4.1 Article

Adaptive Output Feedback Control of Flexible-Joint Robots Using Neural Networks: Dynamic Surface Design Approach

Journal

IEEE TRANSACTIONS ON NEURAL NETWORKS
Volume 19, Issue 10, Pages 1712-1726

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2008.2001266

Keywords

Adaptive observer; dynamic surface control (DSC); flexible-joint electrically driven (FJED) robots; output feedback; robust control; self-recurrent wavelet neural network (SRWNN)

Funding

  1. Yonsei University Institute of TMS Information Technology
  2. Brain Korea 21 program
  3. MOCIE
  4. Yonsei University, Seoul, Korea
  5. Korea Institute of Industrial Technology(KITECH) [2007-8-0741] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances.

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