• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.506-506
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• 2000

To improve control performance of a non-linear system, many other researches have used the sliding mode control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However. this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network generates the control input for compensating unmodeled dynamics terms and disturbance. And, the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors to converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluating control performance of the proposed approach. tracking control simulation is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.228-235
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• 2010

This paper deals with an autonomous flight controller design problem for a tilt-rotor aircraft in rotary-wing mode. The inner-loop algorithm is designed using the output-based approximate feedback linearization. The model error originated from the feedback linearization is cancelled within allowable tolerance by using single-hidden-layer neural network. According to Lyapunov direct stability theory, the adaptive update law is derived to run the neural network on-line, which is based on the linear observer dynamics. Moreover, the outer-loop algorithm is designed to track the trajectory generated from way-point guidance. Especially, heading and flight-path angle line-of-sight guidance are applied to the outer-loop to improve accuracy of the landing tracking performance. The 6-DOF nonlinear simulation shows that the overall performance of the flight control algorithm is satisfactory even though the collective input response shows instantaneous actuator saturation for a short time due to the lack of the neural network and the saturation protection logic in that loop.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.82-88
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• 2005

A compensation scheme for a class of linearly parameterized systems is presented. The compensator consists of a typical linearizing control and an adaptive observer with integration type update law, which is based on Speed Gradient (SG) algorithm.. Instead of the intermediate functions of the compensation schemes suggested by other researchers, the proposed compensator is designed with some design functions which guarantee the growth, convexity, attainability, and pseudo gradient conditions in the update law. The scheme achieves the asymptotic stability of the tracking error and the boundedness of the estimation errors. A numerical example is given to demonstrate the validity of the proposed design.