Research Article

Hybrid adaptive control for non-linear uncertain impulsive dynamical systems

  1. Wassim M. Haddad1,*,
  2. Tomohisa Hayakawa2,
  3. Sergey G. Nersesov1,
  4. VijaySekhar Chellaboina3

Article first published online: 6 DEC 2004

DOI: 10.1002/acs.848

Issue

International Journal of Adaptive Control and Signal Processing

International Journal of Adaptive Control and Signal Processing

Volume 19, Issue 6, pages 445–469, August 2005

Additional Information

How to Cite

Haddad, W. M., Hayakawa, T., Nersesov, S. G. and Chellaboina, V. (2005), Hybrid adaptive control for non-linear uncertain impulsive dynamical systems. International Journal of Adaptive Control and Signal Processing, 19: 445–469. doi: 10.1002/acs.848

Author Information

  1. 1

    School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0150, U.S.A.

  2. 2

    CREST, Japan Science and Technology Agency, Saitama, 332-0012, Japan

  3. 3

    Mechanical and Aerospace Engineering, The University of Tennessee, Knoxville, TN 37996-2210, U.S.A.

*School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0150, U.S.A

Publication History

  1. Issue published online: 18 JUL 2005
  2. Article first published online: 6 DEC 2004
  3. Manuscript Accepted:
  4. Manuscript Revised:
  5. Manuscript Received: 17 MAR 2003

Funded by

  • National Science Foundation. Grant Numbers: ECS-9496249, ECS-0133038
  • Air Force Office of Scientific Research. Grant Number: F49620-03-1-0178

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Keywords:

  • hybrid adaptive control;
  • non-linear hybrid systems;
  • impulsive dynamical systems;
  • system uncertainty;
  • stabilization;
  • attraction;
  • hybrid normal form

Abstract

A direct hybrid adaptive control framework for non-linear uncertain hybrid dynamical systems is developed. The proposed hybrid adaptive control framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop hybrid system; that is, asymptotic stability with respect to part of the closed-loop system states associated with the hybrid plant states. Furthermore, hybrid adaptive controllers guaranteeing attraction of the closed-loop system plant states are also developed. Finally, two numerical examples are provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach. Copyright © 2004 John Wiley & Sons, Ltd.

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