• Title/Summary/Keyword: Nonlinear Algorithm

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Online GA-based Nonlinear System Identification (온라인 GA 기반 비선형 시스템 식별)

  • Lee, Jung-Youn;Lee, Hong-Gi
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.6
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    • pp.820-824
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    • 2010
  • Genetic algorithm is known to be an effective method to solve a global nonlinear optimization. However, a huge amount of calculation is needed to improve the dependability of the solution and thus Ga is not adequate for online implementation. In this paper, we propose an online nonlinear system identification scheme which employs population feedback genetic algorithm. The effectiveness of our scheme is shown by several simulations.

Nonlinear Inelastic Optimal Design Using Genetic Algorithm (유전자 알고리즘을 이용한 비선형 비탄성 최적설계)

  • 마상수;김승억
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2003.10a
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    • pp.145-152
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    • 2003
  • An optimal design method in cooperated with nonlinear inelastic analysis method 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 uses a procedure based on Darwinian notions of survival of the fittest, where selection, crossover, and mutation operators are used among sections in the database to look for high performance ones. They satisfy the constraint functions and give the lightest weight to the structure. The objective function is set to the total weight of the steel structure and the constraint functions are load-carrying capacities, serviceability, and ductility requirement. Case studies of a three-dimensional frame and a three-dimensional steel arch bridge are presented.

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Parameter Calibration o fthe Nonlinear Muskingum Model using Harmony Search

  • Geem, Jong-Woo;Kim, Joong-Hoon;Yoon, Yong-Nam
    • Proceedings of the Korea Water Resources Association Conference
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    • 2000.05a
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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 players, 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 (deviations of peak time of rented and actual outflow). Harmony Search also has the advantage that it does not require the process of assuming the initial values of design parameters. The sensitivity analysis of Harmony Memory Considering Rate showed that relatively large values of Harmony Memory Considering Rate makes the Harmony Search converse to a better solution.

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A study on the trajectory control of SCARA robot using sliding mode (슬라이딩 모드를 이용한 SCARA 로보트의 궤적제어에 관한 연구)

  • 진상영;이민철;이만형
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.1031-1035
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    • 1993
  • In this paper, we suggest a new algorithm diminishing the chattering in sliding mode control by setting a dead-band along the switching line on the phase plane although nonlinear terms of an nonlinear system are regarded as disturbances and apply this algorithm to the trajectory control of SCARA robot By this algorithm, we can expect the high performance of the trajectory trajet of an industrial robot which needs a robust and simple algorithm.

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Development of an Educational System and Real Time Nonlinear Control (I) (교육용 시스템 개발과 실시간 비선형 제어(I))

  • 박성욱
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.12
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    • pp.562-570
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    • 2002
  • The Purpose of this paper is to design and manufacture an educational system in order to demonstrate the causes and effects of electromagnetic induction.'rho educational system described in this study is a "jumping ring apparatus". This system demonstrates the principle of electromagnetic induction, a force from AC sources, Lenz's law of repulsion and transformer. The educational system is composed of a jumping ring apparatus, a sensor array, encoder, A/D converter, D/A converter and nonlinear controller. The educational system is controlled by 586 PC using Turbo C program. The sensor array is composed of 20 optical sensors. The nonlinear controller consists of nonlinear control algorithm and control board included SCR, FET and phase controller. The A/D converter is used to show the height of ring position to analog for an education purpose. The control signal calculated from the nonlinear control of algorithm send control board through 8 bit D/A convertor. Experiment results are given to verify that Proposed nonlinear controller is useful in on line control of the educational system.al system.

Development of the Position Control Algorithm for Nonlinear Overhead Crane Systems (비선형 천장 크레인시스템의 위치제어 알고리즘 개발)

  • 이종규;이상룡
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.4
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    • pp.142-147
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    • 2000
  • An overhead crane system which transports an object by girder motion, trolley motion, and hoist motion becomes a nonlinear system because the length of a rope changes. To develope the position control algorithm for the nonlinear crane systems, we apply a nonlinear optimal control method which uses forward and backward difference methods and obtain optimal inputs. This method is suitable for the overhead crane system which is characterized by the differential equation of higher degree and swing motion. From the results of computer simulation, it is founded that the position of the overhead crane system is controlled, and the swing of the object is suppressed.

