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Rigid aircraft nonsingular fixed time attitude stabilization method based on neural network estimation

A fixed time, neural network technology, applied in attitude control, instrumentation, non-electric variable control, etc.

Inactive Publication Date: 2019-01-08
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0005] In order to overcome the unknown nonlinear problem existing in the existing rigid aircraft attitude control system, the present invention provides a non-singular fixed-time attitude stabilization method for rigid aircraft based on neural network estimation, and when the system has external disturbances and uncertain moments of inertia A control method that achieves a constant-time uniformly ultimately bounded system state under

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  • Rigid aircraft nonsingular fixed time attitude stabilization method based on neural network estimation
  • Rigid aircraft nonsingular fixed time attitude stabilization method based on neural network estimation
  • Rigid aircraft nonsingular fixed time attitude stabilization method based on neural network estimation

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[0072] The present invention will be further described below in conjunction with the accompanying drawings.

[0073] refer to Figure 1-Figure 6 , a non-singular fixed-time attitude stabilization method for rigid aircraft based on neural network estimation, the control method comprising the following steps:

[0074] Step 1, establish the kinematics and dynamics model of the rigid aircraft, initialize the system state and control parameters, the process is as follows:

[0075] 1.1 The kinematic equation of the rigid aircraft system is:

[0076]

[0077]

[0078] where q v =[q 1 ,q 2 ,q 3 ] T and q 4 are the vector part and the scalar part of the unit quaternion respectively and satisfy q 1 ,q 2 ,q 3 are the values ​​mapped on the x, y, and z axes of the space Cartesian coordinate system; respectively q v and q 4 derivative of for q v transpose of ; Ω∈R 3 is the angular velocity of the rigid vehicle; I 3 is R 3×3 identity matrix; Expressed as:

[0...

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Abstract

A rigid aircraft nonsingular fixed time attitude stabilization method based on neural network estimation designs a nonsingular fixed time sliding mode surface specific to a rigid aircraft attitude stabilization problem with concentrated uncertainty, so that not only fixed time convergence of state is guaranteed, but also a singular value problem is solved; and a function that a neural network approaches the total uncertainty is introduced, and a nonsingular neural network fixed time controller is designed. The method provided by the invention realizes fixed time uniform ultimate boundedness control on the state of an aircraft system under the condition that external disturbance and rotational inertia are uncertain.

Description

technical field [0001] The invention relates to a non-singular fixed-time attitude stabilization method for a rigid aircraft based on neural network estimation, in particular to an attitude stabilization method for a rigid aircraft with external disturbance and uncertain moment of inertia matrix. Background technique [0002] Rigid aircraft attitude control systems play an important role in the healthy and reliable motion of rigid aircraft. In a complex aerospace environment, the rigid aircraft attitude control system will be affected by various external disturbances and uncertain moment of inertia matrices. In order to effectively maintain the performance of the system, it needs to be robust to external disturbances and uncertain moment of inertia matrix. As a typical nonlinear control method, sliding mode variable structure control can effectively improve the stability and maneuverability of rigid aircraft, and has strong robustness, thereby improving the ability to perfo...

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Application Information

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IPC IPC(8): G05D1/08
CPCG05D1/0808
Inventor 陈强谢树宗孙明轩
Owner ZHEJIANG UNIV OF TECH
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