• Title/Summary/Keyword: Input and Output Parameters

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Angle-Range-Polarization Estimation for Polarization Sensitive Bistatic FDA-MIMO Radar via PARAFAC Algorithm

  • Wang, Qingzhu;Yu, Dan;Zhu, Yihai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2879-2890
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    • 2020
  • In this paper, we study the estimation of angle, range and polarization parameters of a bistatic polarization sensitive frequency diverse array multiple-input multiple-output (PSFDA-MIMO) radar system. The application of polarization sensitive array in receiver is explored. A signal model of bistatic PSFDA-MIMO radar system is established. In order to utilize the multi-dimensional structure of array signals, the matched filtering radar data can be represented by a third-order tensor model. A joint estimation of the direction-of-departure (DOD), direction-of-arrival (DOA), range and polarization parameters based on parallel factor (PARAFAC) algorithm is proposed. The proposed algorithm does not need to search spectral peaks and singular value decomposition, and can obtain automatic pairing estimation. The method was compared with the existing methods, and the results show that the performance of the method is better. Therefore, the accuracy of the parameter estimation is further improved.

Lane Following Control of Vision Based Mobile Robot Using Neural Network (신경회로망을 이용한 비전기반 이동로봇의 경로추적제어)

  • Yang Seng-Ho;Shin Suk-Hun;Jang Young-Hak;Ryoo Young-Jae
    • Proceedings of the KIPE Conference
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    • 2004.07a
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    • pp.155-158
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    • 2004
  • This paper describes a lane following control of vision based mobile robot that follows guidline. Summation of binarization conversion and image data of vertical axis was used in image processing. As an extraction of specific parameters of lane image, the raw image was converted to the binary data, and the binary data was summerized to the specific data vertically. The specific parameters were made to the inputs of neural network. Summation of image data was used for input of the net, and optimized value of turn angles of learned mobile robot was output. By using neural network algorithm, possibility of mobile robot moving to the target point and following the guidlines quickly and effectively was proved.

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Complex Fuzzy Logic Filter and Learning Algorithm

  • Lee, Ki-Yong;Lee, Joo-Hum
    • The Journal of the Acoustical Society of Korea
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    • v.17 no.1E
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    • pp.36-43
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    • 1998
  • A fuzzy logic filter is constructed from a set of fuzzy IF-THEN rules which change adaptively to minimize some criterion function as new information becomes available. This paper generalizes the fuzzy logic filter and it's adaptive filtering algorithm to include complex parameters and complex signals. Using the complex Stone-Weierstrass theorem, we prove that linear combinations of the fuzzy basis functions are capable of uniformly approximating and complex continuous function on a compact set to arbitrary accuracy. Based on the fuzzy basis function representations, a complex orthogonal least-squares (COLS) learning algorithm is developed for designing fuzzy systems based on given input-output pairs. Also, we propose an adaptive algorithm based on LMS which adjust simultaneously filter parameters and the parameter of the membership function which characterize the fuzzy concepts in the IF-THEN rules. The modeling of a nonlinear communications channel based on a complex fuzzy is used to demonstrate the effectiveness of these algorithm.

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Manipulability Analysis of a Parallel Machine Tool: Application to Optimal Link Parameters Design (병렬형 공작기계의 조작성 해석: 기구부 최적설계에 적용)

  • Kim, Jeom-Goo;Hong, Keum-Shik;Park, Frank-C.;Kim, Jong-Won
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.11
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    • pp.213-223
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    • 1999
  • In this paper, input-output transmission characteristics of the Eclipse, which is a parallel machine tool capable of 5 face rapid machining, are investigated. By splitting the weighted Jacobian matrix into two parts, the force and moment transmission characteristics together with the velocity and angular velocity transmission characteristics are analyzed. A new manipulability measure, which combines the volume of the manipulability ellipsoid and the condition number of the splitted Jcobian matrix, is proposed. Two link parameters, the ratio of upper and lower platforms' radii and the length of a supporting link of the Eclipse, are designed by applying the new manipulability measure derived. Computer simulations are provided.

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A Study on Performance Analysis of Articulated Robot System for Smart Factory Based on Monitoring Simulator

  • Kim, Hee Jin;Kim, Dong-ho;Jung, Kum-jun;Han, Sung-Hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.6_1
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    • pp.889-896
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    • 2020
  • We describe a new approach to the analyze the control performance of robotic manipulator based on the monitoring system. The structure of monitoring simulator is consist of seven modes such as control state mode, coordinate mode, input/output mode, program mode, parameters mode, and track mode. The applied control algorithme consists of an time varying feed-forward and feedback controller. The proposed scheme is simple in structure, fast in computation, and suitable for real-time implimemtation. Moreover, this scheme does not require any accurate dynamic modeling and values of parameters. Performance of the proposed monitoring system is illustrated by simulation and experiment for robot manipulator with six degrees of freedom.

