Journal of Intelligent and Robotic Systems

, Volume 42, Issue 1, pp 95–111 | Cite as

A Proposed Hybrid Recurrent Neural Control System for Two Co-operating Robots

  • Şahin Yildirim


This paper discusses a model refernce adaptive (MRAC) position/force controller using proposed neural networks for two co-operating planar robots. The proposed neural network is a recurrent hybrid network. The recurrent networks have feedback connections and thus an inherent memory for dynamics, which makes them suitable for representing dynamic systems. A feature of the networks adopted is their hybrid hidden layer, which includes both linear and nonlinear neurons. On the other hand, the results of the case of a single robot under position control alone are presented for comparison. The results presented show the superior ability of the proposed neural network based model reference adaptive control scheme at adapting to changes in the dynamics parameters of robots.


co-operating robots neural network hybrid control 


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Copyright information

© Kluwer Academic Publishers 2005

Authors and Affiliations

  1. 1.Engineering FacultyErciyes UniversityKayseriTurkey

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