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Adaptive fuzzy decentralized control of robot manipulators

Sadati, N ; Sharif University of Technology | 2005

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  1. Type of Document: Article
  2. DOI: 10.1109/ICIECA.2005.1644352
  3. Publisher: IEEE Computer Society , 2005
  4. Abstract:
  5. In this paper an adaptive fuzzy decentralized control algorithm for trajectory tracking of robot manipulators is developed. The proposed decentralized control algorithm allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), without having any prior knowledge of the robot manipulator dynamics. The interconnections in the dynamic equations of each subsystem are considered with unknown nonlinear bounds. The adaptive fuzzy neural networks (AFNNs) are proposed to model the unknown nonlinear dynamics of the robots and the interconnection terms. Using Lyapunov method, the stability of the overall system is investigated. © 2005 IEEE
  6. Keywords:
  7. Adaptive control systems ; Algorithms ; Lyapunov functions ; Manipulators ; Nonlinear systems ; Robot applications ; Adaptive fuzzy decentralized control ; Decentralized control algorithms ; Robot manipulators ; Trajectory tracking ; Fuzzy control
  8. Source: ICIECA 2005: International Conference on Industrial Electronics and Control Applications 2005, Quito, 29 November 2005 through 2 December 2005 ; Volume 2005 , 2005 ; 0780394194 (ISBN); 9780780394193 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/1644352