Neural Network and Nonlinear Continuous Unmanned Helicopter Attitude Control Method

An unmanned helicopter and neural network technology is applied in the research field of autonomous flight control of small rotary-wing unmanned aerial vehicles, which can solve the problems of staying, unknown availability of actual flight, and high degree of dependence on system models.

Active Publication Date: 2016-06-01
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 dependence on the system model, and it is still unknown whether they are available for actual flight

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  • Neural Network and Nonlinear Continuous Unmanned Helicopter Attitude Control Method
  • Neural Network and Nonlinear Continuous Unmanned Helicopter Attitude Control Method

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Embodiment Construction

[0087] Aiming at the problem of attitude control of unmanned helicopter, the attitude dynamic model of unmanned helicopter is analyzed first. Then a nonlinear continuous robust control algorithm based on neural network feed-forward compensation is designed, and the stability analysis based on Lyapunov method is carried out, which proves that the designed controller can realize the semi-global progressive tracking control of the attitude of the unmanned helicopter. The flight test results of attitude control show that the invention can make the unmanned helicopter realize fast and accurate stabilization control, and has good robustness to the uncertainty of the system.

[0088] The invention proposes a novel attitude control method for small unmanned helicopters based on neural network feedforward and nonlinear continuous robustness. This method has strong adaptability to the uncertainty of the system model and the interference of the environment, and can significantly improve ...

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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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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/08
Inventor 鲜斌刘世博张垚赵勃
Owner TIANJIN UNIV
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