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Adaptive ball rod system particle swarm optimization method based on priori knowledge

A particle swarm optimization, prior knowledge technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., to achieve the effect of suitable transition process, enhanced global search ability, and strong comprehensive adaptability

Active Publication Date: 2021-06-18
HOHAI UNIV
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Problems solved by technology

[0007] The object of the present invention is to provide a kind of particle swarm optimization method of self-adaptive cue system based on prior knowledge, to solve the relevant technical problems in the prior art

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  • Adaptive ball rod system particle swarm optimization method based on priori knowledge
  • Adaptive ball rod system particle swarm optimization method based on priori knowledge
  • Adaptive ball rod system particle swarm optimization method based on priori knowledge

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Embodiment Construction

[0048] Some improvements and modifications are made to the present invention below in conjunction with the accompanying drawings, and these improvements and modifications should also be regarded as the protection scope of the present invention. .

[0049] A particle swarm optimization method for adaptive club system based on prior knowledge, by improving the nonlinear inertia weight, using the adaptive change strategy including the variation factor and the fitness function combining prior knowledge and traditional performance integral, the particle The swarm algorithm is improved, and the improved particle swarm optimization algorithm is used for the proportional integral differential controller of the cue system to find the equilibrium position to make the cue system stable. The specific steps are as follows:

[0050] Step 1: Design a proportional speed compensator to control the internal motor control loop that has little influence on the control effect of the club system ac...

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Abstract

The invention provides an adaptive ball rod system particle swarm optimization method based on priori knowledge, which improves a particle swarm algorithm by improving a nonlinear inertia weight, using an adaptive change strategy containing a variation factor and combining priori knowledge and a fitness function of a traditional performance integral, and then an improved particle swarm optimization algorithm is used for controlling a proportional integral differential controller of the ball arm system, so that a balance position is found, and the ball arm system is stable. The invention provides a priori knowledge-based adaptive ball arm system particle swarm optimization method, which adopts the idea of fusing priori knowledge into an improved particle swarm optimization method, makes full use of the result of each iteration of the algorithm, and improves the ability of the ball arm system to deal with interference and the operation efficiency of the algorithm.

Description

technical field [0001] The invention relates to a particle swarm optimization method for an adaptive cue system based on prior knowledge, belonging to the field of swarm intelligence optimization control. Background technique [0002] The cue system consists of a metal ball and a track for it to roll freely. It has the characteristics of nonlinearity, open-loop instability, and underactuation. The movement of the ball on the guide rail is very complicated, and the control is difficult and extremely challenging. [0003] In order to solve the difficulty of controlling the cue system, more and more engineers and technicians have focused on researching the best cue system control method in recent years, and proposed various cue system control schemes to achieve better and faster balance. cue system. [0004] Chinese Patent No.: CN109782595A, discloses a network predictive control method based on an event-triggered mechanism for cue systems. According to the reconstructed syste...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 姜云逸李璟钰何超威
Owner HOHAI UNIV
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