• 제목/요약/키워드: Nonlinear Algorithm

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비선형 공정을 위한 FCM 클러스터링 알고리즘 기반 퍼지 추론 시스템 (Fuzzy Inference Systems Based on FCM Clustering Algorithm for Nonlinear Process)

  • 박건준;강형길;김용갑
    • 한국정보전자통신기술학회논문지
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    • 제5권4호
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    • pp.224-231
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    • 2012
  • 본 논문에서는 비선형 공정을 퍼지 모델링하기 위해 FCM 클러스터링 알고리즘을 기반으로 하는 퍼지 추론 시스템을 소개한다. 비선형 공정에 대한 퍼지 규칙의 생성은 일반적으로 차원이 증가할수록 규칙의 수가 지수적으로 증가하는 문제를 가지고 있다. 이를 해결하기 위해, FCM 클러스터링 알고리즘을 이용하여 입력 공간을 분산 형태로 분할함으로써 퍼지 모델의 규칙을 생성한다. 퍼지 규칙의 전반부 파라미터는 FCM 클러스터링 알고리즘에 의한 소속행렬로 결정된다. 퍼지 규칙의 후반부는 다항식 함수의 형태로 표현되며, 각 규칙의 후반부 파라미터들은 표준 최소자승법에 의해 동정된다. 마지막으로, 비선형 공정의 특성 및 성능을 평가하기 위하여 비선형 공정으로는 널리 이용되는 데이터를 이용한다.

Hard 분산 분할 기반 추론 시스템을 이용한 비선형 공정 모델링 (Nonlinear Process Modeling Using Hard Partition-based Inference System)

  • 박건준;김용갑
    • 한국정보전자통신기술학회논문지
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    • 제7권4호
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    • pp.151-158
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    • 2014
  • 본 논문에서는 Hard 분산 분할 방법을 이용하는 추론 시스템을 소개하고 비선형 공정을 모델링한다. 이를 위해 입력 공간을 분산 형태로 분할하고 소속 정도가 0 또는 1을 갖는 Hard 분할 방법을 이용한다. 제안한 방법은 C-Means 클러스터링 알고리즘에 의해 구현되며, 초기 중심값에 민감한 단점을 보완하기 위해 LBG 알고리즘을 적용하여 이진 분할에 의한 초기 중심값을 이용한다. Hard 분산 분할된 입력 공간은 규칙 기반의 시스템 모델링에서 규칙을 형성한다. 규칙의 전반부 파라미터는 C-Means 클러스터링 알고리즘에 의한 소속행렬로 결정된다. 규칙의 후반부는 다항식 함수의 형태로 표현되며, 각 규칙의 후반부 파라미터들은 표준 최소자승법에 의해 동정된다. 비선형 공정으로는 널리 이용되는 데이터를 이용하여 비선형 공정을 모델링한 후 특성을 평가한다.

시선 안정화 시스템의 고 정밀 적응제어 (Adaptive High Precision Control of Lime-of Sight Stabilization System)

  • 전병균;전기준
    • 제어로봇시스템학회논문지
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    • 제7권1호
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    • pp.1155-1161
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    • 2001
  • We propose an adaptive nonlinear control algorithm for high precision tracking and stabilization of LOS(Line-of-Sight). The friction parameters of the LOS gimbal are estimated by off-line evolutionary strategy and the friction is compensated by estimated friction compensator. Especially, as the nonlinear control input in a small tracking error zone is enlarged by the nonlinear function, the steady state error is significantly reduced. The proposed algorithm is a direct adaptive control method based on the Lyapunov stability theory, and its convergence is guaranteed under the limited modeling error or torque disturbance. The performance of the pro-posed algorithm is verified by computer simulation on the LOS gimbal model of a moving vehicle.

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A dynamic analysis algorithm for RC frames using parallel GPU strategies

  • Li, Hongyu;Li, Zuohua;Teng, Jun
    • Computers and Concrete
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    • 제18권5호
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    • pp.1019-1039
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    • 2016
  • In this paper, a parallel algorithm of nonlinear dynamic analysis of three-dimensional (3D) reinforced concrete (RC) frame structures based on the platform of graphics processing unit (GPU) is proposed. Time integration is performed using Newmark method for nonlinear implicit dynamic analysis and parallelization strategies are presented. Correspondingly, a parallel Preconditioned Conjugate Gradients (PCG) solver on GPU is introduced for repeating solution of the equilibrium equations for each time step. The RC frames were simulated using fiber beam model to capture nonlinear behaviors of concrete and reinforcing bars. The parallel finite element program is developed utilizing Compute Unified Device Architecture (CUDA). The accuracy of the GPU-based parallel program including single precision and double precision was verified in comparison with ABAQUS. The numerical results demonstrated that the proposed algorithm can take full advantage of the parallel architecture of the GPU, and achieve the goal of speeding up the computation compared with CPU.