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Nonlinear system control using neural network guaranteed Lyapunov stability (리아프노브 안정성이 보장되는 신경회로망을 이용한 비선형 시스템 제어)

  • Seong, Hong-Seok;Lee, Kwae-Hui
    • Journal of Institute of Control, Robotics and Systems
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    • v.2 no.3
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    • pp.142-147
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    • 1996
  • In this paper, we describe the algorithm which controls an unknown nonlinear system with multilayer neural network. The multilayer neural network can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate unknown nonlinear function on the nonlinear system by using of multilayer neural network. The weight-update rule of multilayer neural network is derived to satisfy Lyapunov stability. The whole control system constitutes controller using feedback linearization method. The weight of neural network which is used to implement nonlinear function is updated by the derived update-rule. The proposed control algorithm is verified through computer simulation.

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A Study on the Nonlinear Controller Design Using T-S Fuzzy Model and GA (T-S 퍼지 모델과 GA를 이용한 비선형 제어기의 설계에 관한 연구)

  • Kang, Hyeong-Jin;Kwon, Cheol;Shim, Han-Su;Kim, Seun-U;Park, Min-Yong
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1996.10a
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    • pp.310-312
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    • 1996
  • In this paper, we propose a design method for nonlinear SISO system using Takagi-Sugeno fuzzy model and Genetic Algorithm. Our method can reduce the number of design parameters and has advantage of small search space of Genetic Algorithm. The proposed nonlinear controller, which can be implemented by fuzzy controller and simple nonlinear controller, cancels the original nonlinear dynamics and gives the optimal nonlinear dynamics. We illustrated the performance of the proposed controller by simple simulation example.

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PSO-Based Nonlinear PI-type Controller Design for Boost Converter

  • Seo, Sang-Wha;Kim, Yong;Choi, Han Ho
    • Journal of Electrical Engineering and Technology
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    • v.13 no.1
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    • pp.211-219
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    • 2018
  • This paper designs a nonlinear PI-type controller for the robust control of a boost DC-DC converter using a particle swarm optimization (PSO) algorithm. Based on the common knowledge that the transient responses can be improved if the P and I gains increase when the transient error is big, a nonlinear PI-type control design method is developed. A design procedure to autotune the nonlinear P and I gains is given based on a PSO algorithm. The proposed nonlinear PI-type controller is implemented in real time on a Texas Instruments TMS320F28335 floating-point DSP. Simulation and experimental results are given to demonstrate the effectiveness and practicality of the proposed method.

A study on Improvement for distorted images of the Digital X-ray Scanner System based on Fuzzy Correction Algorithm

  • Baek, Jae-Ho;Kim, Kyung-Jung;Park, Mi-Gnon
    • Proceedings of the Korea Society of Information Technology Applications Conference
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    • 2005.11a
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    • pp.173-176
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    • 2005
  • This paper proposes a fuzzy correction algorithm that can correct the distorted medical image caused by the scanning nonlinear velocity of the Digital X-ray Scanner System (DX-Scanner) using the Multichannel Ionization Chamber (MIC). In the DX-Scanner, the scanned medical image is distorted for reasons of unsuitable integration time at the nonlinear acceleration period of the AC servo motor during the inspection of patients. The proposed algorithm finds the nonlinear motor velocity modeling through fuzzy system by clustering and reconstructs the normal medical image lines by calculating the suitable moving distance with the velocity of the motor using the modeling, acceleration time and integration time. In addition, several image processing is included in the algorithm. This algorithm analyzes exact pixel lines by comparing the distance of the acceleration period with the distance of the uniform velocity period in every integration time and is able to compensate for the velocity of the acceleration period. By applying the proposed algorithm to the test pattern for checking the image resolution, the effectiveness of this algorithm is verified. The corrected image obtained from distorted image is similar to the normal and better image for a doctor's diagnosis.

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