• Title/Summary/Keyword: Extended Model

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Speed Sensorless Vector Control of Induction Motor Using a Reduced-model Extended Kalman Filter (축소모델 확장 칼만필터를 이용한 유도전동기의 센스리스 벡터제어)

  • Heo, Jong-Myung;Seo, Young-Soo
    • Proceedings of the KIEE Conference
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    • 2001.07b
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    • pp.1141-1143
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    • 2001
  • This paper presents a detailed study of the reduced-model extended Kalman filter(EKF) for estimating the rotor speed of an induction motor drive. The general structure of the Kalman filter is reviewed and the various system vectors and matrices are defined. By including the rotor speed as a state variable, the EKF equations are established from a discrete two axis model of the three-phase induction motor, using the software MATLAB/Simulink, simulation of the EKF speed estimation algorithm is carried out for an induction motor drive with indirect vector control.

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Equivalent nonlinear error model of SDINS using quaternion (쿼터니언을 이용한 SDINS의 등가 비선형 오차모델)

  • Yoo, Myung-Jong;Jeon, Chang-Bae;Park, Jun-Pyo;Yoo, Jun
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.864-866
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    • 1996
  • The attitude error is expressed using four kinds of quaternion errors. And the explicit relation equations between them are derived four kinds of nonlinear error models of SDINS using the their explicit relation are also proposed for a nonlinear filter which may be available for a system in the presence of a large attitude error the concept of the proposed nonlinear error model is applied to the velocity aided SDINS using a linear Kalman filter and an extended Kalman filter the simulation results reveal a improvement of performance using the nonlinear error model.

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A New Learning Algorithm for Neuro-Fuzzy Modeling Using Self-Constructed Clustering

  • Kim, Sung-Suk;Kwak, Keun-Chang;Kim, Sung-Soo;Ryu, Jeong-Woong
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1254-1259
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    • 2005
  • In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

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A Defense Interoperability Evaluation Model for Weapon Systems Considering Technical and Non-Technical Attributes (기술 및 비 기술 요소를 고려한 무기체계 상호운용성 평가 모델)

  • Han, Ik-Joon;Bang, Choon-Sik;Yoon, Gwang-Sik;Cheon, Jae-Young;Kim, Hyung-Gyoon;Cho, Byoung-In
    • Journal of the Korea Institute of Military Science and Technology
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    • v.12 no.4
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    • pp.424-436
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    • 2009
  • In the modern warfield, as the defense systems has been digitalized, intelligent, and working with network, the importance of interoperability among the systems has been also increasing. KMND(Korean Ministry of National Defense) has developed and used the SITES(Systems Interoperability Test & Evaluation System) based on Korean LISI(Levels of Information Systems Interoperability). SITES had been developed in order to evaluate the interoperability among information systems from the viewpoint of technical attributes. In this paper, we propose the extended interoperability evaluation model which can be applied not only the information systems, but also the weapon systems. Moreover, the extended interoperability evaluation model also includes the consideration of non-technical attributes.

Adaptive Control of Space Robot in Inertia Space (Inertia Space에서 우주 로봇의 적응제어)

  • Lee, Ju-Jang
    • Proceedings of the KIEE Conference
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    • 1992.07a
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    • pp.381-385
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    • 1992
  • In this paper, dynamic modeling and adaptive control problems for a space robot system are discussed. The space robot consist of a robot manipulator mounted on a free-floating base where no attitude control is applied. Using an extended robot model, the entire space robot can be viewed as an under-actuated robot system. Based on nonlinear control theory, the extended space robot model can then be decomposed into two subsystems: one is input-output exactly linearizable, and the other is unlinearizable and represents an internal dynamics. With this decomposition, a normal form-augmentation approach and an augmented state-feedback control are proposed to facilitate the design of adaptive control for the space robot system against parameter uncertainty, unknown dynamics and unmodeled payload in space applications. We demonstrate that under certain conditions, the entire space robot can be represented as a full-actuated robot system to avoid the inclusion of internal dynamics. Based on the dynamic model, we propose an adaptive control scheme using Cartesian space representation and demonstrate its validity and design procedure by a simulation study.