ON SOLVABILITY AND ALGORITHM OF GENERAL STRONGLY NONLINEAR VARIATIONAL-LIKE INEQUALITIES

  • Liu Zeqing;Sun, Juhe;Shim, Soo-Hak;Kang, Shin-Min
    • 대한수학회보
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    • 제43권2호
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    • pp.319-331
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    • 2006
  • In this paper, a new class of general strongly nonlinear variational-like inequalities was introduced and studied. The existence and uniqueness of solutions and a new iterative algorithm for the general strongly nonlinear variational-like inequality are established and suggested, respectively. The convergence criteria of the iterative sequence generated by the iterative algorithm are also given.

LM 최적화 알고리즘을 이용한 유리함수 모델의 데이터 피팅 (A Data Fitting Technique for Rational Function Models Using the LM Optimization Algorithm)

  • 박재한;배지훈;백문홍
    • 제어로봇시스템학회논문지
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    • 제17권8호
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    • pp.768-776
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    • 2011
  • This paper considers a data fitting problem for rational function models using the LM (Levenberg-Marquardt) optimization method. Rational function models have various merits on representing a wide range of shapes and modeling complicated structures by polynomials of low degrees in both the numerator and denominator. However, rational functions are nonlinear in the parameter vector, thereby requiring nonlinear optimization methods to solve the fitting problem. In this paper, we propose a data fitting method for rational function models based on the LM algorithm which is renowned as an effective nonlinear optimization technique. Simulations show that the fitting results are robust against the measurement noises and uncertainties. The effectiveness of the proposed method is further demonstrated by the real application to a 3D depth camera calibration problem.

Optimal design using genetic algorithm with nonlinear inelastic analysis

  • Kim, Seung-Eock;Ma, Sang-Soo
    • Steel and Composite Structures
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    • 제7권6호
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    • pp.421-440
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    • 2007
  • An optimal design method in cooperated with nonlinear inelastic analysis is presented. The proposed nonlinear inelastic method overcomes the difficulties due to incompatibility between the elastic global analysis and the limit state member design in the conventional LRFD method. The genetic algorithm used is a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are used to look for high performance ones among sections in the database. They are satisfied with the constraint functions and give the lightest weight to the structure. The objective function taken is the total weight of the steel structure and the constraint functions are load-carrying capacity, serviceability, and ductility requirement. Case studies of a planar portal frame, a space two-story frame, and a three-dimensional steel arch bridge are presented.

Parameter Calibration of the Nonlinear Muskingum Model using Harmony Search

  • Geem, Zong-Woo;Kim, Joong-Hoon;Yoon, Yong-Nam
    • 한국수자원학회논문집
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    • 제33권S1호
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    • pp.3-10
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    • 2000
  • A newly developed heuristic algorithm, Harmony Search, is applied to the parameter calibration problem of the nonlinear Muskingum model. The Harmony Search could, mimicking the improvisation of music player, find better parameter values for in the nonlinear Muskingum model than five other methods including another heuristic method, genetic algorithm, in the aspect of SSQ(the sum of the square of the deviations between the observed and routed outflows) as well as in the aspects of SAD(the sum of the absolute value of the deviations), DPO(deviations of peak of routed and actual flows) and DPOT(deviatios of peak time of routed and actual outflow). Harmony Search also has the advantage that it does not require the process of asuming the initial values of desing parameters. The sensitivity analysis of Harmony Memory Considering Rate showed that relatively large values of Harmony Memory Considering Rate makes the Harmony Search converge to a better solution.

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마찰력 보상 기법을 이용한 동적 시스템의 고 정밀 적응제어 (Adaptive High Precision Control of Dynamic System Using Friction Compensation Schemes)

  • 전병균;전기준
    • 대한전기학회논문지:시스템및제어부문D
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    • 제49권10호
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    • pp.555-562
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    • 2000
  • We propose an adaptive nonlinear control algorithm for compensation of the stick-slip friction in a dynamic system. The friction force and mass of the system are estimated and compensated by adaptive control law. Especially, as the nonlinear control input in a small tracking error zone is enlarged by the nonlinear function, the steady state error is significantly reduced. The proposed algorithm is a direct adaptive control method based on the Laypunov stability theory, and its convergence is guaranteed under the bounded noise or torque disturbance. We verified the performance of the proposed algorithm by computer simulation on one-DOF mechanical system with friction.

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SDS 알고리즘을 이용한 비선형 파라미터 최적화에 관한 연구 (A Study on Nonlinear Parameter Optimization Problem using SDS Algorithm)

  • 이영진;장용훈;이권순
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 B
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    • pp.623-625
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    • 1998
  • This paper focuses on the fast convergence in nonlinear parameter optimization which is necessary for the fitting of nonlinear models to data. The simulated annealing(SA) and genetic algorithm(GA), which are widely used for combinatorial optimization problems, are stochastic strategy for search of the ground state and a powerful tool for optimization. However, their main disadvantage is the long convergence time by unnecessary extra works. It is also recognised that gradient-based nonlinear programing techniques would typically fail to find global minimum. Therefore, this paper develops a modified SA which is the SDS(Stochastic deterministic stochastic) algorithm can minimize cost function of optimal problem.

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