• 제목/요약/키워드: Parameter adaptive algorithm

검색결과 438건 처리시간 0.031초

Adaptive Vector Control for Induction Motor Using Block Adaptive Algorithm (블록 적응알고리즘을 이용한 유도전동기 적응벡터제어)

  • 박영산;조성훈;배철오;이성근;김윤식
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 한국해양정보통신학회 1999년도 춘계종합학술대회
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    • pp.324-329
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    • 1999
  • This paper proposes new torque control of an induction motor, which is robust against time verying parameters. The control is based on adaptive vector control with serial block adaptive algorithm. Motor parameters used to estimates slip frequency and torque. Frequency mismatch in the control system detrimentally affects slip frequency estimation and torque response. In order to compensate for degradation of the responses an adaptive identifier for the magnetizing inductance and the secondary time constand is introduced. adaptive vector control system consisted of two subsystems, a vector control system realized on synchronous frame and a parameter identification system on stationary frame. the effectiveness of the proposed method was verified by some digital simulations.

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The Design of Model Reference Adaptive Controller via Block Pulse Functions (블럭펄스 함수를 이용한 기준 모델 적응 제어기 설계)

  • Kim, Jin-Tae;Kim, Tai-Hoon;Lee, Myung-Kyu;Ahn, Doo-Soo
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • 제51권1호
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    • pp.1-7
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    • 2002
  • This paper proposes a algebraic parameter determination of MRA(Model Reference Adaptive Control) controller using block Pulse functions and block Pulse function's differential operation. Generally, adaption is performed by solving differential equations which describe adaptive low for updating controller parameter. The proposes algorithm transforms differential equations into algebraic equation, which can be solved much more easily inn a recursive manner. We believe that proposes methods are very attractive and proper for parameter estimation of MRAC controller on account of its simplicity and computational convergence.

Design of Adaptive PID Controller with Fuzzy Model (퍼지 모델을 이용한 적응 PID 제어기 설계)

  • 김종화;이원창;강근택
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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    • pp.84-87
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    • 2002
  • This paper presents an adaptive PID control scheme with fuzzy model for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model was used to estimate the error of control input, and the parameter of PID controller was adapted from the error The parameter of TSK fuzzy model was also adapted to plant by comparing the activity output of plant and model output. PID controller which was adapted the uncertainty of nonlinear plant and the change of parameter can be designed by using the presented method. The usefullness of algorithm which was proposed by the simulation of several nonlinear system was also certificated.

Transcoding Algorithm for AMR and EVRC Vocoders Via Direct Parameter Transformation (AMR과 EVRC 음성부호화기를 위한 파라미터 직접 변환 방식의 상호부호화 알고리듬)

  • Lee, Sun-Il;Yu, Chang-Dong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • 제39권6호
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    • pp.696-708
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    • 2002
  • In this paper, a novel transcoding algorithm for the Adaptive Multi Rate(AMR) and the Enhanced Variable Rate Codec(EVRC) vocoders via direct parameter transformation is proposed. In contrast to the conventional tandem transcoding algorithm, the proposed algorithm converts the parameters of one coder to the other without going through the decoding and encoding processes. The proposed algorithm consists of the parameter decoding, frame classification, mode decision, and transcoders for two frame types. The transcoders convert the parameters such as LSP, frame energy, pitch delay for the adaptive codebook, fixed codebook vector, and codebook gains. Evaluation results show that while exhibiting better computational and delay characteristics, the proposed algorithm produces equivalent speech quality to that produced by the tandem transcoding algorithm.

Development of Self-Adaptive Meta-Heuristic Optimization Algorithm: Self-Adaptive Vision Correction Algorithm (자가 적응형 메타휴리스틱 최적화 알고리즘 개발: Self-Adaptive Vision Correction Algorithm)

  • Lee, Eui Hoon;Lee, Ho Min;Choi, Young Hwan;Kim, Joong Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • 제20권6호
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    • pp.314-321
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    • 2019
  • The Self-Adaptive Vision Correction Algorithm (SAVCA) developed in this study was suggested for improving usability by modifying four parameters (Modulation Transfer Function Rate, Astigmatic Rate, Astigmatic Factor and Compression Factor) except for Division Rate 1 and Division Rate 2 among six parameters in Vision Correction Algorithm (VCA). For verification, SAVCA was applied to two-dimensional mathematical benchmark functions (Six hump camel back / Easton and fenton) and 30-dimensional mathematical benchmark functions (Schwefel / Hyper sphere). It showed superior performance to other algorithms (Harmony Search, Water Cycle Algorithm, VCA, Genetic Algorithms with Floating-point representation, Shuffled Complex Evolution algorithm and Modified Shuffled Complex Evolution). Finally, SAVCA showed the best results in the engineering problem (speed reducer design). SAVCA, which has not been subjected to complicated parameter adjustment procedures, will be applicable in various fields.

