Finite-time extended state observer and fractional-order sliding mode controller for impulsive hybrid port-Hamiltonian systems with input delay and actuators saturation: Application to ball-juggler robots

Authors

Yousef Farid, Fabio Ruggiero

Abstract

This paper addresses the robust control problem of mechanical systems with hybrid dynamics in port-Hamiltonian form. It is assumed that only the position states are measurable, and time-delay and saturation constraint affect the control signal. An extended state observer is designed after a coordinate transformation. The effect of the time delay in the control signal is neutralized by applying Padé approximant and augmenting the system states. An assistant system with faster convergence is developed to handle actuators saturation. Fractional-order sliding mode controller acts as a centralized controller and compensates for the undesired effects of unknown external disturbance and parameter uncertainties using the observer estimation results. Stability analysis shows that the closed-loop system states, such as the observer tracking error, and the position/velocity tracking errors, are finite-time stable. Simulation studies on a two ball-playing juggler robot with three degrees of freedom validate the theoretical results’ effectiveness.

Keywords

Impulsive hybrid systems; Port-Hamiltonian dynamics; Extended state observer; Fractional sliding surface; Finite-time control; Input delay

Citation

• Journal: Mechanism and Machine Theory
• Year: 2022
• Volume: 167
• Issue:
• Pages: 104577
• Publisher: Elsevier BV
• DOI: 10.1016/j.mechmachtheory.2021.104577

BibTeX

@article{Farid_2022,
  title={{Finite-time extended state observer and fractional-order sliding mode controller for impulsive hybrid port-Hamiltonian systems with input delay and actuators saturation: Application to ball-juggler robots}},
  volume={167},
  ISSN={0094-114X},
  DOI={10.1016/j.mechmachtheory.2021.104577},
  journal={Mechanism and Machine Theory},
  publisher={Elsevier BV},
  author={Farid, Yousef and Ruggiero, Fabio},
  year={2022},
  pages={104577}
}

Download the bib file

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