• Journal of Advanced Marine Engineering and Technology
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• 제41권1호
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• pp.105-110
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• 2017

이 논문에서는 해상에서의 환경 하중과 외력을 고려한 해상 크레인의 상하 동요 보상 시스템에 대해 연구한 내용을 소개한다. 이를 위해 강체라 가정된 해상 크레인과 유압 구동식 윈치, 탄성력을 갖는 로프, 그리고 로프 끝단의 중량물로 구성된 동역학 모델을 먼저 살펴본다. 중량물의 상하 동요 움직임을 보상하기 위해, 선형화를 통한 PD 제어를 적용했다. 또한, 비선형 시스템에 맞춘 슬라이딩 모드 제어기 및 시간 지연을 고려한 비선형 일반 예측 제어 알고리즘을 사용한 제어를 적용했으며, 그 결과 진동폭이 줄어듬을 확인할 수 있다. 결과적으로, 1초의 시간 지연을 고려하여 설계한 강인 제어기를 활용하게 되면, 상하동요 보상시스템에서 오차를 가장 많이 줄여서 본 시스템에 적합한 제어 알고리즘으로써 활용할 수 있음을 볼 수 있다.

• 전자공학회논문지S
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• 제34S권11호
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• pp.53-62
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• 1997

In this study, a controller design method is proposed for controlling the discrete-time chaotic systems efficiently. The proposed control method is based on Generalized Predictive Control and uses NARMAX models as controlled models. In order to evaluate the performance of the proposed method, a proposed controller is applied to discrete-time chaotic systems, and then the control performance and initial sensitivity of the proposed controller are compared with those of the conventional model-based controler through computer simulations. Through simulations results, it is shown that the control performance of the proposed controller is superior to that of the conventional model-based controller and shown that the peorposed controller is less sensitive to initial values of discrete-time chaotic systems in comparison with the conventional model-based controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.176-181
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• 1992

In this paper, an adaptive generalized predictive control(GPC) algorithm which minimizes a N-stage cost function is proposed. The resulting controller is based on GPC algorithm and can be used in unknown plant parameters as the parameters of one step ahead predictor are estimated by recursive least squares method. The estimated parameters are extended to G,P, and F amtrix which contain the parameters of N step ahead predictors. And the minimization of cost function assuming no constraints on future controls results in the projected control increment vector. Hence this adaptive GPC algorithm can be used for either unknown system or varing system parameters, and it is also shown through simulations that the algorithm is robust to the variation of system parameters. This adaptive GPC scheme is shown to have the same stability properties as the deterministic GPC, and requires small amount of calculation compared to other adaptive algorithms which minimize N-stage cost function. Especially, in case that the maximum output horizon is 1, the proposed algorithm can be applicable to direct adaptive GPC.

• 제어로봇시스템학회논문지
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• 제13권3호
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• pp.268-272
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• 2007

These days many scientists make studies of feedback control system for stability on non-linear state and for the maneuver of flying objects. These feedback control systems have to satisfy trajectory condition and angular conditions, that is to say, controllability and stability simultaneously to achieve mission. In this paper, a design methods using model based control system which consists of spiral predictive model, Q-function included into generalized-work function is shown. It is made a clear that the proposed algorithm using SPM maneuvers for controllability and stability at the same time is successful in attaining our purpose. The feature of the proposed algorithm is illustrated by simulation results. As a conclusion, the proposed algorithm is useful for the control of moving objects.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.111-112
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• 2006

A new MR cylinder with built-in valves using Magneto - Rheological fluid (MR valve) is proposed for fluid power control systems. The MR fluid is a newly developed functional fluid whose obvious viscosity is controlled by the applied magnetic field intensity. This MR cylinder, which is composed of cylinder with small clearance and piston with electromagnet, has the characteristics of simple, compact and reliable structure. This paper presents a method to control the pressure of MR cylinder by using Generalized Predictive Control (GPC) algorithm. The differential pressure is controlled by applying magnetic field intensity to MR fluid. The use of GPC controller is to generate a control sequence by minimizing a cost function in such a way that the future system output is driven close to reference over finite prediction horizons. Experimental results from real time control using GPC method compared with conventional PID control method are also shown in this paper.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.183-186
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• 2002

In this paper, a predictive control method using wavelet neural network for chaotic nonlinear systems is presented. In our method, we use the adjusting method of the parameter for the training a wavelet neural network. The control signals are directly obtained by minimizing the difference between a reference signal and the output of a wavelet neural network. To verify the efficiency of our method, we apply it to the Duffing and the Henon system, which are a representative continuous and discrete time chaotic nonlinear system respectively.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 춘계학술대회 논문집
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• pp.326-329
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• 1995

PID control has been widely used for real control system Further, there are muchreasearches on control schemes of tuning PID gains. However, there is no results for discrete-time systems with unknown time-dealy and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown parameters and unknown tiem-delay system. A numerical simulation was presented to illuatrate the effectiveness of this method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1838-1842
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• 2004

Gain and phase margins of a first order plus delayed time (FOPDT) process controlled by generalized predictive controller (GPC) are related to the control parameters ${\lambda}$ (control move suppression parameter) and ${\alpha}$ (smoothing filter coefficient) and the normalized delay of the process. Variation ranges of gain and phase margins are determined. It is shown that the margins cannot be assigned independently for a wide range of variation and the range is narrowing by increase of the normalized delay of the process. And finally curves are given to use for adjustment of the controller parameters in order to obtain a specific pair of gain and phase margins.

• Nuclear Engineering and Technology
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• 제27권6호
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• pp.833-844
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• 1995

증기발생기 수위제어를 위한 자기동조 예측제어기법을 제안하였다. 제어기설계시 측정 가능한 앞되먹임 신호에 대한 고려와 비선형계통이나 시변계통에 적용하기 위해 적응형으로 유도한 것이 제안된 제어기의 특징이다. 이러한 이유로 제안된 제어기는 계통의 동특성에 직접 영향을 주는 앞되먹임 신호가 존재하고, 시간이나 동작조건에 따라 계통의 계수가 변하는 계통에 적용 가능하다. 제안된 제어기의 성능을 검증하기 위해 웨스팅하우스형의 증기발생기 모델을 이용하여 모의실험을 수행하였다. 모의실험 결과 기존의 비례-적분제어기 보다 우수한 성능을 나타냄을 알 수 있었다.

• 한국지능시스템학회논문지
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• 제15권4호
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• pp.457-466
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• 2005

본 논문에서는 다중 입$\cdot$출력을 갖는 이동 로봇의 경로 추종을 위해 웨이블깃 신경 회로망에 기반한 예측 제어 방법을 제안한다. 제안된 방법에서 상태 예측기로는 학습 능력이 뛰어난 신경 회로망의 특성 및 웨이블릿 분해의 특성을 합성한 웨이블릿 신경 회로망을 사용한다. 예측기는 경사 하강법을 사용하여 웨이블릿 신경회로망의 출력에 대한 실제 이동 로봇의 상태 오차를 최소화하도록 학습된다. 또한 이동 로봇의 제어 신호인 직진 속도 및 각속도는 추종하고자 하는 기준 경로에 대한 이동 로봇의 예측 상태 오차를 이용하여 정의된 비용 함수를 최소화하도록 구해진다. 컴퓨터 모의 실험에서 변화되는 기준 경로에 대한 경로 추종 성능을 통해 제안한 예측 제어 시스템의 적용 가능성 및 효율성을 보인다.