• 제목/요약/키워드: nonlinear algorithm

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TS 퍼지 모델 동정을 이용한 표적 추적 시스템 설계 (The Design of Target Tracking System Using the Identification of TS Fuzzy Model)

  • 이범직;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 D
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    • pp.1958-1960
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    • 2001
  • In this paper, we propose the design methodology of target tracking system using the identification of TS fuzzy model based on genetic algorithm(GA) and RLS algorithm. In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter(EKF), the performance of the system may be deteriorated in highly nonlinear situation. In this paper, to resolve these problems of nonlinear filtering technique, the error of EKF by nonlinearity is compensated by identifying TS fuzzy model. In the proposed method, after composing training datum from the parameters of EKF, by identifying the premise and consequent parameters and the rule numbers of TS fuzzy model using GA, and by tuning finely the consequent parameters of TS fuzzy model using recursive least square(RLS) algorithm, the error of EKF is compensated. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

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화학 공정의 편미분 방정식 모델설정과 제어에 관한 연구 (Development of Pprocess Models by Partial Differential Equations and Ccontrol Systems)

  • 최영순;이인범;장근수
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.105-107
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    • 1991
  • A chemical process model represented by partial differential equations was studied as one of nonlinear distributed parameter control problems. Using an optimal control theory in the form of maximum principles based on nonlinear integral equations, an algorithm to solve the problem was developed and coded into a computer program.

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GENERALIZED STRONGLY NONLINEAR QUASI-VARIATIONAL INEQUALITIES

  • Jeong, Jae-Ug
    • Journal of applied mathematics & informatics
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    • 제6권1호
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    • pp.253-264
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    • 1999
  • In this paper we introduce and study a new class of vari-ational inequalities which are called the generalized strongly nonlin-ear quasi-variational inequalities. An algorithm for finding the ap-proximate solution of generalized strongly nonlinear quasi-variational inequalities is also given. These variational inequalities include the previously known classes of variational inequalities as special cases.

Computational Methods for Detection of Multiple Outliers in Nonlinear Regression

  • Myung-Wook Kahng
    • Communications for Statistical Applications and Methods
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    • 제3권2호
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    • pp.1-11
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    • 1996
  • The detection of multiple outliers in nonlinear regression models can be computationally not feasible. As a compromise approach, we consider the use of simulated annealing algorithm, an approximate approach to combinatorial optimization. We show that this method ensures convergence and works well in locating multiple outliers while reducing computational time.

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Sliding Mode Controller with Sliding Perturbation Observer Based on Gain Optimization using Genetic Algorithm

  • You, Ki-Sung;Lee, Min-Cheol;Yoo, Wan-Suk
    • Journal of Mechanical Science and Technology
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    • 제18권4호
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    • pp.630-639
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    • 2004
  • The Stewart platform manipulator is a closed-kinematics chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. However, this is a complex and nonlinear system, so the control performance of the system is not so good. In this paper, a new robust motion control algorithm is proposed. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is the design of a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observe. (SMCSPO). The optimal gains of SMCSPO, which is determined by nominal eigenvalues, are easily obtained by genetic algorithm. The proposed fitness function that evaluates the gain optimization is to put sliding function. The control performance of the proposed algorithm is evaluated by the simulation and experiment to apply to the Stewart platform. The results showed high accuracy and good performance.

회귀용 Support Vector Machine의 성능개선을 위한 조합형 학습알고리즘 (Hybrid Learning Algorithm for Improving Performance of Regression Support Vector Machine)

  • 조용현;박창환;박용수
    • 정보처리학회논문지B
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    • 제8B권5호
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    • pp.477-484
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    • 2001
  • 본 논문에서는 회귀용 support vector machine의 성능 개선을 위한 모멘텀과 kernel-adatron 기법이 조합형 학습알고리즘을 제안하였다. 제안된 학습알고리즘은 supper vector machine의 학습기법인 기술기상승법에 발생하는 최적해로의 수렴에 따란 발진을 억제하여 그수렴속도를 좀 더 개선시키는 모멘텀의 장점과 비선형 특징공간에서의 동작과 구현의 용이성을 갖는 kernel-adatorn 알고리즘의 장점을 그대로 살린 것이다. 제안된 알고리즘의 support vector machine을 1차원과 2차원 비선형 함수 회귀에 적용하여 시뮬레이션한 결과, 학습속도에 있어서 2차 프로그래밍과 기존의 kernel-adaton 알고리즘보다 더 우수하고, 회귀성능면에서도 우수한 성능이 있음을 확인하였다.

