• Proceedings of the KSME Conference
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• 2001.06b
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• pp.253-258
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• 2001

This paper introduces a simple nonlinear adaptive control method for pipeline inspection gauge (PIG) flow in natural gas pipeline. The dynamic behavior of the PIG depends on the different pressure across its body and the bypass flow through it. The system dynamics includes: dynamics of driving gas flow behind the PIG, dynamics of expelled gas in front of the PIG, and dynamics of the PIG. The method of characteristics (MOC) and Runger-Kuta method are used to solve the dynamics of flow. The PIG velocity is controlled through the amount of bypass flow across its body. A simple nonlinear adaptive controller based on the backstepping method is introduced. To derive the controller, three system parameters should be measured: the PIG position, its velocity and the velocity of bypass flow across the PIG body. The simulation has been done with a pipeline segment in the KOGAS low pressure system, Ueijungboo-Sangye line to verify the effectiveness of the proposed controller. Three cases of interest are considered: the PIG starts to move at its launcher, the PIG arrives at its receiver and the PIG restarts after stopping in the pipeline by obstruction. The simulation results show that the proposed nonlinear adaptive controller attained good performance and can be used for controlling the PIG velocity.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.494-499
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• 2013

Based on the state-feedback adaptive neuro-control algorithm for a SISO nonaffine pure-feedback nonlinear system proposed in [15], an output-feedback controller is proposed in this paper. The output-feedback adaptive neural-net controller for the considered nonlinear system has not been previously proposed in any other literatures yet. The proposed output-feedback controller inherits all the advantages of [15] such that it does not adopt backstepping and this results in relatively simple control and adapting laws. Only one neural network is required for the proposed adaptive controller. The proposed neural-net control scheme expands the applicable class of nonlinear systems.

• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.115-117
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• 1997

본 논문에서는 유도전동기의 적응 비선형 제어에 대해 논한다. 제어 목적은 회전자저항의 불확실성에도 불구하고 유도전동기의 속도 및 자속을 분리하여 제어하는 것이며, 이를 위해 백스테핑(Backstepping) 기법을 사용한 비선형제어기와 회전자 저항 추정기를 결합한다. 제안된 적응제어시스템은 내부의 모든 변수가 유계(Bounded)되어 있다는 점에서 안정하며, 더불어 그 개선된 성능을 모의실험을 통해 보인다.