• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.115-123
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• 1997

이산기간 H/sub .inf./ 제어에 의한 최적 예견제어기를 제안한다. 기존의 H/sub .inf./ 제어기는 미지의 외란만 고려한 것이고, LQ 에 의한 예견제어기는 예견 가능한 외란과 미지의 외란이 동시에 가해지는 동적 시스템의 전달함수 행렬의 infinity 놈의 최소화하는 피드백제어기가 동시에 설계된다. 제어기의 설계는 full-information H/sub .inf./ 제어 이론을 따르나, 그 유도 과정은 LQ 에 기초한 예견제어기와 유사하게 이루어진다. 설계된 H/sub .inf./ 예견 게인 행렬은 LQ 예견 게인 행렬과 유사한 구조를 갖는다. 전달함수 행렬의 infinity 놈이 .inf.로 갈수록 H/sub .inf./ 예견 게인 행렬은 LQ에 의한 것에 접근한다. LQ 예견 게인 행렬은 H/sub .inf./ 예견 게인 행렬의 부분 집합임이 입증한다.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.61-66
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• 1997

로보트 매니퓰레이터가 일정한 접촉 힘을 유지하며 공작물의 표면을 따라가게 하는 작업은 많은 자동화 생산공정에서 유용하게 이용될 수 있다. 일반적인 위치제어용 산업용 로보트를 이러한 공정에 사용하기 위해서는 접촉힘이 계측되어 로보트의 제어에 이용되어야만 한다. 이 연구는 accommodation force control 방식으로 산업용 로보트를 제어하여 edge-following에 응용하도록하며, 접촉 힘의 계측에는 wrist force sensor를 사용한다. 이 시스템의 궤도추적속도와 force regulation 등이 예견제어에 의해 향상될 수 있다. 예견제어에 의해 설계된 전체 제어 시스템은 feedback 제어기와 feedforward 예견제어기로 구성된다. 여기서, 시스템의 안정성은 feedback 제어기에 의해서 결정되며, 예견제어기는 시스템에 미치는 외란을 통제하는 것을 주 기능으로 한다. 일반적으로 선형제어 방식을 채택한 경우와 예견제어를 이용한 edge-following을 실험을 통해 비교함으로써, 예견제어의 효용성을 확인한다.

• ICROS
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• v.1 no.3
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• pp.101-108
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• 1995

이 글에서는 퍼지제어기의 기본 구성에 대해 간단히 다루고 모델에 근거해 다음 제어상태를 예견해 내는 제어기법인 모델참조 적응을 기반으로 한 적응 퍼지제어에 대해서, 그리고 신경회로망을 이용한 퍼지제어기의 파라미터의 조정과 클러스터링을 통해서 퍼지규칙을 예측하는 적응 퍼지제어기에 대해서 살펴보았다.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.9
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• pp.2142-2153
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• 1995

A digital preview controller using optimal LQ control theory is suggested for tandem cold mills to achieve a remarkable improvement of the thickness accuracy. Optimal preview control system is constructed for each rolling stand of tandem cold mills for which the blocked noninteracting control is carried out, and it is compared with the optimal LQ control system which has only feedback control. And in the cases that all/some of disturbance inputs are previewable, full and partial preview controllers are designed, and their performance effects are compared and discussed. The simulation results show that the performance of tandem cold mills can be improved largely through partial preview control.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.7
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• pp.114-122
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• 1995

A digital preview controller is designed for tandem cold mills to achieve a more improvement of the thickness accuracy. Simultaneously a blocked noninteracting controller is synthesized for rejecting the interactive effects among adjacent stands and for controlling independently each roll stand of tandem cold mills. The performance effects and characteristics of the suggested roll contol system are discussed in the practical viewpoint. The simulaltion results show that the thickness accuracy of tandem cold mills can be largely improved by the blocked noninteracting and digital preview controller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.115-119
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• 2007

In this paper, practical problems will be covered in applying preview control to real tracked vehicle systems. Previous researches about the preview control assume that the vehicle speed is constant and the actuators have full frequency bandwidth. However, in order to apply it to real systems, those should be taken into account. Therefore this paper show the algorithm to apply the preview control to speed changing vehicles and performance variation according to a restricted frequency bandwidth.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.892-895
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• 1996

An unknown input observer is proposed that can be used in wheelbase preview control of commercial vehicles. The preview and state information, required to calculate actuator force, are reconstructed from the measurement variables such as heave and pitch acceleration. Gain matrix of observer is optimally selected so that influence of system and measurement noises on the estimation error can be minimized. Estimated preview information requires low pass filtering to eliminate high frequency components resulting from differentiation of noisy output signals. Effectiveness of the proposed method is demonstrated by numerical simulation of half car model.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.4
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• pp.15-26
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• 1998

Full car model is needed for investigating as a entire dynamics of vehicle. In this study, 7DOF of full car model's dynamics is selected. This paper proposes the output feedback controller based on optimal control theory. Input data and output data from the optimal controller are used for neural network system identification of the suspension system. To do system identification, neural network which has robustness against nonlinearities and disturbances is adapted. This study uses back-propagation algorithm to train a multil-layer neural network. After obtaining a neural network model of a suspension system, a neuro-controller is designed. Neuro-controller controls suspension system with off-line learning method and multistep ahead prediction model based on the neural network model and a neuro-controller. The optimal controller and the neuro-controller are designed and then, both performances are compared through. For simulation, sinusoidal and rectangular virtual bumps are selected.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.293-298
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• 1995

A digital preview controller is designed for tandem cold mills to achieve a better improvement of the thickness accuracy. And simultaneously a blocked noniteracting controller is synthesized for rejecting the interactive effects among adjacent stands and for controlling independently each roll stand of landem cold mills. The performance effects and characteristics of the suggested roll control system are discussed in the practical view points. The simulation results show that the thickness accuracy of tandem cold mills can be largely improved by the blocked noninteracting and digital preview contoller.

• Journal of Drive and Control
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• v.14 no.2
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• pp.9-15
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• 2017

The steering systems of all-terrain cranes have been developed with various control strategies for the stability and drivability. To optimally control the input steering angle, an accurate mathematical model that represents the actual crane dynamics is required. The derivation of an accurate mathematical model to optimally control the steering angle, however, is difficult since the steering-control strategy generally varies with the magnitude of the crane's longitudinal velocity, and the postures of the crane's working parts vary while it is being driven. To address this problem, this paper proposes an automatic steering-control algorithm that is based on the MPC (model predictive control) with a disturbance observer for all-terrain cranes. The designed disturbance observer of this study was used to estimate the error between the base steering model and the actual crane. A model predictive controller was used for the computation of the optimal steering angle, along with the use of the base steering model with an estimated uncertainty. Performance evaluations of the designed control algorithms were conducted based on a curved-path scenario in the Matlab/Simulink environment. The performance-evaluation results show a sound reference-path-tracking performance despite the large uncertainties.