued Switches (입력단에 버퍼가 있는 라우터를 위한 일정계획 방안)

  • 주운기;이형섭;이형호
    • Proceedings of the IEEK Conference
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    • 2000.11a
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    • pp.445-448
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    • 2000
  • This paper considers a scheduling algorithm for high-speed routers, where the router has an N x N port input-queued switch and the input queues are composed of N VOQ(Virtual Output Queue)s at each input port. The major concern of the paper is on the scheduling mechanism for the router. The paper discusses the preferred levels of the performance measures and then develope a non-linear mixed integer programming. Additionally, the paper suggests a heuristic scheduling algorithm for efficient and effective switching.

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Implementation of Self-Adaptative System using Algorithm of Neural Network Learning Gain (신경회로망 학습이득 알고리즘을 이용한 자율적응 시스템 구현)

  • Lee, Sung-Su
    • Proceedings of the KIEE Conference
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    • 2006.07d
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    • pp.1868-1870
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    • 2006
  • Neural network is used in many fields of control systems, but input-output patterns of a control system are not easy to be obtained and by using as single feedback neural network controller. And also it is difficult to get a satisfied performance when the changes of rapid load and disturbance are applied. To resolve those problems, this paper proposes a new algorithm which is the neural network controller. The new algorithm uses the neural network instead of activation function to control object at the output node. Therefore, control object is composed of neural network controller unifying activation function, and it supplies the error back propagation path to calculate the error at the output node. As a result, the input-output pattern problem of the controller which is resigned by the simple structure of neural network is solved, and real-time learning can be possible in general back propagation algorithm. Application of the new algorithm of neural network controller gives excellent performance for initial and tracking response and it shows the robust performance for rapid load change and disturbance. The proposed control algorithm is implemented on a high speed DSP, TMS320C32, for the speed of 3-phase induction motor. Enhanced performance is shown in the test of the speed control.

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A genetic algorithm for determining the optimal operating policies in an integrated-automated manufacturing system (통합자동생산시스템에서 최적운영방안 결정을 위한 유전자 알고리즘의 개발)

  • 임준묵
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 1999.05a
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    • pp.145-153
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    • 1999
  • We consider a Direct Input Output Manufacturing System(DIOMS) which has a munber of machine centers placed along a built-in Automated Storage/Retrieval System(AS/RS). The Storage/Retrieval (S/R) machine handles parts placed on pallets for the machine centers located at either one or both sides of the As/Rs. This report studies the operational aspect of DIOMS and determines the optimal operating policy by combining computer simulation and genetic algorithm. The operational problem includes: input sequencing control, dispatching rule of the S/R machine, machine center-based part type selection rule, and storage assignment policy. For each operating policy, several different policies are considered based on the known research results. In this report, using the computer simulation and genetic algorithm we suggest a method which gives the optimal configuration of operating policies within reasonable computation time.

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Output Voltage Control of Z-Source Inverter by the Detection of the Input DC Voltage and Z-Network Capacitor Voltage (입력 직류 전압과 Z-네트워크 커패시터 전압 검출에 의한 Z-소스 인버터의 출력 전압 제어)

  • Kim, Se-Jin;Jung, Young-Gook;Lim, Young-Cheol;Choi, Joon-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.8
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    • pp.1515-1522
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    • 2011
  • This paper proposes the algorithm for the output AC voltage control of Z-source inverter by the detection of the input DC voltage and Z-network capacitor voltage. The actual modulation index of the proposed method is detected by the capacitor voltage in Z-network and input DC voltage of three-phase Z-source inverter. Control modulation index for the output voltage control is calculated by the detected actual modulation index and reference modulation index. And, calculated control modulation index is applied to the modified space vector modulation (SVM) for control the output voltage of Z-source inverter. To verify the validity of the proposed method, PSIM simulation was achieved and a DSP controlled 1[kW] three-phase Z-source inverter was producted. The simulation and experiment were performed under the condition that the load was changed in case of the constant input DC voltage and the input DC voltage was changed in case of the load was constant. As a result, we could know that the output phase voltage of Z-source inverter followed to the reference voltage 70[VRMS] despite the load or the input DC voltage were suddenly changed.