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적응퍼지-뉴럴네트워크를 이용한 비선형 공정의 온-라인 모델링 (on-line Modeling of Nonlinear Process Systems using the Adaptive Fuzzy-neural Networks)

  • 오성권;박병준;박춘성
    • 대한전기학회논문지:전력기술부문A
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    • 제48권10호
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    • pp.1293-1302
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    • 1999
  • In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

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틸트로터 항공기의 경로점 추종 비행유도제어 알고리즘 설계 : 헬리콥터 비행모드 (Guidance and Control Algorithm for Waypoint Following of Tilt-Rotor Airplane in Helicopter Flight Mode)

  • 하철근;윤한수
    • 제어로봇시스템학회논문지
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    • 제11권3호
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    • pp.207-213
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    • 2005
  • This paper deals with an autonomous flight guidance and control algorithm design for TR301 tilt-rotor airplane under development by Korea Aerospace Research Institute for simulation purpose. The objective of this study is to design autonomous flight algorithm in which the tilt-rotor airplane should follow the given waypoints precisely. The approach to this objective in this study is that, first of all, model-based inversion is applied to the highly nonlinear tilt-rotor dynamics, where the tilt-rotor airplane is assumed to fly at helicopter flight mode(nacelle angle=0 deg), and then the control algorithm, based on classical control, is designed to satisfy overall system stabilization and precise waypoint following performance. Especially, model uncertainties due to the tiltrotor model itself and inversion process are adaptively compensated in a simple neural network(Sigma-Phi NN) for performance robustness. The designed algorithm is evaluated in the tilt-rotor nonlinear airplane in helicopter flight mode to analyze the following performance for given waypoints. The simulation results show that the waypoint following responses for this algorithm are satisfactory, and control input responses are within control limits without saturation.

층간 연결에 의한 GMDH 알고리듬의 모델링 성능 향상 (Improvement of Modeling Capability of GMDH Algorithm with Interlayer Connection)

  • 홍연찬
    • 한국정보통신학회논문지
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    • 제13권6호
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    • pp.1200-1207
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    • 2009
  • 복잡한 비선형 시스템을 모델링하기 위하여 GMDH(Group Method of Data Handling) 알고리듬을 사용할 수 있다. 기존의 GMDH 알고리듬은 정해진 절차에 의해 입력층부터 중간층들을 거쳐 출력층에서 시스템의 모델링 출력을 생성한다. 각 층의 출력은 전 층의 출력에 의해서만 생성된다. 그러나 입력들 중에서는 다른 입력들보다 모델링 결과에 더 큰 영향을 줄 수 있는 입력들이 있을 수 있다. 따라서 본 논문에서는 영향이 큰 입력들을 층간 연결하여 모델링 성능을 향상시키는 방법을 제안하였다. 제안된 알고리듬이 기존의 알고리듬보다 성능이 향상된 것을 컴퓨터 시뮬레이션을 통해 검증하였다.

DEVELOPMENT OF A SIMPLE CONTROL ALGORITHM FOR SWIRL MOTOR CONTROLLER

  • Lee, W.T.;Kang, J.J.
    • International Journal of Automotive Technology
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    • 제7권3호
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    • pp.369-375
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    • 2006
  • This paper describes a simple proportional and integral control algorithm for a swirl motor controller and its application. The control algorithm may be complicated in order to have desired performance, such as low steady state errors, fast response time, and relatively low overshoot. At the same time, it should be compact so that it can be easily implemented on a low cost microcontroller, which has no floating-point calculation capability and low computing speed. These conflicting requirements are fulfilled by the proposed control algorithm which consists of a gain scheduling proportional controller and an anti-windup integral controller. The mechanical friction, which is caused by gears and a return spring, varies very nonlinearly according to the angular position of the system. This nonlinear static friction is overcome by the proportional controller, which has a two-dimensional look up gain table. It has error axis and angular position axis. The integral controller is designed not only to minimize the steady state error but also to avoid the windup effect, which may be caused by the saturation of a motor driver. The proposed control algorithm is verified by use of a commercial product to prove the feasibility of the algorithm.