Chaotic neural network applied to two-dimensional motion control |
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Authors: | Hiroyuki Yoshida Shuhei Kurata Yongtao Li Shigetoshi Nara |
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Institution: | (1) Department of Electrical & Electronic Engineering, Faculty of Engineering, Okayama University, Okayama 700-8530, Japan;(2) Graduate School of Natural Science and Technology, Okayama University, 3-1-1 Tsushima-naka, Okayama 700-8530, Japan; |
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Abstract: | Chaotic dynamics generated in a chaotic neural network model are applied to 2-dimensional (2-D) motion control. The change
of position of a moving object in each control time step is determined by a motion function which is calculated from the firing
activity of the chaotic neural network. Prototype attractors which correspond to simple motions of the object toward four
directions in 2-D space are embedded in the neural network model by designing synaptic connection strengths. Chaotic dynamics
introduced by changing system parameters sample intermediate points in the high-dimensional state space between the embedded
attractors, resulting in motion in various directions. By means of adaptive switching of the system parameters between a chaotic
regime and an attractor regime, the object is able to reach a target in a 2-D maze. In computer experiments, the success rate
of this method over many trials not only shows better performance than that of stochastic random pattern generators but also
shows that chaotic dynamics can be useful for realizing robust, adaptive and complex control function with simple rules. |
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Keywords: | Constrained chaos Chaotic neural network Motion control 2-Dimensional maze Ill-posed problem |
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