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Design of a proposed neural network control system for trajectory controlling of walking robots

机译:提出的步行机器人轨迹控制神经网络控制系统设计

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The use of a proposed recurrent hybrid neural network to control of walking robot with four legs is investigated in this paper. A neural networks based control system is utilized to the control of four-legged walking robot. The control system consists of four proposed neural controllers, four standard PD controllers and four-legged planar walking robot. The proposed neural network (NN) is employed as an inverse controller of the robot. The NN has three layers, which are input, hybrid hidden and output layers. In addition to feedforward connections from the input layer to the hidden layer and from the hidden layer to the output layer, there is also feedback connection from the output layer to the hidden layer and from the hidden layer to itself. The reason to use hybrid layer is that robot's dynamics consists of linear and non-linear parts. The results show that the proposed neural control system has superior performance to control trajectory of walking robot with payload. (C) 2007 Elsevier B.V. All rights reserved.
机译:本文研究了一种提出的递归混合神经网络在四腿步行机器人控制中的应用。基于神经网络的控制系统被用来控制四足步行机器人。该控制系统由四个拟议的神经控制器,四个标准PD控制器和四足平面行走机器人组成。所提出的神经网络(NN)被用作机器人的逆控制器。 NN具有三层,分别是输入层,混合隐藏层和输出层。除了从输入层到隐藏层以及从隐藏层到输出层的前馈连接之外,还存在从输出层到隐藏层以及从隐藏层到自身的反馈连接。使用混合层的原因是机器人的动力学由线性和非线性部分组成。结果表明,所提出的神经控制系统在控制具有有效载荷的步行机器人的轨迹方面具有优越的性能。 (C)2007 Elsevier B.V.保留所有权利。

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