Skip to main content
SpringerLink
Log in

Mathematical model with sensor and actuator for a transelevator

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

In this paper, the structural, sensor, and actuator mathematical models of a transelevator are presented; after, the mathematical model with sensor and actuator of the transelevator is obtained by using the combination of the above mentioned mathematical models. The proposed mathematical model is validated comparing the simulation results against the experimental results. Finally, the stability analysis of the aforementioned model is studied.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Bachrach J, Beal J, McLurkin J (2010) Composable continuous-space programs for robotic swarms. Neural Comput Appl 19:825–847

    Article  Google Scholar 

  2. Celikkanat H, Sahin E (2010) Steering self-organized robot flocks through externally guided individuals. Neural Comput Appl 19:849–865

    Article  Google Scholar 

  3. Chaoui H, Sicard P (2011) Adaptive Lyapunov-based neural network sensorless control of permanent magnet synchronous machines. Neural Comput Appl 20:717–727

    Article  Google Scholar 

  4. Chen C, Inoue Y, Shibata K (2011) Identification of a golf swing robot using soft computing approach. Neural Comput Appl 20:729–740

    Article  Google Scholar 

  5. Chiu C-H (2010) Self-tuning output recurrent cerebellar model articulation controller for a wheeled inverted pendulum control. Neural Comput Appl 19:1153–1164

    Article  MathSciNet  Google Scholar 

  6. Christensen DJ, Campbell J, Stoy K (2010) Anatomy-based organization of morphology and control in self-reconfigurable modular robots. Neural Comput Appl 19:787–805

    Article  Google Scholar 

  7. Lee W-P, Yang T-H (2011) Combining GRN modeling and demonstration-based programming for robot control. Neural Comput Appl 20:909–921

    Article  MathSciNet  Google Scholar 

  8. Leite D, Ballini R, Costa P, Gomide F (2012) Evolving fuzzy granular modeling from nonstationary fuzzy data streams. Evolv Syst 3(2):65–79

    Article  Google Scholar 

  9. Lemos A, Caminhas W, Gomide F (2011) Fuzzy evolving linear regression trees. Evolv Syst 2(1):1–14

    Article  Google Scholar 

  10. Lewis FL, Dawson DM, Abdallah CT (2004) Control of robot manipulators. Theory Pract. ISBN: 0-8247-4072-6

  11. Lughofer E, Bouchot JL (2011) On-line elimination of local redundancies in evolving fuzzy systems. Evolv Syst 2(3):165–187

    Article  Google Scholar 

  12. Pérez-Cruz JH, Alanis AY, Rubio JJ, Pacheco J (2012) System identification using multilayer differential neural networks: a new result. J Appl Math 2012:1–20

    Article  Google Scholar 

  13. Pérez-Cruz JH, Ruiz-Velázquez E, Rubio JJ, de Alba-Padilla CA (2012) Robust adaptive neurocontrol of SISO nonlinear systems preceded by unknow deadzone. Math Probl Eng 2012:1–23

    Article  Google Scholar 

  14. Rubio JJ, García E, Pacheco J (2011) Trajectory planning and collisions detector for robotic arms. Neural Comput App, online

  15. Rubio JJ, Torres C, Rivera R, Hernández CA (2011) Comparison of four mathematical models for braking of a motorcycle. IEEE Latin Am Trans 9(5):630–637

    Article  Google Scholar 

  16. Rubio JJ, Ortiz F, Mariaca CR, Tovar JC (2011) A method for online pattern recognition for abnormal eye movements. Neural Comput Appl. doi: 10.1007/s00521-011-0784-2

  17. Rubio JJ, Salazar M, Gomez AD, Lugo R (2012) Modeling of the relative humidity via functional networks and control of the temperature via classic controllers for a bird incubator. Neural Comput Appl 21(7):1491–1500

    Article  Google Scholar 

  18. Spong MW, Hutchinson S, Vidyasagar M (2006) Robot modeling and control. Wiley, London. ISBN-13: 978-0-471-64990-8

  19. Villaverde I, Graña M (2011) Neuro-evolutionary mobile robot egomotion estimation with a 3D ToF camera. Neural Comput Appl 20:345–354

    Article  Google Scholar 

  20. Wu Y, Sun F, Zheng J, Song Q (2010) A robust training algorithm of discrete-time MIMO RNN and application in fault tolerant control of robotic system. Neural Comput Appl 19:1013–1027

    Article  Google Scholar 

Download references

Acknowledgments

The authors are grateful to the editors and the reviewers for their valuable comments and insightful suggestions, which helped to improve this research significantly. The authors thank the Secretaría de Investigación y Posgrado and the Comisión de Operación y Fomento de Actividades Académicas del IPN and the Consejo Nacional de Ciencia y Tecnología for their help in this research. The third author would like to thank the financial support through a postdoctoral fellowship from Mexican National Council for Science and Technology (CONACYT).

Author information

Authors and Affiliations

  1. Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional, Av. de las Granjas no. 682, 02250, Col. Santa Catarina, México D.F., México

    José de Jesús Rubio, Jaime Pacheco & Francisco Torres

  2. Centro Universitario de Ciencias Exactas e Ingenierías, Universidad de Guadalajara, Boulevard Marcelino García Barragán No. 1421, 44430, Guadalajara, JAL, México

    J. Humberto Pérez-Cruz

Authors
  1. José de Jesús Rubio
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jaime Pacheco
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. Humberto Pérez-Cruz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Francisco Torres
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to José de Jesús Rubio.

Rights and permissions

Reprints and permissions

About this article

Cite this article

de Jesús Rubio, J., Pacheco, J., Pérez-Cruz, J.H. et al. Mathematical model with sensor and actuator for a transelevator. Neural Comput & Applic 24, 277–285 (2014). https://doi.org/10.1007/s00521-012-1224-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-012-1224-7

Keywords

Search

Navigation