Direct Adaptive Control of Nonminimum Phase Systgems based on PID Structures (PID 구조를 기초로 한 비최소 위상 시스템의 직접적응제어)

  • Kim, Jong-Hwan;Choi, Keh-Kun
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.23 no.6
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    • pp.895-901
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    • 1986
  • This paper presents direct adaptive controllers for single-input single-output nonminimum phase systems based on PID structures. Also, characteristics of these schemes are compared, and convergence properties are considered. In these schemes, controller parameters are estimated from the least-square algorithm and some additional auxiliary parameters are obtained from the proposed polynomial identity which is derived from the pole placement equation and the Bezout identity. The effectiveness of these schemes is demonstrated by computer simulation that has been carried out for a very difficult example.

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Flood Forecasting for Pre-Release of Taech'ong Reservoir (대청댐 예비 방류를 위한 홍수 예보)

  • Lee, Jae-Hyeong;Sim, Myeong-Pil;Jeon, Il-Gwon
    • Water for future
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    • v.26 no.2
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    • pp.99-105
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    • 1993
  • A practical flood forecasting model(FFM) is suggested. The output of the model is the results which the initial condition of meteorological parameters and soil moisture are projected on the future. The physically based station model for rainfall forecasting(RF) and the storage function model for runoff prediction(RP) are adopted respectively. Input variables for FFM are air temperature, pressure, and dew-point temperature at the ground level and the flow at the rising limb(FRL). The constant parameters for FFM are average of optimum values which the past storm events have. Also loss rate of rainfall can predicted by FRL.

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A Sensorless Vector Controller for Induction Motors using an Adaptive Fuzzy Logic

  • Huh, Sung-Hoe;Park, Jang-Hyun;Ick Choy;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.162.5-162
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    • 2001
  • This paper presents a indirect vector control system for induction motors using an adaptive fuzzy logic(AFL) speed estimator. The proposed speed estimator is based on the MRAS(Mode Referece Adaptive System) scheme. In general, the MRAS speed estimation approaches are more simple than any other strategies. However, there are some difficulties in the scheme, which are strong sensitivity to the motor parameters variations and necessity to detune the estimator gains caused by different speed area. In this paper, the AFL speed estimator is proposed to solve the problems. The structure of the proposed AFL is very simple. The input of the AFL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed. Moreover, the back propagation algorithm is combined to adjust the parameters of the fuzzy logic to the most appropriate values during the operating the system. Finally, the validity of the ...

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Analysis of Effects of Sizes of Orifice and Pockets on the Rigidity of Hydrostatic Bearing Using Neural Network Predictor System

  • Canbulut, Fazil;Sinanoglu, Cem;Yildirim, Sahin
    • Journal of Mechanical Science and Technology
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    • v.18 no.3
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    • pp.432-442
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    • 2004
  • This paper presents a neural network predictor for analysing rigidity variations of hydrostatic bearing system. The designed neural network has feedforward structure with three layers. The layers are input layer, hidden layer and output layer. Two main parameter could be considered for hydrostatic bearing system. These parameters are the size of bearing pocket and the orifice dimension. Due to importancy of these parameters, it is necessary to analyse with a suitable optimisation method such as neural network. As depicted from the results, the proposed neural predictor exactly follows experimental desired results.

Developed high performance wireless charging system (고성능 무선충전 시스템 개발)

  • Jo, heol-Hee;Chen, Ya-Fei;Zhang, Hai-Long;Kim, Dong-Hee
    • Proceedings of the KIPE Conference
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    • 2018.07a
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    • pp.368-369
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    • 2018
  • In this paper, a wireless charging system for drones is developed. The system is consists of PFC(Power Factor Correction), Full-Bridge inverter, S-S(Series-Series) resonant circuit and Full-Bridge rectifier. The parameters of the S-S resonant circuit is designed and calculated. According to these parameters and the switching devices, the system model without PFC is setted up with thermal module devices in PSIM. When output voltage is setted to 50[V] and input voltage is changed from 100[V] to 380[V], The efficiency of the system model is measured by simulation.

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