• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.268-270
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• 1993

The implementation of Nonlinear Feedback Linearization control for Electro-Magnetic Suspension system is presented. The controller using TMS320C31 DSP chip was proposed and the experiments were performed Control law for EMS system using feedback linearization is derived and implemented in the DSP. Some tests were constructed far experimental comparison between feedback linearization and classical state feedback The experimental results demonstrate that the feedback linearization controller shows bettor performance than that of the classical state feedback controller and it is robust with respect to disturbance and parameter variation, though some steady-state errors appear.

• Journal of Power Electronics
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• 제19권2호
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• pp.569-579
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• 2019

A robust controller is designed based on feedback linearization and sliding mode control to damp sub-synchronous control interaction (SSCI) in doubly fed induction generator (DFIG) wind power plants (WPPs) interfaced with the grid. A feedback-linearized sliding mode controller (FLSMC) is developed for the rotor-side converter (RSC) through feedback linearization, design of the sliding mode controller, and parameter tuning with the use of particle swarm optimization. A series-compensated 100-MW DFIG WPP is adopted in simulation to evaluate the effectiveness of the designed FLSMC at different compensation degrees and wind speeds. The performance of the designed controller in damping SSCI is compared with proportional-integral controller and conventional sub-synchronous resonance damping controller. Besides the better damping capability, the proposed FLSMC enhances robustness of the system under parameter variations.

• 제어로봇시스템학회논문지
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• 제6권2호
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• pp.127-137
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• 2000

This paper presents a novel neural based controller which controls the water level of the nuclear power plant steam generator. The controller consists of a model reference feedback linearization controller and a PI controller for stabilizing the feedback linearization controller. The feedback linearization controller consists of a neural network model and an inversing module which uses the neural network model for computing the control input to the steam generator. We chose Piecewise Linearly Trained Network(PLTN) and Recurrent Neural Netwrok(RNN) for an approximator of the plant and used these approximators in calculating the input from the feedback linearization controller. Combining the above two controllers gives a result of better performance than the case which uses only a PI controller Each control result of PLTN and RNN is given.

• 한국정밀공학회지
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• 제24권4호
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• pp.68-75
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• 2007

In this study, the ultimate goal is to acquire stability when turning around efficiently by using the controller which is applied partial feedback linearization of One-wheel Unicycle Robot. When moving around, linear controller could result in unstable factor according to widening operation range. So in order to reduce instability, 1 have developed Non-linear Controller using Partial Feedback Linearization. Compared with linear controller, Non-linear Controller guarantees the superiority of Regulating Control and Tracking Control in direct and also revolution motion of Robot. I'm sure of the Non-linear controller performance through many experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.936-938
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• 1999

In this Paper, the design of a feedback linearization controller using multilayer neural network is proposed. The Proposed feedback linearization control scheme is designed by finding Lie derivatives from an identified neural networks. Lie derivatives are expressed as a combination of weights and neuron outputs. The proposed method is applied to an antenna arm problem and the simulation results show performance comparisons between the ordinary feedback linearization and the Proposed method.

• Transactions on Control, Automation and Systems Engineering
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• 제2권4호
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• pp.221-227
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• 2000

This paper combines the constrained model predictive control with the feedback linearization to solve a nonlinear system control problem with input constraints. The combined approach consists of two steps: Firstly, the nonlinear model is linearized by the feedback linearization. Secondly, based on the linearized model, the constrained model predictive controller is designed taking input constraints into consideration. The proposed controller is applied to two link robot system, and tracking performances of the controller are investigated via some simulations, where the comparisons are done for the cases of unconstrained, constrained input in feedback linearization.

• Journal of Power Electronics
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• 제9권2호
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• pp.288-299
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• 2009

This paper proposes a feedback linearization control scheme of AC/DC PWM converters with LCL input filters using no damping resisters. Feedback linearization techniques use a transformation from nonlinear system models into equivalent linear models in a simpler form. The feedback linearization scheme in this work has cascade structures unlike usual feedback linearization, therefore it has an advantage that it is possible to limit the capacitor current to a certain level. The performance of the proposed controller is validated with simulation and experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1064-1067
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• 1996

This paper describes the design and implementation of an intelligent controller for continuous casting process. The proposed controller adopted a fuzzy control with feedback linearization. The simulation result shows that proposed intelligent controller is superior to the conventional PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1253-1256
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• 1996

In this paper, a new nonlinear feedback linearization control scheme for induction motors is developed. The control scheme employs a fuzzy nonlinear identification scheme based on fuzzy basis function expansion to adoptively compensate the parameter variations, i.e. rotor resistance, mutual and self inductance etc. An important feature of the proposed control scheme is to incorporate the sliding mode controller into the scheme to speed up convergence rate. Simulation tests show the robust behavior of the proposed controller in the presence of the parameter uncertainties of the machine.

• 한국항공우주학회지
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• 제36권6호
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• pp.558-564
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• 2008

적응제어신호를 저역필터에 통과시켜 점근적 추종과 과도구간 성능을 동시에 보장하는 적응제어 기법과 비선형 시스템을 선형 시불변 형태로 변환하는 피드백 선형화 기법을 결합하여 적응제어 기법의 적용가능 범위를 확대하였다. Barbalat의 보조정리를 이용하여 추종오차가 0으로 수렴함을 증명하고 과도구간의 추종오차도 원하는 크기로 감소시킬 수 있음을 보였다.