• 제목/요약/키워드: sums of products

검색결과 48건 처리시간 0.021초

디지털 시그널 프로세서를 이용한 스카라 로봇의 적응-신경제어기 설계 (Design of Adaptive-Neuro Controller of SCARA Robot Using Digital Signal Processor)

  • 한성현
    • 한국생산제조학회지
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    • 제6권1호
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    • pp.7-17
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    • 1997
  • During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

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DSP(TMS320C50) 칩을 사용한 산업용 로봇의 적응-신경제어기의 실현 (Implementation of the Adaptive-Neuro Controller of Industrial Robot Using DSP(TMS320C50) Chip)

  • 김용태;정동연;한성현
    • 한국공작기계학회논문집
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    • 제10권2호
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    • pp.38-47
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    • 2001
  • In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

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TMS320C30칩을 사용한 산업용 로봇의 적응-신경제어기 설계 (The Adaptive-Neuro Controller Design of Industrial Robot Using TMS320C3X Chip)

  • 하석흥
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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    • pp.162-169
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    • 1999
  • In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital Signal Processors. Digital signal processors DSPs. are micro-processors that are particularly developed for variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a biable computatinal tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for implementation of real-time control of robot system by the simulation and experiment.

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중국(中國) 절강성(浙江省) 영파지역(寧波地域) 남성(男性)의 체형연구(體形硏究) (Body Types of Adult Males in the Ningbo Area of Zhejiang Province in China)

  • 심부자
    • 패션비즈니스
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    • 제11권1호
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    • pp.108-124
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    • 2007
  • Body measurement was held for the subjects of Chinese adult males in their 20s through 40s residing in the Ningbo area of Zhejiang Province in order to provide body type information and raise the fit of clothing products for the advancement into the Chinese market. The following sums up the analysis of body types based on body measurement: 1. Seven factors to compose body types were produced from the analysis of males in their 20s, explaining 76.07% of variables and representing 3 types according to cluster analysis. Type 1 was H-b and appeared as much as 32.14%. Type 2, semi X-d, was 40.81%, while Type 3, A-i, had 27.04%. 2. Eight body type composing factors were extracted from the analysis of men in their 30s and 40s. The factors explained 76.77% of all the variables and represented 4 types according to cluster analysis. Type 1, H-d, had the appearance rate of 18.47%; Type 2, H-b, 40.84%; Type 3, Y-i, 27.71%; and Type 4, semi X-s, 11.95%.

확장된 2-큐브 행렬을 이용한 부울 분해식 산출 (A Boolean Factorization Using an Extended Two-cube Matrix)

  • 권오형;오임걸
    • 한국컴퓨터산업학회논문지
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    • 제8권4호
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    • pp.229-236
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    • 2007
  • 분해식은 SOP 형태의 논리식들이 논리합과 논리곱으로 반복해서 표현된 논리식이다. 분해식을 산출하는 과정은 논리식 내에 있는 공통식을 찾아 인수분해를 반복하는 과정이다. 분해식의 형태에 따라 대수 분해식과 부울 분해식으로 구분되며, 리터럴 개수를 기준으로 부울 분해식이 대수 분해식보다 간략화된 형태를 갖는다. 본 논문은 부울 분해식 산출 방법을 제안한 것이다. 제안하는 방법은 주어진 논리식에서 2개의 큐브를 선택하여 제수/몫 쌍들을 산출한다. 이 때, 2개의 큐브로 구성된 몫에 공통인수를 남겨두어 확장 제수/몫 쌍들을 산출하고 후에 몫/몫 쌍들을 산출하도록 하였다. 산출된 제수/몫 쌍과 확장 제수/몫 쌍, 몫/몫 쌍들을 이용하여 부울 분해식 산출 을 위한 행렬을 산출하고, 행렬 커버링을 통해 부울 분해식을 산출하는 방법을 제시한다.

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SAVITZKY-GOLAY DERIVATIVES : A SYSTEMATIC APPROACH TO REMOVING VARIABILITY BEFORE APPLYING CHEMOMETRICS

  • Hopkins, David W.
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1041-1041
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    • 2001
  • Removal of variability in spectra data before the application of chemometric modeling will generally result in simpler (and presumably more robust) models. Particularly for sparsely sampled data, such as typically encountered in diode array instruments, the use of Savitzky-Golay (S-G) derivatives offers an effective method to remove effects of shifting baselines and sloping or curving apparent baselines often observed with scattering samples. The application of these convolution functions is equivalent to fitting a selected polynomial to a number of points in the spectrum, usually 5 to 25 points. The value of the polynomial evaluated at its mid-point, or its derivative, is taken as the (smoothed) spectrum or its derivative at the mid-point of the wavelength window. The process is continued for successive windows along the spectrum. The original paper, published in 1964 [1] presented these convolution functions as integers to be used as multipliers for the spectral values at equal intervals in the window, with a normalization integer to divide the sum of the products, to determine the result for each point. Steinier et al. [2] published corrections to errors in the original presentation [1], and a vector formulation for obtaining the coefficients. The actual selection of the degree of polynomial and number of points in the window determines whether closely situated bands and shoulders are resolved in the derivatives. Furthermore, the actual noise reduction in the derivatives may be estimated from the square root of the sums of the coefficients, divided by the NORM value. A simple technique to evaluate the actual convolution factors employed in the calculation by the software will be presented. It has been found that some software packages do not properly account for the sampling interval of the spectral data (Equation Ⅶ in [1]). While this is not a problem in the construction and implementation of chemometric models, it may be noticed in comparing models at differing spectral resolutions. Also, the effects on parameters of PLS models of choosing various polynomials and numbers of points in the window will be presented.

