• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.174-180
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• 2012

This paper proposes a decentralized adaptive output-feedback controller design for nonlinear interconnected systems with unknown time delays. The interaction terms with unknown delays are related to all states of subsystems. The time-delayed functions are compensated by using appropriate Lyapunov-Krasovskii functionals and function approximation technique. The observer dynamic surface design technique is employed to design the proposed memoryless local controller for each subsystem. In addition, we prove that all signals in the closed-loop system are semiglobally uniformly bounded and control errors converge to an adjustable neighborhood of the origin.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.724-727
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• 2007

선박 운항 자동화 시스템은 선내 노동력 감소, 작업 환경 개선, 운항 안전성 확보 및 운항 능률의 향상을 목표로 하며, 궁극적으로는 운항 경제성확보를 위한 승선 인원의 최소화에 그 목적이 있다. 최근에는 적응 제어방법 등을 응용하여 선박의 비선형성을 보상하여 선박의 회두각 유지제어(Course Keeping Control), 항로 추적제어(Track Keeping Control), 롤-타각제어(Roll-Rudder Stabilization), 선박 위치제어(Dynamic Ship Positioning), 선박자동 접이안(Automatic Mooring Control) 등에 관한 연구를 수행하고 있으며 실제의 선박으로 대상으로 응용연구가 진행 중이다. 선박은 Steering Machine에 의해 조정되는 Rudder angle과 선박의 회두각의 관계는 비선형적이며, 선박의 Load Condition은 선박의 Parameter에 영향을 주는 비선형적인 요소로서 작용한다. 또한 외란요소인 파도의 유속(流速)과 방향, 풍속과 풍량 등이 비선형적인 형태로 작용하므로 선박의 운항을 힘들게 하는 요인이 된다. 따라서 선박의 운항시스템에는 비선형성을 극복할 수 있는 강인한 제어 알고리즘을 요구한다. 본 논문에서는 퍼지 알고리즘을 이용하여 선박의 비선형적인 요인 및 외란을 극복할 수 있는 선박의 자율운항 시스템을 설계하고 시뮬레이션을 통해 그 결과를 살펴보았다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5194-5201
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• 2011

In this paper, an adaptive nonlinear friction compensation scheme for second-order nonlinear mechanical system with a partially known nonlinear dynamic friction is proposed to achieve asymptotic position and velocity tracking in the absence of disturbances and modeling errors. It is also shown that even with disturbances and modeling errors, in contrast to existing other adaptive control schemes, by proper adjustment of design parameters, reduced error bounds on position and velocity tracking can be achieved.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.11
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• pp.990-998
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• 2007

Adaptive output feedback control technique using Neural Networks(NN) is proposed for uncertain nonlinear Multi-Input Multi-Output(MIMO) systems. Modified Dynamic Inversion Model(MDIM) is introduced to decouple uncertain nonlinearities from inversion-based control input. MDIM consists of approximated dynamic inversion model and inversion model error. One NN is applied to compensate the MDIM of the system. The output of the NN augments the tracking controller which is based upon a filtered error approximation with online weight adaptation laws which are derived from Lyapunov's direct method to guarantee tracking performance and ultimate boundedness. Several numerical results are illustrated in the simulation of Van der Pol system and unmanned helicopter with model uncertainties.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.564-570
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• 2003

This paper presents an adaptive fuzzy control scheme for nonlinear helicopter system which has uncertainty or unknown variations in parameters. The proposed adaptive fuzzy controller is a model reference adaptive controller. The parameters of fuzzy controller are adjusted so that the plant output tracks the reference model output. It is shown that the adaptive law guarantees the stability of the closed-loop system by using Lyapunov function. Several experiments with a small model helicopter having parameter variations are performed to show the usefulness of the proposed adaptive fuzzy controller.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1551-1552
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• 2008

본 논문은 네트워크 기반 제어시스템(NCS: Networked Control Systems)에 모델매칭 제어기법을 적용한 효율적인 제어알고리즘을 제안한다. 비선형의 특징을 가지는 제어기 및 관측기의 시간지연을 Taylor 근사법으로 선형화하여 선형시스템 이론을 적용한 모델매칭 제어기를 설계하였다. 또한, 제어기의 차수를 우세극 기법과 극,영점 상쇄기법(Pole-Zero Cancelation)을 통해 저차화한 후 그 타당성을 검증하였다. 제안한 제어알고리즘의 컴퓨터 시뮬레이션을 실시하였으며 기존의 고차 모델매칭 제어기와 비교분석하여 타당성 및 신뢰성을 검증하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.395-399
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• 2001

This paper describes modular fuzzy inference systems(MFIS) with adaptive capability to extract fuzzy inference modules from observation data through the learning process. The proposed MFIS is based on the structural similarity to Tagaki-Sugeno fuzzy models and a modular neural architecture. The learning of MFIS is done by assigning new fuzzy inference modules and by updating the parameters of existing modules. The fuzzy inference modules consist of local model network and fuzzy gating network. The parameters of the MFIS are updated by the standard LMS algorithm. The performance of the MFIS is illustrated with adaptive control of a nonlinear dynamic system.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.851-853
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• 2016

본 논문은 물류 작업을 위한 지상 보행이 가능한 드론의 제어기를 개선시키기 위한 방법 중 하나로 비선형 자세제어기를 적용한 결과를 보여준다. 로봇은 물류 작업을 위하여 설계되었는데, 페이로드의 변화에 따라서 모델 파라미터가 변하기 때문에 특별한 제어기가 필요하다. 따라서 기존 연구에서 제안되었던 비선형 적응제어기를 채택하여 실험 모델에 적용시켰다. 실험은 실내에서 진행되었고 초기 조건에서 30초 간 자세 안정화 명령의 응답 특성을 확인하는 방식으로 진행되었고, 제어기의 실효성과 안정성을 입증했다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.4
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• pp.730-737
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• 2001

In this paper, an stabilization control method using adaptive neuro-fuzzy controller(ANFC) is proposed for modeling of nonlinear complex systems. The proposed adaptive neuro-fuzzy controller implements system structure and parameter identification using the intelligent schemes together with optimization theory, linguistic fuzzy implication rules, and neural networks from input and output data of processes. The results show that the proposed method can produce the intelligence model with higher accuracy than other works achieved previously.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.5 no.1
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• pp.57-64
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• 1991

The paper considers a distributed adaptive control technique for Industrial Robots which contribute to the factory automation. The control object is to tracking for a desired trajectories under various load conditions, rapidly against load variation. These control techniques divided whole system into subsystems which is controlled with the Nominal and Adaptational controllers. And also the asymptotic stability of these substem was proved. Simulation results shown that the proposed techniques was feasible in spite of nonlinear dynamics of robot manipulator and payload variations.