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Journal of Intelligent and Robotic Systems

, Volume 18, Issue 1, pp 47–66 | Cite as

Integrated PID-type Learning and Fuzzy Control for Flexible-joint Manipulators

  • Lih-Chang Lin
  • Tzong-En Lee
Article

Abstract

The increased complexity of the dynamics of robots considering joint elasticity makes conventional model-based control strategies complex and difficult to synthesize. In this paper, a model-free control using integrated PID-type learning and fuzzy control for flexible-joint manipulators is proposed. Optimal PID gains can be learned by a neural network learning algorithm and then a simple standard fuzzy control could be incorporated in the overall control strategy, if needed, for enhancing the system responses. A modified recursive least squares algorithm is suggested for faster learning of the connection weights representing the PID-like gains. Simulation results show that the suggested simple model-free approach can control a complex flexible-joint manipulator to meet stringent requirements for both transient and steady-state performances.

flexible-joint robot model-free control PID-type learning fuzzy control 

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Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Lih-Chang Lin
    • 1
  • Tzong-En Lee
    • 1
  1. 1.Department of Mechanical EngineeringNational Chung Hsing University, TaichungTaiwan R.O.C

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