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This paper introduces a scheme for waypoint-based path-following control for an Unmanned Robot Sailboat (URS) in the presence of actuator gain uncertainty and unknown environment disturbances. The proposed scheme has two components: intelligent guidance and an adaptive neural controller. Considering upwind and downwind navigation, an improved version of the integral Line-Of-Sight (LOS) guidance principle is developed to generate the appropriate heading reference for a URS. Associated with the integral LOS guidance law, a robust adaptive algorithm is proposed for a URS using Radial Basic Function Neural Networks (RBF-NNs) and a robust neural damping technique. In order to achieve a robust neural damping technique, one single adaptive parameter must be updated online to stabilise the effect of the gain uncertainty and the external disturbance. To ensure Semi-Global Uniform Ultimate Bounded (SGUUB) stability, the Lyapunov theory has been employed. Two simulated experiments have been conducted to illustrate that the control effects can achieve a satisfactory performance.
The Be-based materials with many particular properties lead to an important research subject. The investigation progresses in the fabrication technologies are introduced here, including main three kinds of Be-based materials, such as Be–Cu capsule,
ablator and high-purity Be material. Compared with the pioneer workgroup on Be-based materials, the differences in Be–Cu target fabrication were described, and a grain refinement technique by an active hydrogen reaction for Be coating was proposed uniquely.
coatings were first prepared by the DC reactive magnetron sputtering with a high deposition rate
. Pure polycrystalline
films with uniform microstructures, smooth surface, high density
and good optical transparency were fabricated. In addition, the high-purity Be materials with metal impurities in a ppm magnitude were fabricated by the pyrolysis of organometallic Be.
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