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Particle Swarm Optimization Based Sliding Mode Control Design: Application to a Quadrotor Vehicle

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Applications of Sliding Mode Control in Science and Engineering

Part of the book series: Studies in Computational Intelligence ((SCI,volume 709))

Abstract

In this chapter, a design method for determining the optimal sliding mode controller parameters for a quadrotor dynamic model using the Particle Swarm Optimization algorithm is presented. In particular, due to the effort to determine optimal or near optimal sliding mode parameters, which depend on the nature of the considered dynamic model, a population based solution is proposed to tune the parameters. The proposed population based-method tunes the controller parameters (boundary layers and gains) according to a fitness function that measures the controller performances. A comparison of the designed sliding mode control with two popular controllers (PID and Backstepping) applied to a quadrotor dynamic model is proposed. In particular sliding mode control shows better performances in terms of steady state and transient response, as confirmed by performance indexes IAE, ISE, ITAE and ITSE.

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Notes

  1. 1.

    For the sake of clarity, we note that \(h'\) is time dependent due to \(\ddot{x}_{1d}\), so it is actually \(h'(\varvec{x},t)\). Therefore in the following steps, we assert relations \(\forall \> t\).

  2. 2.

    The remaining two couples of equations are used in the outer loop, which permits to calculate the reference angles required to track a desired position.

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Author information

Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Via Brecce Bianche, 60131, Ancona, Italy

    Alessandro Baldini, Lucio Ciabattoni, Riccardo Felicetti, Francesco Ferracuti & Andrea Monteriù

  2. Università degli studi eCampus, Via Isimbardi 10, Novedrate (CO), Italy

    Alessandro Freddi

  3. Research and Development Centre, Vel Tech University, Avadi, Chennai, 600062, Tamil Nadu, India

    Sundarapandian Vaidyanathan

Authors
  1. Alessandro Baldini
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  2. Lucio Ciabattoni
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  3. Riccardo Felicetti
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  4. Francesco Ferracuti
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  5. Alessandro Freddi
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  6. Andrea Monteriù
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  7. Sundarapandian Vaidyanathan
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Corresponding author

Correspondence to Lucio Ciabattoni .

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Editors and Affiliations

  1. Research and Development Centre, Vel Tech University, Chennai, Tamil Nadu, India

    Sundarapandian Vaidyanathan

  2. Maritime College and Department of Marine Engineering, National Kaohsiung Marine University, Kaohsiung, Taiwan

    Chang-Hua Lien

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Baldini, A. et al. (2017). Particle Swarm Optimization Based Sliding Mode Control Design: Application to a Quadrotor Vehicle. In: Vaidyanathan, S., Lien, CH. (eds) Applications of Sliding Mode Control in Science and Engineering. Studies in Computational Intelligence, vol 709. Springer, Cham. https://doi.org/10.1007/978-3-319-55598-0_7

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  • DOI: https://doi.org/10.1007/978-3-319-55598-0_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55597-3

  • Online ISBN: 978-3-319-55598-0

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