Intelligent setting method for attitude control parameters of carrier rocket

A technology of launch vehicle and attitude control, applied in electric controllers, controllers with specific characteristics, etc., can solve the problems of unsatisfactory search accuracy of global optimal results, low accuracy of global optimal results, and reduced convergence performance, etc. Achieve the effect of enhancing the global optimization ability, improving the probability of global optimization, and fast convergence speed

Pending Publication Date: 2021-09-03
NORTHWESTERN POLYTECHNICAL UNIV
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AI Technical Summary

Problems solved by technology

[0004] However, the standard salp algorithm still has some defects: although it can achieve large-scale and fast convergence in the early stage, the convergence efficiency in the later stage is not good; the search accuracy for the global optimal result under a fixed step size is not ideal
The above studies have improved the performance of the salp algorithm to a certain extent, but there are still problems such as decreased convergence performance in the later stage, low precision of global optimization results, and easy to fall into local optimum. From the perspective of improving control parameter tuning efficiency and optimal control effect, Substantial improvements to the salp algorithm are necessary for better parameter tuning results

Method used

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  • Intelligent setting method for attitude control parameters of carrier rocket
  • Intelligent setting method for attitude control parameters of carrier rocket
  • Intelligent setting method for attitude control parameters of carrier rocket

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Experimental program
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Embodiment 1

[0147] Using the test function to verify the solution accuracy and convergence of the quantum salp algorithm

[0148] In order to verify the improvement effect of the improved algorithm in terms of solution accuracy and convergence, the standard test function two-dimensional F1 function and Ackley function were selected to compare the effect of the algorithm before and after the improvement. Based on the two function calculation methods for the problem of the minimum value, the obtained The objective function is Y=f(X)=-g h (X)h=G, R,; the mathematical expressions and global optimal solutions of the two standard test functions are given in Table 1.

[0149] Assuming that there are N quantum salps in the quantum salp group, F=(X Q1 ,X Q2 ,...,X Qi ,...,X QN ), 1≤i≤N, the state X of each individual quantum salp 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 variab...

Embodiment 2

[0170] Feasibility verification of quantum salp algorithm launch vehicle attitude control parameter tuning

[0171] Refer to attached Figure 1-7 , the specific implementation steps of the inventive method are as follows:

[0172] Step 1. Establish the attitude motion model of the launch vehicle and obtain the nominal data:

[0173] 1. Rigid body motion modeling of launch vehicle

[0174] According to the analysis of the attitude motion of the launch vehicle and in view of the symmetrical characteristics of the launch vehicle, the motion model of the rocket pitch channel is established, which consists of three parts: rigid body motion, elastic motion and attitude measurement.

[0175] The equation of motion for a rigid body is:

[0176]

[0177]

[0178]

[0179] The elastic vibration equation is:

[0180]

[0181] The inertial measurement equation is:

[0182]

[0183]

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Abstract

The invention discloses an intelligent setting method for attitude control parameters of a carrier rocket. The method comprises the following steps: acquiring nonlinear controller parameters and an objective function of the attitude of the carrier rocket; adopting a quantum dogvessel algorithm, setting and optimizing nonlinear controller parameters by solving the maximum value of an objective function, and determining optimal nonlinear controller parameters, wherein the determination of the quantum dogvessel alveolar algorithm comprises the following steps: on the basis of the standard dogvessel alveolar algorithm, determining the state of the quantum dogvessel alveolar by adopting a quantum bit probability amplitude coding mode; and according to the sine and cosine position variables corresponding to the two positions in the parameter solution space, determining the target function value of the two position coordinates, and taking the maximum value as the target function value of the quantum dogvessel state. According to the method, the quantum theory is combined with the dogvessel alveolar algorithm, each quantum dogvessel alveolar state is equivalent to two positions occupied in an optimization parameter space, each dogvessel alveolar state corresponds to two solutions of an optimization problem, the ergodicity of the algorithm is improved, and the global convergence speed of the algorithm is increased.

Description

technical field [0001] The invention relates to the field of parameter tuning of nonlinear attitude controllers of launch vehicles, in particular to an intelligent tuning method for attitude control parameters of launch vehicles based on quantum salp algorithm. Background technique [0002] Although the nonlinear attitude controller of the launch vehicle can better solve the influence of gusts, parameter perturbations, unknown disturbances, etc. The introduction of nonlinear functions leads to problems such as multi-variable, nonlinear, and multi-extreme values ​​in the tuning of nonlinear controller parameters, and it is impossible to obtain an analytical tuning method similar to that of PID controller parameters. Therefore, it is necessary to transform the controller parameter tuning problem into an optimization design problem with control performance as the objective function and controller parameters as the design variable. For the problems caused by the introduction of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B11/42
CPCG05B11/42
Inventor 高华宇王佩张科吕梅柏邢超周大明
Owner NORTHWESTERN POLYTECHNICAL UNIV
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