In this paper, the output feedback control problem for a genetic hypersonic vehicle is considered under the restriction that only the vehicle's velocity and altitude are measurable. High gain observers (HGO) are utilized to provide estimation signals for unmeasurable derivatives of the vehicle's velocity and altitude. Neural network based feedforward function is designed to compensate for model uncertainties. The proposed control design require less knowledge of the hypersonic vehicle's dynamic model. A comprehensive stability analysis of the closed loop system under the output feedback control is carried to prove that the proposed control law yields semiglobal uniformly ultimately bounded tracking while keeping all the closed loop signals bounded. Numerical simulation results are presented to validate the proposed control design.Keywords hypersonic vehicle, nonlinear, output feedback control, neural network, high gain observer
CitationLi X D, Xian B, Diao C, et al. Output feedback control of hypersonic vehicles based on neural network and high gain observer.
Once an asymmetrical fault occurs on the AC side of the receiving-end of a high-voltage direct current (HVDC) transmission system, the current reference will be affected by the control regulation on the DC inverter side and the commutation voltage asymmetry. In this case, the advance firing angle will fluctuate periodically, causing security threats to the system. If the fault cannot be cleared in time, the effect may be even more serious. However, the traditional proportional-integral (PI) controller cannot effectively suppress the periodic components in the input error signal, which is an important cause of continuous commutation failure. Thus, the system requires more time to recover from the fault. Motivated by this, a selfadaptive auto-disturbance rejection PI controller is proposed in this study. The controller has the advantages of fast response speed and strong anti-interference ability of the auto-disturbance rejection controller. On one hand, it can automatically adjust PI, and the parameters can maintain the system' s adaptive ability. On the other hand, the discretization process satisfies the computer simulation requirements. By applying the proposed controller to a system under constant current control and extinction angle control, the dynamic response speed can be improved and the robust performance of the system can be ensured when dealing with a wide range of perturbations. Finally, simulation results show that the proposed algorithm can effectively suppress the continuous commutation failure of DC transmission systems.
Ion-adsorbed rare earth minerals have rare earth ions adsorbed on the surfaces of clay minerals such as kaolinite and have high contents of medium and heavy rare earth elements. They are important resources supporting the development of high-tech industries. In this study, the CASTEP module in Materials Studio was used to study the adsorption of the rare earth ion Y(III) on the interface of (Al-OH)-H2O and (Si-O)-H2O with density functional theory. The monitoring and calculation of the chemical bond of the adsorption structure showed that Y(III) on the (Al-OH)-H2O interface has a bond with O32, O34, and water molecules in the interface. In the (Si-O)-H2O interface, Y(III) interacts with O3, O4, and O10 to form new chemical bonds. The Mulliken population and density of states analysis showed that Y(III) bonds with surface oxygen atoms and water molecules in the kaolinite-H2O interface, and finally adsorbs on the surface of kaolinite in the form of metal ion hydrate.
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