Decentralized fuzzy control of multiple nonholonomic vehicles

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This work considers the problem of controlling multiple nonholonomic vehicles so that they converge to a scent source without colliding with each other. Since the control is to be implemented on simple 8-bit microcontrollers, fuzzy control rules are used to simplify a linear quadratic regulator control design. The inputs to the fuzzy controllers for each vehicle are the (noisy) direction to the source, the distance to the closest neighbor vehicle, and the direction to the closest vehicle. These directions are discretized into four values: Forward, Behind, Left, and Right, and the distance into three values: Near, Far, Gone. The values ... continued below

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10 p.

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Driessen, B.J.; Feddema, J.T. & Kwok, K.S. September 1, 1997.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM (United States)
    Place of Publication: Albuquerque, New Mexico

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Description

This work considers the problem of controlling multiple nonholonomic vehicles so that they converge to a scent source without colliding with each other. Since the control is to be implemented on simple 8-bit microcontrollers, fuzzy control rules are used to simplify a linear quadratic regulator control design. The inputs to the fuzzy controllers for each vehicle are the (noisy) direction to the source, the distance to the closest neighbor vehicle, and the direction to the closest vehicle. These directions are discretized into four values: Forward, Behind, Left, and Right, and the distance into three values: Near, Far, Gone. The values of the control at these discrete values are obtained based on the collision-avoidance repulsive forces and the change of variables that reduces the motion control problem of each nonholonomic vehicle to a nonsingular one with two degrees of freedom, instead of three. A fuzzy inference system is used to obtain control values for inputs between the small number of discrete input values. Simulation results are provided which demonstrate that the fuzzy control law performs well compared to the exact controller. In fact, the fuzzy controller demonstrates improved robustness to noise.

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10 p.

Notes

OSTI as DE98000242

Source

  • 1998 American controls conference, Philadelphia, PA (United States), 24-26 Jun 1998

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  • Other: DE98000242
  • Report No.: SAND--97-2352C
  • Report No.: CONF-980623--
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 654205
  • Archival Resource Key: ark:/67531/metadc710542

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  • September 1, 1997

Added to The UNT Digital Library

  • Sept. 12, 2015, 6:31 a.m.

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  • May 5, 2016, 6:24 p.m.

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Driessen, B.J.; Feddema, J.T. & Kwok, K.S. Decentralized fuzzy control of multiple nonholonomic vehicles, article, September 1, 1997; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc710542/: accessed June 24, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.