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


Yidirim Ş.

SIMULATION MODELLING PRACTICE AND THEORY, vol.16, no.3, pp.368-378, 2008 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 16 Issue: 3
  • Publication Date: 2008
  • Doi Number: 10.1016/j.simpat.2007.12.002
  • Journal Name: SIMULATION MODELLING PRACTICE AND THEORY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.368-378
  • Keywords: four-legged robot, neural networks, PD controller, recurrent neural network
  • Erciyes University Affiliated: Yes

Abstract

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.