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Cuckoo-behavior-RNA-GA-based bridge crane neural network modeling method

A neural network modeling and neural network model technology, applied in the field of bridge crane neural network modeling, can solve problems such as poor local search ability and premature convergence.

Active Publication Date: 2016-09-28
ZHEJIANG UNIV
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Problems solved by technology

However, the traditional genetic algorithm also has the disadvantages of poor local search ability and easy premature convergence.

Method used

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  • Cuckoo-behavior-RNA-GA-based bridge crane neural network modeling method

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Embodiment Construction

[0063] The present invention will be further elaborated and illustrated below in conjunction with the accompanying drawings and specific embodiments. The technical features of the various implementations in the present invention can be combined accordingly on the premise that there is no conflict with each other.

[0064] In the application of a cuckoo behavior RNA-GA to the neural network modeling of bridge cranes, the specific implementation steps are as follows:

[0065] Step 1: Pass a 3D bridge crane experimental platform [2] (simplified to a two-dimensional bridge crane system in the x direction and in an open-loop state, see Ma Bojun, Fang Yongchun, Wang Pengcheng, Yuan Yinghai, Three-dimensional bridge crane automatic control experiment system, Control Engineering, 18(2):239 -243, 2011) to obtain the input and output sampling data of the horizontal direction control of the two-dimensional bridge crane system, where the input sampling data is the control force F x , th...

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Abstract

The invention, which belongs to the intelligent modeling field, discloses a cuckoo-behavior-RNA-GA-based bridge crane neural network modeling method. The bridge crane is a complicated under-actuated non-linear system; and effective control realization is based on establishment of a high-precision bridge crane model. With the Cuckoo-behavior RNA genetic algorithm, optimizing is carried out on a radial basis function center of a bridge crane neural network model, thereby obtaining a corresponding RBF neural network model. According to the method, an ideal effect is realized during testing. And the method is suitable for modeling of other complicated non-linear systems.

Description

technical field [0001] The invention relates to a bridge crane neural network modeling method of cuckoo behavior RNA-GA. Background technique [0002] Bridge crane is a representative large-scale engineering handling equipment, which is widely used in industrial production, ports, warehouses and other cargo transportation places. In order to achieve the purpose of quickly and accurately transporting the load, on the one hand, the trolley of the overhead crane is required to reach the target quickly and accurately, and on the other hand, it is required to be able to effectively restrain the load from swinging. Since the overhead crane is an underactuated nonlinear system, it is prone to swing during the load transportation process, which affects the positioning accuracy of the load, reduces work efficiency, and may collide with people and objects around the load. In order to realize the effective control of the overhead crane, it is necessary to establish a high-precision ov...

Claims

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Application Information

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IPC IPC(8): G06N3/08
CPCG06N3/086
Inventor 陈怡萍王宁郝利帆
Owner ZHEJIANG UNIV
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