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기업의 기술개발(R&D)중시 전략에 관한 연구 (A Study on Improvement of a company's R&D Strategy)

  • 구현서
    • 한국컴퓨터정보학회논문지
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    • 제4권2호
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    • pp.147-154
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    • 1999
  • 기업발전에 있어 R&D부문의 연구개발과 그에 따른 기술개발에 대한 중요도는 그 기업의 장래까지 결정하는 대단히 중요한 고려사항임을 감안할 때 R&D에 대한 투자 및 전략적인 우선권부여는 절대적이라 하겠다. 이 글에서는 무엇보다도 제품기술개발에 대한 기업내의 각 부문별 시너지 전략, 품질전략, 제품관련이론전략, 및 관련마케팅전략등의 중요성에 대해 재인식하고 기업에 있어 무한경쟁시대의 21세기를 준비하는데 보탬이 되고자 한다.

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ON THE DIRECT PRODUCTS AND SUMS OF PRESHEAVES

  • PARK, WON-SUN
    • 호남수학학술지
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    • 제1권1호
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    • pp.21-25
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    • 1979
  • Abelian군(群)의 presheaf에 관한 직적(直積)과 직화(直和)를 Category 입장에서 정의(定義)하고 presheaf $F_{\lambda}\;({\lambda}{\epsilon}{\Lambda})$들의 두 직적(直積)(또는 直和)은 서로 동형적(同型的) 관계(關係)에 있으며, 특히 ${\phi}:X{\rightarrow}Y$가 homeomorphism이라 하고 ${\phi}_*F$를 X상(上)의 presheaf F의 direct image이라 하면 (1) $({\phi}_*F, \;{\phi}_*(f_{\lambda})_{{\lambda}{\epsilon}{\Lambda}})$$({\phi}_*F_{\lambda})_{{\lambda}{\epsilon}{\Lambda}}$의 직적(直積)일 때 오직 그때 한하여 $(F,\;(f_{\lambda})_{{\lambda}{\epsilon}{\Lambda}})$$(F_{\lambda})_{{\lambda}{\epsilon}{\Lambda}})$의 직적(直積)이다. (2) $({\phi}_*F,\;{\phi}_*(l_{\lambda})_{{\lambda}{\epsilon}{\Lambda}})$$({\phi}_*F_{\lambda})_{{\lambda}{\epsilon}{\Lambda}}$의 직화(直和)일 때 오직 그때 한하여 $(F,\;(l_{\lambda})_{{\lambda}{\epsilon}{\Lambda}})$$(F_{\lambda})_{{\lambda}{\epsilon}{\Lambda}})$의 직화(直和)이다. Let $(F_{\lambda})_{{\lambda}{\epsilon}{\Lambda}})$ be an indexed set of presheaves of abelian group on topological space X. We can define the cartesian product $$\prod_{{\lambda}{\epsilon}{\Lambda}}\;F_{\lambda}$$ of $(F_{\lambda})_{{\lambda}{\epsilon}{\Lambda}})$ by $$(\prod_{{\lambda}{\epsilon}{\Lambda}}\;F_{\lambda})(U)=\prod_{{\lambda}{\epsilon}{\Lambda}}(F_{\lambda}(U))$$ for U open in X $${\rho}_v^u:\;(\prod_{{\lambda}{\epsilon}{\Lambda}}\;F_{\lambda})(U){\rightarrow}(\prod_{{\lambda}{\epsilon}{\Lambda}}\;F_{\lambda})(V)((s_{\lambda})_{{\lambda}{\epsilon}{\Lambda}}{\rightarrow}(_{\lambda}{\rho}_v^u(s_{\lambda}))_{{\lambda}{\epsilon}{\Lambda}})$$ for $V{\subseteq}U$ open in X where $_{\lambda}{\rho}^U_V$ is a restriction of $F_{\lambda}$, And we have natural presheaf morphisms ${\pi}_{\lambda}$ and ${\iota}_{\lambda}$ such that ${\pi}_{\lambda}(U):\;({\prod}_\;F_{\lambda})(U){\rightarrow}F_{\lambda}(U)((s_{\lambda})_{{\lambda}{\epsilon}{\Lambda}}{\rightarrow}s_{\lambda})$ ${\iota}_{\lambda}(U):\;F_{\lambda}(U){\rightarrow}({\prod}\;F_{\lambda})(U)(s_{\lambda}{\rightarrow}(o,o,{\cdots}\;{\cdots}o,s_{\lambda},o,{\cdots}\;{\cdots}o)$ for $(s_{\lambda}){\epsilon}{\prod}_{\lambda}\;F_{\lambda}(U)$ and $(s_{\lambda}){\epsilon}F_{\lambda}(U)$.

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