Journal
JOURNAL OF MARINE SCIENCE AND ENGINEERING
Volume 11, Issue 1, Pages -Publisher
MDPI
DOI: 10.3390/jmse11010138
Keywords
model reference adaptive control; environmental compensation; wavelet neural network; approximation using incomplete states
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Adaptive control methods are used to adapt to coastal and nearshore physics for offshore steel structures subject to harmful vibrations. A compensating measure containing the ocean environment is proposed to decrease the dependence on accurate characteristics of the offshore platform. Numerical experiments show the effectiveness of the adaptive controller in reducing excessive vibration.
Adaptive control methods are suitable for offshore steel structures subject to harmful vibrations, as they employ reference models to adapt to coastal and nearshore physics. To decrease the dependence on the accurate characteristics of the offshore platform, a compensating measure containing the ocean environment is proposed in the adaptive control scheme. With incomplete states as the driving input, external loads are approximated using a wavelet neural network frame. Numerical experiments are conducted on a platform model with varying parameters to test the performance of the proposed adaptive controller. It is shown that the adaptive weights derived from the chosen Lyapunov function are qualified both theoretically and practically. The system-output-based adaptive controller overcomes the disadvantage of state loss. The compensated disturbance environment guarantees the reliability of the restored reference system based on mismatched physics. The designed estimator as a part of the adaptive controller compensates for the deviations of the environment between the reference and the practical, resulting in a desirable reduction in the excessive vibration.
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