Helicopter system adaptive neural network control method based on specified performance constraint

A neural network control and neural network technology, which is applied in the field of adaptive neural network control of helicopter systems based on specified performance constraints, can solve problems such as actuator overrun and closed-loop system instability, achieve less sensors and control, and improve robustness. , the effect of precise tracking and control

Pending Publication Date: 2022-07-12
GUANGZHOU UNIVERSITY
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Problems solved by technology

For example, large overshoots can cause the actuator to exceed physical limits, leading to instability in the closed-loop system
Research on transient performance such as overshoot and convergence speed is for further consideration

Method used

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  • Helicopter system adaptive neural network control method based on specified performance constraint
  • Helicopter system adaptive neural network control method based on specified performance constraint
  • Helicopter system adaptive neural network control method based on specified performance constraint

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Embodiment 1

[0096] like figure 1 As shown, this embodiment provides an adaptive neural network control method for a helicopter system based on a specified performance constraint, which includes the following steps:

[0097] Step 1: Build the nonlinear model of the 2-DOF helicopter system;

[0098] In step 1, according to the Lagrangian mechanics model, the nonlinear dynamic equation of the system is as follows:

[0099]

[0100] Among them, J b and J d are expressed as moments of inertia about the pitch and yaw axes, respectively, V c is the voltage applied to the pitch rotor motor, V d is the voltage applied to the yaw rotor motor; M d represents the mass of the helicopter, l c Indicates the distance from the center of mass to the origin of the fixed frame of the fuselage, θ represents the pitch angle, φ represents the yaw angle, and K cpp Represents the torque thrust gain acting on the pitch axis in the pitch propeller, K cpy Represents the torque thrust gain acting on the pi...

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Abstract

The invention relates to the technical field of helicopter system control, and relates to a helicopter system adaptive neural network control method based on specified performance constraints, comprising the following steps: step 1, establishing a nonlinear model of a 2-DOF helicopter system; 2, introducing a performance function to help to evaluate the specified performance of the system; 3, designing a controller; 4, constructing an adaptive law according to the controller; 5, constructing a Lyapunov equation, and verifying the stability of the 2-DOF helicopter system; and 6, performing simulation, and checking and analyzing a simulation effect. According to the invention, the helicopter system can be well controlled.

Description

technical field [0001] The invention relates to the technical field of helicopter system control, in particular to an adaptive neural network control method for a helicopter system based on specified performance constraints. Background technique [0002] In recent years, drones have been widely used in aerial photography, agriculture, plant protection, express transportation, disaster relief, manufacturing and other fields. Unmanned helicopters have attracted the attention of many people because of their good advantages. In practical applications, the helicopter control system is a complex nonlinear system with multiple inputs and multiple outputs, which puts forward higher requirements for the controller design of the helicopter; at the same time, the helicopter system itself is also subject to mechanical design and safety constraints. There are constraints, if the system constraints are ignored in the control process, the system performance may be degraded, and even lead ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042Y02T90/00
Inventor 邹涛吴辉源赵志甲李致富马鸽
Owner GUANGZHOU UNIVERSITY
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