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GP-based motion control design for the double-integrator system subject to velocity constraint

Published: 15 July 2017 Publication History

Abstract

The motion control problem for the double-integrator system subject to velocity constraint is addressed. A novel methodology, which consists of a two-stage process and regards a trade-off between natural and learned behaviors to develop a family of analytic controllers, is proposed. To this end, firstly, a natural behavior is designed to achieve asymptotic tracking of a desired continuous trajectory by using a Control-Theory approach. Secondly, learned behaviors are discovered by using a Genetic Programming approach to synthesize an analytic controller to ensure a bounded velocity of the system. The integration of these approaches allows the system to exhibit a good tracking performance while keeping the velocity bounded to a desired value, freely set by the user. Simulation results are provided to illustrate the effectiveness of the proposal, and a comparison with a traditional Control-Theory-Based solution is also given and discussed.

References

[1]
S. Ding and W.X. Zheng. 2015. Robust control of multiple integrators subject to input saturation and disturbance. Internat. J. Control 88, 4 (2015), 844--856.
[2]
D. Gu and H. Hu. 2008. Using Fuzzy Logic to Design Separation Function in Flocking Algorithms. IEEE Transactions on Fuzzy Systems 16, 4 (Aug 2008), 826--838.
[3]
C. Knoll and K. Röbenack. 2011. Control of an underactuated manipulator using similarities to the double integrator. IFAC Proceedings Volumes 44, 1 (2011), 11501--11507.
[4]
H.B. Oza, Y.V. Orlov, and S.K. Spurgeon. 2014. Finite time stabilization of a perturbed double integrator with unilateral constraints. Mathematics and Computers in Simulation 95 (2014), 200--212. Discontinuous Differential Systems: Theory and Numerical Methods.
[5]
E. Serpelloni, M. Maggiore, and C. Damaren. 2016. Bang-bang hybrid stabilization of perturbed double-integrators. Automatica 69 (2016), 315--323.

Cited By

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  • (2022)Evolved Extended Kalman Filter for first-order dynamical systems with unknown measurements noise covarianceApplied Soft Computing10.1016/j.asoc.2021.108174115:COnline publication date: 1-Jan-2022
  • (2020)Family of controllers based on sector non‐linear functions: an application for first‐order dynamical systemsIET Control Theory & Applications10.1049/iet-cta.2019.068014:10(1387-1392)Online publication date: 18-May-2020

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cover image ACM Conferences
GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion
July 2017
1934 pages
ISBN:9781450349390
DOI:10.1145/3067695
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 July 2017

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Author Tags

  1. bounded velocity
  2. double-integrator system
  3. genetic programming
  4. motion control design

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Cited By

View all
  • (2022)Evolved Extended Kalman Filter for first-order dynamical systems with unknown measurements noise covarianceApplied Soft Computing10.1016/j.asoc.2021.108174115:COnline publication date: 1-Jan-2022
  • (2020)Family of controllers based on sector non‐linear functions: an application for first‐order dynamical systemsIET Control Theory & Applications10.1049/iet-cta.2019.068014:10(1387-1392)Online publication date: 18-May-2020

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