Nonlinear self-adaption control method of near-space hypersonic vehicle

An adaptive control and hypersonic technology, applied in the field of flight control, can solve the problems of many weight parameters, time-consuming calculation, poor approximation effect, etc.

Inactive Publication Date: 2011-01-05
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

This method does not require uncertain information, but it is a static mapping method, which does not perform well in the approximation of fast dynamically changing disturbances
Recurrent neural network is a kind of dynamic mapping network, which is suitable for approximating high-order nonlinear dynamic functions, but ordinary recurrent network needs to learn more weight parameters, which will lead to excessive calculation time when applied to attitude control

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  • Nonlinear self-adaption control method of near-space hypersonic vehicle

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Embodiment

[0082] 1) The established NHV six-degree-of-freedom twelve-state equation (Zhu Liang, Uncertain Nonlinear Robust Adaptive Control of Aerospace Vehicles, Doctoral Thesis of Nanjing University of Aeronautics and Astronautics, 2006) is used as the controlled object model, and the equation The three airflow attitude angle (attack angle α, side slip angle β, track roll angle μ) equations and three angular velocity (p, q, r) equations around the body axis are written in the form of affine nonlinear equations, extracting It is used as the controlled variable equation for designing nonlinear predictive control law. The six variable equations are divided into two subsystems—an angular rate fast loop and an attitude angle slow loop, the expressions are as follows:

[0083] ω · = f f ( ...

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Abstract

The invention discloses a nonlinear self-adaption control method of near-space hypersonic vehicle (NHV), which belongs to a flight control method in the technical field of aerospace. The control method mainly comprises three control law parts: a nominal nonlinear generalized predictive control law (NGPC), a B-spline recursive functional linkage network (BRFLN) self-adaption control law, and a robust control law of gain self-adaption adjustment. The invention integrates the simplicity of the NGPC method and the effectiveness of dynamic uncertainty of the BRFLN learning, targets the immeasurable dynamic uncertainty and fast interference of an attitude system in the flight of the NHV, brings favorable learning effect, and realizes the nonlinear accurate control to the attitude angle.

Description

technical field [0001] The invention relates to a flight control method in the field of aerospace technology, in particular, a nonlinear adaptive control method, especially suitable for the attitude control method of hypersonic aircraft in near space with model height uncertainty and fast-changing interference. Background technique [0002] Due to the characteristics of large flight envelope, complex flight environment, high maneuverability, and multi-mission mode, near-space hypersonic vehicles (NHV) inevitably have uncertainties caused by internal structure and aerodynamic parameters, as well as external environment. In addition, when flying in the near-space region, the state variables are highly coupled, showing strong nonlinear dynamic characteristics. These factors will increase the difficulty of attitude control algorithm design. If the classical linear control method is used, the control accuracy will decrease or even the system will become unstable. Therefore, the ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/08G05B13/04
Inventor 都延丽吴庆宪姜长生陈谋王玉惠王宇飞
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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