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Robust-tracking control for robot manipulator with deadzone and friction using backstepping and RFNN controller

Robust-tracking control for robot manipulator with deadzone and friction using backstepping and RFNN controller

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  • Author(s): S.H. Park 1  and  S.I. Han 2
    • View affiliations
    • Affiliations: 1: Department of Mechatronics Engineering, Dongseo University, Busan, Republic of Korea
      2: School of Electrical Engineering, Pusan National University, Busan, Republic of Korea
  • Source: Volume 5, Issue 12, 18 August 2011, p. 1397 – 1417
    DOI:  10.1049/iet-cta.2010.0460 , Print ISSN 1751-8644, Online ISSN 1751-8652
© The Institution of Engineering and Technology
Published

This study deals with a robust non-smooth non-linearity compensation scheme for the direct-drive robot manipulator with an asymmetric deadzone, dynamic friction in joints and between the environmental contact space and end-effector and uncertainty. A model-free recurrent fuzzy neural network (RFNN) control system to approximate the ideal backstepping control law is designed to replace the traditional model-based adaptive controller, which requires information on the robots dynamics in advance. The simple dead-zone estimator and friction compensator based on the elasto-plastic friction model are developed in order to estimate unknown dead-zone width and friction parameters. The Lyapunov stability analysis yields the adaptive laws of the RFNN controller as well as the estimators of a dead-zone width and an elasto-plastic friction parameter. The validity of the proposed control scheme is confirmed from simulated results for free and constrained direct-drive robots with a deadzone in joint actuator, dynamic friction in joints and contact surfaces of the end-effector and uncertainty.

Inspec keywords: neurocontrollers; control nonlinearities; compensation; end effectors; recurrent neural nets; robust control; Lyapunov methods

Other keywords: direct-drive robot manipulator; dynamic friction; model-free recurrent fuzzy neural network control system; RFNN controller; robust nonsmooth nonlinearity compensation scheme; Lyapunov stability analysis; end-effector; friction compensator; elasto-plastic friction model; robust-tracking control; dead-zone estimator; asymmetric deadzone; backstepping control law

Subjects: Manipulators; Stability in control theory; Nonlinear control systems; Neurocontrol

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