Fuzzy sliding mode controller with RBF neural network for robotic manipulator trajectory tracking

Ak A. G., Cansever G.

INTELLIGENT CONTROL AND AUTOMATION, vol.344, pp.527-532, 2006 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 344
  • Publication Date: 2006
  • Journal Name: INTELLIGENT CONTROL AND AUTOMATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, zbMATH
  • Page Numbers: pp.527-532
  • Yıldız Technical University Affiliated: Yes

Abstract

This paper proposes a fuzzy sliding mode controller with radial basis function neural network (RBFNN) for trajectory tracking of robot manipulator. The main problem of sliding mode controllers is that a whole knowledge of the system dynamics and system parameters is required to compute the equivalent control. In this paper, a RBFNN is proposed to compute the equivalent control. Computer simulations of three link robot manipulator for trajectory tracking indicate that the proposed method is a good candidate for trajectory control applications.