Control method for neural network and nonlinear continuous unmanned helicopter attitude

An unmanned helicopter and neural network technology, applied in the research field of autonomous flight control of small rotor-type unmanned aerial vehicles, can solve problems such as high dependence on system models, dwelling, and unknown availability of actual flight

Active Publication Date: 2014-04-30
TIANJIN UNIV
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Problems solved by technology

However, most of them are still in simulation experiments, and have a high degree of depende

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  • Control method for neural network and nonlinear continuous unmanned helicopter attitude
  • Control method for neural network and nonlinear continuous unmanned helicopter attitude
  • Control method for neural network and nonlinear continuous unmanned helicopter attitude

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[0088] Aiming at the attitude control problem of unmanned helicopter, the attitude dynamics model of unmanned helicopter is first analyzed. Then a nonlinear continuous robust control algorithm based on neural network feedforward compensation is designed, and stability analysis based on the Lyapunov method is carried out. It is proved that the designed controller can realize the semi-global progressive tracking control of the unmanned helicopter attitude. The experimental results of attitude control flight show that the present invention can enable the unmanned helicopter to achieve rapid and accurate stabilization control, and has good robustness to the uncertainty of the system.

[0089] The present invention proposes a novel attitude control method for a small unmanned helicopter based on neural network feedforward and nonlinear continuous robustness. This method has strong adaptability to the uncertainty of the system model and environmental interference, and can significantly...

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Abstract

The invention belongs to the field of autonomous flight control research of small-scale rotary wing type unmanned aerial vehicles, and provides a control method for an unmanned helicopter. The control method achieves rapid and accurate stabilization control over the unmanned helicopter, and has the good robustness for system uncertainty. According to the adopted technical scheme, the control method for a neural network and a nonlinear continuous unmanned helicopter attitude comprises the steps of firstly, analyzing a dynamic model of the small-scale unmanned helicopter, and giving the following rigid body dynamics model which is shown in formula in the specification; secondly, controlling the unmanned helicopter attitude to obtain the following closed-loop system which is shown in the formula of the specification. The control method is mainly applied to design and manufacturing of the small-scale rotary wing type unmanned aerial vehicles.

Description

technical field [0001] The present invention belongs to the research field of autonomous flight control of small rotor type unmanned aerial vehicles, and is mainly aimed at the control algorithm design of a single rotor unmanned aerial vehicle, including the design of nonlinear robust attitude control law and attitude flight control experiments. Neural Network and Nonlinear Continuous Robust Control Method for Unmanned Helicopter Attitude Control. Background technique [0002] Unmanned aircraft, referred to as UAV, refers to an unmanned aircraft that can be manipulated by wireless remote control or program control. UAVs were born in the 1920s and have developed rapidly since the 1950s. UAVs have the characteristics of flexibility, low cost, easy portability, and multiple uses. By loading the UAV with an automatic flight control system and integrating various airborne sensors, image acquisition equipment, and wireless communication equipment, it can be completed. Manned air...

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Application Information

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IPC IPC(8): G05D1/08
Inventor 鲜斌刘世博张垚赵勃
Owner TIANJIN UNIV
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