New prospects in the adaptive control of robots under unmodeled environmental interactions

Jozsef K. Tar, Imre J. Rudas, Janos F. Bito, Bela Patkai

Research output: Contribution to conferencePaper

Abstract

A new method for a simultaneous tackling of the effects of incomplete and approximate robot models and that of the dynamic interaction with an unmodeled environment in robot control was recently outlined. The basic idea was to gain adaptivity via tuning the parameters of the Symplectic Group inherent in the Hamiltonian description of Classical Mechanical Systems. This description results in equations of uniform structure independent of the particular properties of the system to be controlled. Till now only the effects of tuning of only special parameters were investigated by simulation for a special 3 DOF robot arm. In this paper the behavior of a similar control with extended parameter space is considered in lite case of a vertical 3DOF SCARA robot. Simulation results are discussed for different nominal trajectories. The results reveal that this approach may open new prospects in the control of mechanical devices.

Original languageEnglish
Pages1349-1354
Number of pages6
Publication statusPublished - Dec 1 1997
EventProceedings of the 1997 23rd Annual International Conference on Industrial Electronics, Control, and Instrumentation, IECON. Part 2 (of 4) - New Orleans, LA, USA
Duration: Nov 9 1997Nov 14 1997

Other

OtherProceedings of the 1997 23rd Annual International Conference on Industrial Electronics, Control, and Instrumentation, IECON. Part 2 (of 4)
CityNew Orleans, LA, USA
Period11/9/9711/14/97

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Tar, J. K., Rudas, I. J., Bito, J. F., & Patkai, B. (1997). New prospects in the adaptive control of robots under unmodeled environmental interactions. 1349-1354. Paper presented at Proceedings of the 1997 23rd Annual International Conference on Industrial Electronics, Control, and Instrumentation, IECON. Part 2 (of 4), New Orleans, LA, USA, .