• Title/Summary/Keyword: 최적제어

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A Learning Algorithm for Optimal Fuzzy Control Rules (최적의 퍼지제어규칙을 얻기위한 퍼지학습법)

  • Chung, Byeong-Mook
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.2
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    • pp.399-407
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    • 1996
  • A fuzzy learning algorithm to get the optimal fuzzy rules is presented in this paper. The algorithm introduces a reference model to generate a desired output and a performance index funtion instead of the performance index table. The performance index funtion is a cost function based on the error and error-rate between the reference and plant output. The cost function is minimized by a gradient method and the control input is also updated. In this case, the control rules which generate the desired response can be obtained by changing the portion of the error-rate in the cost funtion. In SISO(Single-Input Single- Output)plant, only by the learning delay, it is possible to experss the plant model and to get the desired control rules. In the long run, this algorithm gives us the good control rules with a minimal amount of prior informaiton about the environment.

Disturbance Rejection and Optimal Tuning of PID Controller Using $H_\infty$ and Genetic Algorithms ($H_\infty$ 와 유전자 알고리즘을 이용한 PID 제어기루프의 외란제거 및 최적화 튜닝)

  • Kim, Dong-Hwa;Jo, Jae-Hun
    • Proceedings of the KIEE Conference
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    • 2003.11b
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    • pp.323-326
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    • 2003
  • 본 논문에서는 PID 제어기를 이용해 외란제거를 함은 물론 최적 제어가 될 수 있는 파라메터를 유전자 알고리즘을 통해 구하는 방법을 제안하였다. 외란제거를 위해 $H_\infty$-norm을 응용하여 제어시스템의 외란 제거 조건들을 제시하고 이 조건들을 만족하는 PID 제어기를 설계하였다. 설계된 PID제어기의 최적 파라메터를 구하기 위해 유전자 알고리즘을 이용하였고 최적 파라메터를 평가하기 위하여 ITSE(Integral of time weighted squared error)성능지수를 이용하였다. 위의 설계 기법들을 서보모터의 제어에 적용하여 만족할 만한 결과를 얻었다.

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Optimal control of the State Feedback Variables for Controlling DC Motor (DC Motor 제어를 위한 상태궤환 변수의 최적제어)

  • 최진부
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.22 no.3
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    • pp.31-42
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    • 1985
  • Thig paper used two feedback sensors, that is, potentiometer and tachometer in order to control DC motor. Also, the state feedback and kalman regular type in the linear system or the state feedback and on-off relay type in the non-linear system are used as control meth-ods for optimal control values. This compared and analyzed the control estimate of tracking angles by the estimate of three branches of methods of position and speed measured, position and speed by PD and position, speed and covariance by an observer.

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Model Based Control System Design of Two Wheeled Inverted Pendulum Robot (이륜 도립진자 로봇의 모델 기반 제어 시스템 설계)

  • Ku, Dae-Kwan;Ji, Jun-Keun;Cha, Guee-Soo
    • The Transactions of the Korean Institute of Power Electronics
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    • v.16 no.2
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    • pp.162-172
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    • 2011
  • This paper proposes embedded System of two wheeled inverted pendulum robot designed by model based design method, using MATLAB/SIMULINK and LEGO NXT Mindstorms. At first, stability and performance of controller is verified through modeling and simulation. After that direct conversion from simulation model to C code is carried and effectiveness of controller is experimentally verified. Two wheeled inverted pendulum robot has basic function about autonomous balancing control using principle of inverted pedulum and it is also possible to arrive at destination. In this paper, state feedback controller designed by quadratic optimal control method is used. And quadratic optimal control uses state feedback control gain K to minimize performance index function J. Because it is easy to find gain, this control method can be used in the controller of two wheeled inverted pendulum robot. This proposed robot system is experimentally verified with following performances - balancing control, disturbance rejection, remote control, line following and obstacle avoidance.

Integrated Optimal Design of Hybrid Structural Control System using Multi-Stage Goal Programming Technique (다단계 목표계획법을 이용한 복합구조제어시스템의 통합최적설계)

  • 박관순;고현무;옥승용
    • Journal of the Earthquake Engineering Society of Korea
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    • v.7 no.5
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    • pp.93-102
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    • 2003
  • An optimal design method for hybrid structural control system of building structures subject to earthquake excitation is presented in this paper. Designing a hybrid structural control system may be defined as a process that optimizes the capacities and configuration of passive and active control systems as well as structural members. The optimal design proceeds by formulating the optimization problem via a multi-stage goal programming technique and, then, by finding reasonable solution to the optimization problem by means of a goal-updating genetic algorithm. In the multi-stage goal programming, design targets(or goals) are at first selected too correspond too several stages and the objective function is th n defined as the sum of the normalized distances between these design goals and each of the physical values, that is, the inter-story drifts and the capacities of the control system. Finally, the goal-updating genetic algorithm searches for optimal solutions satisfying each stage of design goals and, if a solution exists, the levels of design goals are consecutively updated to approach the global optimal solution closest too the higher level of desired goals. The process of the integrated optimization design is illustrated by a numerical simulation of a nine-story building structure subject to earthquake excitation. The effectiveness of the proposed method is demonstrated by comparing the optimally designed results with those of a hybrid structural control system where structural members, passive and active control systems are uniformly distributed.

