Two-Legged Robot System Identification With Artificial Neural Networks

Author(s):  
Bahadir Catalbas ◽  
Burak Catalbas ◽  
Omer Morgul
2011 ◽  
pp. 941-955
Author(s):  
Masanori Goka ◽  
Kazuhiro Ohkura

Artificial evolution has been considered as a promising approach for coordinating the controller of an autonomous mobile robot. However, it is not yet established whether artificial evolution is also effective in generating collective behaviour in a multi-robot system (MRS). In this study, two types of evolving artificial neural networks are utilized in an MRS. The first is the evolving continuous time recurrent neural network, which is used in the most conventional method, and the second is the topology and weight evolving artificial neural networks, which is used in the noble method. Several computer simulations are conducted in order to examine how the artificial evolution can be used to coordinate the collective behaviour in an MRS.


Author(s):  
Masanori Goka ◽  
Kazuhiro Ohkura

Artificial evolution has been considered as a promising approach for coordinating the controller of an autonomous mobile robot. However, it is not yet established whether artificial evolution is also effective in generating collective behaviour in a multi-robot system (MRS). In this study, two types of evolving artificial neural networks are utilized in an MRS. The first is the evolving continuous time recurrent neural network, which is used in the most conventional method, and the second is the topology and weight evolving artificial neural networks, which is used in the noble method. Several computer simulations are conducted in order to examine how the artificial evolution can be used to coordinate the collective behaviour in an MRS.


2010 ◽  
Vol 171-172 ◽  
pp. 654-658
Author(s):  
De Kun Yue ◽  
Qi Wang

Uncertainty for the building structure and nonlinear, this simulation of a multi-storey structure under earthquake is presented based on the BP neural network and system identification, controller will be built to effectively reduce the structural response, and to strengthen the unique damper performance.


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