• 한국정밀공학회지
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• 제12권8호
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• pp.140-146
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• 1995

In case the uncertainty existing in a system is assumed to satisfy the matching condition and to be come-bounded. Y. H. Chen proposed an adaptive robust control algorithm which introduced adaptive sheme for a design parameter into robust deterministic controls. In this paper, the adaptive robust control algorithm is applied to the position tracking control of direct drive robots, and simulation and experimental studies are conducted to evaluate control performance.

• 전기전자학회논문지
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• 제19권2호
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• pp.225-231
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• 2015

토크제어를 이용한 최대 출력 제어에서 얼마나 많은 풍력에너지를 전기에너지로 변환하는지 결정하는 파라미터 K는 블레이드 형상 변화. 공기 밀도 등으로 인하여 변동하게 된다. 이러한 파라미터 K가 최적의 값이 아니면 이는 출력의 손실까지 이어진다. 이렇게 변동하는 K로 인하여 최적의 K를 찾는 것이 풍력발전시스템의 손실을 줄이는 중요한 문제이다. 본 논문은 양방향 컨버터 제어와 토크제어를 사용한 풍력발전시스템을 고려하여 초기의 K를 이용하여 빠른 제어를 수행하고 칼만 필터를 이용한 기계적 출력을 추정하여 최대 출력 제어 알고리즘의 입력으로 다시 사용하여 결과적으로 최적의 최대 출력 제어 제어를 수행하는 적응 최대 출력 제어 알고리즘을 제안한다.

• 드라이브 ㆍ 컨트롤
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• 제17권1호
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• pp.13-20
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• 2020

Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

• 대한전기학회논문지
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• 제40권4호
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• pp.427-438
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• 1991

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic system is preented. In the learning control structure, the control input converges globally and asymtotically to the desired input as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of the time-duration of trajectories, it may be achieved with system trajectories with small duration. In addition, the proposd learning control schemes are applicable to time-varying parametric systems as well as time-invariant systems, because the parameter estimation is performed at each fixed time along the iteration. In the parameter estimator, the acceleration information as well as the inversion of estimated inertia matrix are not used at all, which makes the proposed learning control schemes more feasible.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.337-340
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• 1997

In this paper we propose direct and indirect adaptive controllers for a nonlinear multivariable steam generating unit(200MW). In the direct adaptive scheme the estimation of the controller parameter are achieved from tracking error, while in the indirect approach the unknown parameter of the boiler system is estimated by the Hopfield network-based identifier. The performance of two proposed adaptive controllers is shown through simulations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.889-894
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• 1993

This paper presents a robust adaptive control scheme based on the Lyapunov design for robot manipulators subjected to inertial parameter uncertainties and bounded torque disturbances. The scheme is a modified version of the adaptive computed torque method which adopts a dead zone into the adaptation mechanism so as to avoid parameter drifts by disturbances. It is shown via stability analysis and computer simulations that all the signals in the overall adaptive system are bounded and tracking errors lie within a prespecified bound.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.503-507
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• 1989

A new decentralized adaptive controller design is proposed. In large scale interconnected system with unknown parameters, nonlinearities and bounded disturbances, even though the interconnection is weak, the controller parameter drifts due to the interconnection, so the decentralized adaptive controller comes to be unstable. The proposed new decentralized adaptive controller guarantees exponential convergence of tracking and parameter errors to residual sets which depend on the bound for the local disturbances and interconnections as well as on some arbitrary design parameters.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2008년도 춘계학술발표대회 논문집
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• pp.61-67
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• 2008

In this paper proposed the solar tracking system to use a fuzzy based on PC in order to increase an output of the PV array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studied. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up. nonlinear altitude and azimuth. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• 전자공학회논문지CI
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• 제37권1호
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• pp.11-20
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• 2000

본 논문은 도로영상에서 움직이는 물체 추적을 위한 윤곽선 및 형태 파라미터 추출방법을 제안코자 한다. 축소영상에서 차영상 방법을 이용하여 윤곽선을 추출하고 원영상에서 특징을 추출함으로써 추적의 정확성을 높이고자 한다. 사용된 특징은 물체화소의 원분포, 중심모멘트, 최대${\cdot}$최소비이다. 이를 이용하여 데이터 연상문제를 해결하였으며, 실시간 추적을 위하여 칼만필터를 사용하였다. 제안된 알고리즘에 의해 추출된 특징 벡터는 다중 차량 추적에 적합함을 실험을 통해 보였다.

• Journal of Advanced Marine Engineering and Technology
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• 제38권10호
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• pp.1318-1326
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• 2014

The purpose of a tracking control system is to track a moving target and to find the exact information of the target. If the platform of the tracking control system is equipped on a moving vehicle such as a ship, the tracking control system will treat even the additional platform motion. In order to avoid the complexity comprising the tracking control system, a process to treat the platform motion, named stabilizing system, must be separated from the tracking control system. In this paper, a method to comprise an attitude control system for the platform stabilization is proposed using an adaptive fuzzy control which is applicable to the system with structural and parametric uncertainty. The suggested adaptive fuzzy control algorithm is the 2nd/1st-type indirect adaptive fuzzy control algorithm using the advantages of 1st-type and 2nd-type indirect adaptive fuzzy control algorithm. Several experiments using the implemented stabilizing system are executed for verifying the effectiveness of the suggested method.