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Timed fuzzy petri net model for fuzzy control model (퍼지 제어를 위한 시간형 퍼지 페트리넷 모델)

  • 윤정모
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.34C no.5
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    • pp.9-18
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    • 1997
  • The petri net is a graphic model which is adaptable in modeling a complex concurrent parallel ssystem, and it is widely used in the fields of industrial enginering, computer science, electric engineeringand chemistry. Recently, the net is applied to the communication protocol, and extended to represent complex systems. There are several extended petri nets named as TPN (timed petri net), SPN (stochastic petri net), FPN(fuzzy petri net) and TFPN(timed fuzzy petri net). Accodingly, this SPN (stochastic petri net), FPN (fuzzy petri net) and TFPN(timed fuzzy petri net). Accodingly, this paper proposes an advanced communication protocol modeling method using the fuzzy value of the transition and firing delay time as the arguments of the function. The proposed method can produce clearer firing rules, and it is supposed to be used to design and analyse communication protocols in great effection.

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H-infinity Control System Design for a Quad-rotor (쿼드로터의 H-infinity 제어시스템 설계)

  • Kang, Taesam;Yoon, Kwang Joon;Ha, Tae-Hyun;Lee, Gigun
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.1
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    • pp.14-20
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    • 2015
  • This paper describes the design of a robust H-infinity attitude controller for a quad-rotor. The linear model of a quad-rotor was estimated using PEM (Prediction Error Minimization) method with experimental input and output data. To design an attitude controller, an extended plant was constructed by adjusting several uncertainties and weighting functions. An H-infinity controller was obtained by applying H-infinity methodology to the extended plant. Through frequency-domain analysis, it was shown that the designed controller can overcome uncertainties up to 75% of the plant model. The performance and robustness of the controller were verified through time-domain simulation.

An Empirical Study on Characteristics of Homenetwork Affecting the Perceived Value of Apartment (홈네트워크의 특성이 아파트의 가치인식에 미치는 영향에 관한 실증적 연구)

  • Kang, Hyoung-Mo;Gim, Gwang-Yong;Kim, Shin-Kon;Kim, Jong-Kon
    • Journal of Information Technology Services
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    • v.6 no.3
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    • pp.27-46
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    • 2007
  • Korean homenetwork industry is now faced with problems like low profitability and unclear commercialilzation. In particular, low awareness of homenetwork usefulness is one of the main reasons why homenetwork industry is not developed. Therefore, this study tried to find what kinds of characteristics of homenetwork affected the value of apartment and how. we conducted a survey of residents of apartment with homenetwork installed in it. Surveyed data was analyzed based on the model of extended Technology Acceptance Model(TAM) including perceived enjoyment and perceived trust as new factors. The research result showed that all factors involved in suggested model had positive effects on the behavioral intention of using homenetwork and the value of apartment. Most importantly, homenetwork user's behavioral intention increased perceived housing value of the apartment. The research result can be used in explaining the advantage of homenetwork to the residence of apartment as well as in designing the homenwtwork install of apartment.

A New Learning Algorithm of Neuro-Fuzzy Modeling Using Self-Constructed Clustering

  • Ryu, Jeong-Woong;Song, Chang-Kyu;Kim, Sung-Suk;Kim, Sung-Soo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.2
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    • pp.95-101
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    • 2005
  • In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

Nonparametric test procedures the changepoint problem with multiple observations (다중자료를 갖는 변화시점 모형에서의 비모수적인 검정법)

  • 김경무
    • The Korean Journal of Applied Statistics
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    • v.4 no.1
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    • pp.33-45
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    • 1991
  • In the analysis of changepoint model the situation where single observation is taken at each time point has been considered. In an effort to extend this to the general situation, we may consider the changepoint model with more than one observation at each time point. These tests are developed without assuming any particular form for the underlying distribution, we propose the one-sided and two-sided nonparametric tests by extending the tests that have been considered in the changepoint model with single observation at each time point and obtain their asymptotic null distributions. We compare the empirical powers among the extended changepoint tests under one-sided or two-sided alternatives. We also compare the powers of the extended changepoint tests with those of the original test via the Monte Carlo simulation.

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