• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.379-380
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• 2011

• Journal of the Korean Society for Precision Engineering
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• v.15 no.10
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• pp.165-171
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• 1998

An axial electromagnetic levitation system using attractive force is a highly nonlinear system due to the nonlinearity of materials, variable air gap and flux density. To control the levitating system with large air gap, a conventional PID control based on the linear model is not satisfactory to obtain the desired performance and the position tracking control of the sinusoidal motion by simulation results. Thus, sliding mode control(SMC) based on the input-output linearization is suggested and evaluated by simulation and experimental approaches. Usefulness of the SMC to this system is conformed experimentally. If the expected variation of added mass can be included in the gain conditions and the model, the position control performance of the electromagnetic levitation system with large air gap will be improved with robustness.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.4
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• pp.24-33
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• 2004

In this paper, the helicopter flight control system using online adaptive neural networks which have the universal function approximation property is considered. It is not compensation for modeling errors but approximation two functions required for feedback linearization control action from input/output of the system. To guarantee the tracking performance and the stability of the closed loop system replaced two nonlinear functions by two neural networks, weight update laws are provided by Lyapunov function and the simulation results in low speed flight mode verified the performance of the control system with the neural networks.