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Intelligent setting method for unmanned aerial vehicle attitude control parameters based on quantum firefly algorithm

A firefly algorithm and parameter tuning technology, which is applied in the field of intelligent tuning of UAV attitude control parameters based on the quantum firefly algorithm, can solve problems such as reduced convergence speed, falling into local optimum, and low accuracy of optimization convergence

Active Publication Date: 2021-04-02
NORTHWESTERN POLYTECHNICAL UNIV +1
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AI Technical Summary

Problems solved by technology

[0005] In order to overcome the shortcomings of the existing parameter tuning methods, such as the low convergence accuracy of the UAV fractional order controller parameter optimization, the serious decrease in the convergence speed in the later stage, and the tendency to fall into local optimum

Method used

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  • Intelligent setting method for unmanned aerial vehicle attitude control parameters based on quantum firefly algorithm
  • Intelligent setting method for unmanned aerial vehicle attitude control parameters based on quantum firefly algorithm
  • Intelligent setting method for unmanned aerial vehicle attitude control parameters based on quantum firefly algorithm

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Experimental program
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Effect test

Embodiment 1

[0110] Example 1 uses the test function to verify the solution accuracy and convergence of the quantum firefly algorithm

[0111] In order to verify the improvement effect of the improved algorithm in terms of solution accuracy and convergence, the standard test functions Rosenbrock function and Rastrigin function were selected to compare the effect of the algorithm before and after the improvement. The function is Y=f(X)=-g h (X)h=Rosenbrock, Rastrigin, the mathematical expressions and global optimal solutions of the two functions are given in Table 1.

[0112] Suppose there are N quantum fireflies in the quantum firefly group, F=(X Q1 ,X Q2 ,...,X Qi ,...,X QN ), 1≤i≤N, the state X of each individual quantum firefly Q Parameter X of available test functions Q =(θ 1 ,θ 2 ) is the optimization design variable; [Down k ,Up k ] is the optimization range of the kth design variable, Up k is the range upper bound, Down k is the lower bound of the range; X Qi =(θ 1i ,θ...

Embodiment 2

[0132] Example 2 Feasibility verification of parameter tuning of quadrotor UAV by quantum firefly algorithm

[0133] Refer to attached Figure 1-7 , the specific implementation steps of the inventive method are as follows:

[0134] Step 1. Establish a typical quadrotor UAV pitch attitude kinematics model as follows:

[0135]

[0136] In the formula, p is the rolling angular velocity of the UAV; q is the pitching angular velocity of the UAV; is the pitch angular acceleration of the UAV; r is the yaw angular velocity of the UAV; I y is the moment of inertia of the UAV on the y-axis; τ y is the moment of the UAV on the y-axis;

[0137] The moment of inertia of a certain type of quadrotor aircraft is: I x =0.045kgm 2 , I y =0.06kgm 2 , I z =0.083kgm 2

[0138] p=0.06cos(0.3t)rad / s, r=0.04cos(0.6t)rad / s

[0139] Transform formula (1) into the integral chain model form of formula (2):

[0140]

[0141] In the formula, x 1 = θ is the pitch angle of the UAV.

...

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Abstract

The invention provides an intelligent setting method for unmanned aerial vehicle attitude control parameters based on a quantum firefly algorithm, and belongs to the field of automatic control. The method comprises the steps of building an unmanned aerial vehicle attitude motion model, designing a fractional order PID controller, determining a to-be-set parameter, and selecting an error index function as an objective function; setting parameters of the quantum firefly algorithm; executing the quantum firefly algorithm to perform controller parameter setting optimization, and obtaining the optimal controller parameter and the objective function value of the current setting; judging whether the objective function value meets requirements or not; if the objective function value meets the requirement, determining that the firefly position is the optimal attitude controller parameter, and ending the setting; otherwise, returning to the step 2, resetting the parameters of the quantum fireflyalgorithm, and executing the steps 2-4. According to the method, on the basis of a standard firefly algorithm, improvement is carried out by utilizing a quantum theory, elite retention and mutation behaviors, and the defects that the later convergence speed of the standard firefly algorithm is seriously reduced, the convergence precision is not high, and local optimum is likely to happen in the prior art are overcome.

Description

technical field [0001] The invention belongs to the field of automatic control, and in particular relates to a method for intelligently setting UAV attitude control parameters based on the quantum firefly algorithm. Background technique [0002] Although the fractional-order PID controller of the quadrotor UAV has better control performance than the PID control, the controller parameters are greatly increased compared with the PID control. Due to the nonlinear characteristics of the fractional-order differential, the parameter tuning of the fractional-order controller Problems such as multi-variable, nonlinear, and multi-extreme values ​​are presented, and it is difficult to obtain an analytical tuning method similar to PID controller parameters. Therefore, it is necessary to transform the controller parameter tuning problem into an optimization problem of control performance according to the controller performance index, and then use an artificial intelligence optimization ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B11/42G05D1/08G06N3/00
CPCG05B11/42G05D1/0825G06N3/006Y02T10/40
Inventor 王佩魏宏夔施国强吕梅柏李旭邢超张岳
Owner NORTHWESTERN POLYTECHNICAL UNIV
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