A new adaptive neural network based observer for robotic manipulators

Asl R. M., Hashemzadeh F., Badamchizadeh M. A.

3rd RSI/ISM International Conference on Robotics and Mechatronics, ICROM 2015, Tehran, Iran, 7 - 09 October 2015, pp.663-668 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icrom.2015.7367862
  • City: Tehran
  • Country: Iran
  • Page Numbers: pp.663-668
  • Keywords: Lyapunov stability, Neural Network, neuro-observer, robot manipulator, state observer
  • Istanbul Technical University Affiliated: No


In this paper, a new neural network based observer is proposed for a class of nonlinear systems. The proposed observer can applied to estimate nonlinear systems with a high nonlinearity without any prior knowledge about system. This features help the proposed neuro-observer for real implementation and to use it in practice. The Lyapunov's direct method employed to show the stability and estimating performance of the proposed scheme. Simulation results on a two DOF robot manipulator are presented to show the efficiency of the proposed neural network based observer.