Weighting Matrices of LQR and ILQR Controllers Considering Structural Energy (구조물의 에너지를 고려한 LQR 및 ILQR제어기의 가중행렬)

  • 민경원;이영철;박민규
    • Journal of the Earthquake Engineering Society of Korea
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    • v.6 no.6
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    • pp.49-53
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    • 2002
  • This paper provides the systematic procedure to determine the weighting matrices of optimal controllers considering structural energy. Optimal controllers consist of LQR and ILQR. The weighting matrices are needed first in the conventional optimal control design strategy. However, they are in general dependent on the experienced knowledge of control designers. Applying the Lyapunov function to total structural energy and using the condition that its derivative is negative, we can determine the weighting matrices without difficulty. It is proven that the control efficiency with using determined weighting matrices is achieved well for LQR and ILQR controllers.

Optimal Control of a Flexible Manipulator Using Kalman Filter (칼만 필터를 이용한 유연성 매니퓨레이터의 최적 제어)

  • 남호법;박종국
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.14 no.2
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    • pp.155-163
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    • 1989
  • For a one link flexible arm control, quadratic optimal control is applied to the dynamic modilling which is derived from an assumed mode method. For the quadratic optimal control technique, the full state feedback must be obtained for closing the control loop, but because some of the states in the flexible system(e.g. the rate of change of the time dependent variables of the mode shapes) can not be directly measured, state estimator is necessary to achieve the practical implementation of the optimal controller. When disturbances and measurement noise occur, stochastic approach must be applied to estimating the states of the system. Kalman Filter is used as a stste estimator. Through the simulation, the flexible system with state estimator is compared with the flexible system assuming that all the states can be measured.

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A PID Genetic Controller Design Using Reference Model (기준모델을 이용한 PID 유전 제어기 설계)

  • Park, K.H.;Nam, M.H.;Hwang, Y.W.;Chun, S.J.
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.894-896
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    • 1999
  • PID 제어는 50년의 역사를 갖기 때문에 현장의 사용자는 이 제어방식에 익숙해져 있으며, 제어장치의 구성이 간단하며 제어기의 최적동조가 가능하므로 많은 분야에서 사용되고 있다[1]. 그러나 PID 제어기에 의해서 얻은 결과에 대하여 만족하기 위해서는 많은 시행착오를 겪어야 한다. 또한 만족하는 결과를 얻었다고 할지라도 외란, 플랜트의 동특성이 바뀌는 경우 시스템을 추종하지 못하기 때문에 파라미터를 재조정하여야 한다. 유전 알고리즘은 자연세계의 진화 현상에 기초한 계산모델로서 John Holland에 의해서 1975년에 개발된 전역적인 최적화 알고리즘이며[1][2], 비선형 고차원, 불연속, 다중모드, 노이즈 함수 등에 대하여 강건함을 보여주고, 복잡한 탐색 공간에서 최적 값을 스스로 발견하는 학습 능력을 갖는다. 이 방법은 재생산, 교배, 돌연변이를 통하여 최적해를 찾은 방법으로 1989년에 D. E. Goldgerg에 의해서 체계적으로 정리된 후 여러 분야에서 응용되고 있다[3][4]. 그러나 유전 알고리즘은 목적함수만을 이용하여 해집단을 탐색하기 때문에 숙련운전자가 원하는 제어 특성 명세인 상승시간, 정착시간, 초과량(oveshoot) 둥을 구체적으로 명시하여 제어에 반영할 수 없다. 또한, 유전 알고리즘은 입력 값이 크게 바뀔 경우 다른 시스템으로 인식하여 새로운 탐색을 수행하는 단점을 가지고 있다. 본 논문은 첫째, 기준모델을 도입하여 플랜트의 성능을 기준모델로 표현하여 플랜트가 요구하는 성능지표를 정량적으로 규정하는 것이 가능하였다. 또한, 이것은 미지 플랜트 동특성을 식별하기 위한 신호로 사용되어, 플랜트의 정보를 얻는데 이용되었다. 즉, 기준모델과 플랜트 출력사이의 추종 오차 정보가 적응기구인 PID 유전제어기의 입력으로 사용되며, 구형파 입력의 경우에도 기준모델과 플랜트의 출력차는 크게 변하지 않는다. 따라서, 유전 알고리즘의 목적함수에 기준 모델을 제안 적용하여 안정적이고, 세밀한 제어를 수행하였다. 둘째, PID의 간단하면서 확실한 제어가 가능하다는 점과 전역적인 최적값을 찾을 수 있는 유전 알고리즘을 적용하여 고속제어를 요하는 직류 서보 모터(DC Servo Motor) 운전 시 실시간 파라미터 동조에 적용하였다.

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