Bayesian Estimation of the Two-Parameter Kappa Distribution

  • Oh, Mi-Ra;Kim, Sun-Worl;Park, Jeong-Soo;Son, Young-Sook
    • Communications for Statistical Applications and Methods
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    • 제14권2호
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    • pp.355-363
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    • 2007
  • In this paper a Bayesian estimation of the two-parameter kappa distribution was discussed under the noninformative prior. The Bayesian estimators are obtained by the Gibbs sampling. The generation of the shape parameter and scale parameter in the Gibbs sampler is implemented using the adaptive rejection Metropolis sampling algorithm of Gilks et al. (1995). A Monte Carlo study showed that the Bayesian estimators proposed outperform other estimators in the sense of mean squared error.

Effect of Initial Value Setting on Convergence Characteristics and Margin of Step Parameters in an Adaptive Ultrasonic Beamforming System using LMS Algorithm (LMS 알고리즘을 이용하는 적응형 초음파 빔포밍 시스템에서 초기치 설정이 수렴 특성과 스텝 파라미터의 여유도에 미치는 영향)

  • Kwang-Chol Chae;Ki-Ryang Cho
    • The Journal of the Korea institute of electronic communication sciences
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    • 제18권2호
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    • pp.241-250
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    • 2023
  • In this paper, when using the LMS algorithm for adaptive ultrasonic beamforming system, the effect of initial value setting on the margin of step parameters was studied. To this end, quasi-ideal beams, rotational beams with arbitrarily set beam widths were used as examples. In the numerical simulations, an arbitrary initial value(the number of sound sources fixed to any number) was set in the ultrasonic beamforming system, and the margin of the step parameter and convergence characteristics thereof were compared.

Indirect Adaptive Regulator Design Based on TSK Fuzzy Models

  • Park Chang-Woo;Choi Jun-Hyuk;Sung Ha-Gyeong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권1호
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    • pp.52-57
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    • 2006
  • In this paper, we have proposed a new adaptive fuzzy control algorithm based on Takagi-Sugeno fuzzy model. The regulation problem for the uncertain SISO nonlinear system is solved by the proposed algorithm. Using the advanced stability theory, the stability of the state, the control gain and the parameter approximation error is proved. Unlike the existing feedback linearization based methods, the proposed algorithm can guarantee the global stability in the presence of the singularity in the inverse dynamics of the plant. The performance of the proposed algorithm is demonstrated through the problem of balancing and swing-up of an inverted pendulum on a cart.

Design of Fuzzy Adaptive IIR Filter in Direct Form (직접형 퍼지 적응 IIR 필터의 설계)

  • 유근택;배현덕
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • 제39권4호
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    • pp.370-378
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    • 2002
  • Fuzzy inference which combines numerical data and linguistic data has been used to design adaptive filter algorithms. In adaptive IIR filter design, the fuzzy prefilter is taken account, and applied to both direct and lattice structure. As for the fuzzy inference of the fuzzy filter, the Sugeno's method is employed. As membership functions and inference rules are recursively generated through neural network, the accuracy can be improved. The proposed adaptive algorithm, adaptive IIR filter with fuzzy prefilter, has been applied to adaptive system identification for the purposed of performance test. The evaluations have been carried out with viewpoints of convergence property and tracking properties of the parameter estimation. As a result, the faster convergence and the better coefficients tracking performance than those of the conventional algorithm are shown in case of direct structures.

Adaptive fuzzy sliding mode control for nonlinear systems (비선형 계통에 대한 적응 퍼지 슬라이딩 모드 제어)

  • 서삼준;서호준;김동식
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.684-688
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    • 1996
  • In this paper, to overcome drawbacks of variable structure control system a self-tuning fuzzy sliding mode control algorithm using gradient descent method is proposed. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties in the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to a one-degree of freedom robot arm. The results show that both alleviation of chattering and performance are achieved.

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