Fixed-wing unmanned aerial vehicle PID parameter control method based on ant colony algorithm

A technology of parameter control and ant colony algorithm, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problem of premature algorithm and achieve the effect of good robustness, fast response speed and high feasibility

Inactive Publication Date: 2017-06-23
GUANGZHOU BUREAU CSG EHV POWER TRANSMISSION
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Problems solved by technology

However, this search method often falls into a local optimum as the pheromone concentra

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  • Fixed-wing unmanned aerial vehicle PID parameter control method based on ant colony algorithm
  • Fixed-wing unmanned aerial vehicle PID parameter control method based on ant colony algorithm
  • Fixed-wing unmanned aerial vehicle PID parameter control method based on ant colony algorithm

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Embodiment Construction

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings and embodiments. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them.

[0019] Ant Colony Algorithm Basic Principles

[0020] The ant colony algorithm is derived from the fact that blinded ants should search the shortest path from the nest to food by leaving pheromone on the path without visual information elements, and the concentration of pheromone left on the path The size plays an important guiding role in the subsequent ants' search and tracking. After multiple round-trip iterations, the search for the shortest path from the nest to the food source is finally achieved. The search mechanism of ants is like the positive feedback mechanism in the control system, and it shows strong robustness to solve combinatorial optimization problems by using parallel distribu...

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Abstract

The invention discloses a fixed-wing unmanned aerial vehicle PID parameter control method based on an ant colony algorithm. The method comprises steps of setting ant colony search nodes, defining the value range of the PID controller parameters: the scale factor Kp, the integration time Ti and the derivative time Td by the empirical method, and setting the search nodes to an N* 3 search point matrix set of one parameter per line, where N is the number of random values within the range of values greater than 1; adding the pheromone evaporation mechanism to the ant colony optimization mechanism, and evaporating the pheromone on the optimal path of the ant colony search after each turn of iteration; and traversing the ant colony search nodes by using the ant colony optimization mechanism of pheromone evaporation to find the node satisfying the evaluation control performance index, wherein the evaluation control performance index is that the integral of the absolute error is the smallest. The method realizes the optimal PID parameter searching and setting of the fixed-wing unmanned aerial vehicle by using the improved ant colony algorithm, accelerates the searching process of the optimal solution, and is suitable for the multi-condition constrained type combinational optimization.

Description

technical field [0001] The invention relates to the field of unmanned aerial vehicle control, in particular to a method for controlling PID parameters of a fixed-wing unmanned aerial vehicle based on an ant colony algorithm. Background technique [0002] Unmanned Aerial Vehicle (UAV) has become the focus of research and development and use in all walks of life due to its small body, flexible movement, convenient operation and high performance-price ratio. The body can be equipped with sensors such as cameras, sonar, lasers, etc., so that the UAV can be well used in strategic environments such as regional reconnaissance and map mapping. [0003] The efficient detection and flexible actions of UAVs are necessarily related to the attitude control of UAVs. At present, the controllers used by most drones are mainly traditional PID (proportional-integral-derivative) control system parameters: proportional factor K p , integration time T i and differentiation time T d The optim...

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 郑武略尚涛张富春张蔓赵敏汲广李伟性金钊赵雪峰袁文俊林翔方博贺敏恒林明杰贾培亮廖江雨马智梁超刘延超
Owner GUANGZHOU BUREAU CSG EHV POWER TRANSMISSION
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