Skip to main content

Design Formulation for a Multi-criteria Optimization of Mechatronic Systems

  • Conference paper
  • First Online:
Advances in Italian Mechanism Science (IFToMM ITALY 2020)

Abstract

This paper introduces a Mechatronic Concurrent Design procedure to address multidisciplinary fields in Mechatronics. This approach takes into account multiple criteria and design variables from mainly mechanical aspects, control issues, and task-oriented features to formulate an optimization problem, which is solved using heuristic algorithms. An example is discussed to show the feasibility and characteristics of the procedure.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Brossog, M., et al.: Reducing the energy consumption of industrial robots in manufacturing systems. Int. J. Adv. Manuf. Technol. 78(5–8), 1315–1328 (2015)

    Google Scholar 

  2. Kayacan, E., Chowdhary, G.: Tracking error learning control for precise mobile robot path tracking in outdoor environment. J. Intell. Robot. Syst. 95, 975–986 (2019)

    Article  Google Scholar 

  3. Loughlin, C., Albu-Schäffer, A., Haddadin, S., Ott, C., Stemmer, A., Wimböck, T., Hirzinger, G.: The DLR lightweight robot: design and control concepts for robots in human environments. Ind. Robot Int. J. 34(5), 376–385 (2007)

    Article  Google Scholar 

  4. Inoue, K., Ogata, K., Kato, T.: An efficient induction motor drive method with a regenerative power storage system driven by an optimal torque. In: 2008 IEEE Power Electronics Specialists Conference, Rhodes, pp. 359–364 (2008)

    Google Scholar 

  5. Zhang, W.J., Li, Q., Guo, L.S.: Integrated design of mechanical structure and control algorithm for a programmable four-bar linkage. IEEE/ASME Trans. Mechatron. 4(4), 354–362 (1999)

    Article  Google Scholar 

  6. Russo, M., Herrero, S., Altuzarra, O., Ceccarelli, M.: Kinematic analysis and multiobjective optimization of a 3-UPR parallel mechanism for a robotic leg. Mech. Mach. Theory 120, 192–202 (2018)

    Article  Google Scholar 

  7. Fahmy, S.A.: Optimal design and scheduling of cellular manufacturing systems: an experimental study. In: 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC) Budapest, pp. 4532–4537 (2016)

    Google Scholar 

  8. Ceccarelli, M., Paglia, R., Lanni, C.: Analysis and optimization of a robotized workcell in fiat plant. In: 9th International Workshop on Robotics in Alpe-Adria Danube Region RAAD2000, Maribor, pp. 361–366 (2000)

    Google Scholar 

  9. Minchala-Avila, L.I., Garza-Castañón, L.E., Vargas-Martínez, A., Zhang, Y.: A review of optimal control techniques applied to the energy management and control of microgrids. Procedia Comput. Sci. 52, 780–787 (2015)

    Article  Google Scholar 

  10. Palli, G., Melchiorri, C.: Robust control of robots with variable joint stiffness. In: 2009 International Conference on Advanced Robotics, Munich, pp. 1–6 (2009)

    Google Scholar 

  11. Zheng, C., Bricogne, M., Le Duigou, J., Eynard, B.: Survey on mechatronic engineering: a focus on design methods and product models. Adv. Eng. Inform. 28(3), 241–257 (2014)

    Article  Google Scholar 

  12. Portilla-Flores, E.A., Mezura-Montes, E., Alvarez-Gallegos, J., Coello-Coello, C.A., Cruz-Villar, C.A.: Integration of structure and control using an evolutionary approach: an application to the optimal concurrent design of a CVT. Int. J. Numer. Meth. Eng. 71(8), 883–901 (2007)

    Article  Google Scholar 

  13. Yang, X.-S.: Nature-Inspired Algorithms and Applied Optimization. Springer, Cham (2018)

    Book  Google Scholar 

  14. Deb, K.: Multi-objective optimization. In: Burke, E.K., Kendall, G. (eds.) Search Methodologies. Springer, Cham (2005)

    Google Scholar 

Download references

Acknowledgments

The first author acknowledge Consejo Nacional de Ciencia y Tecnología and Instituto Politécnico Nacional for supporting his period of study at LARM2 of Rome Tor Vergata University in the A.Y. 2019–20 within a double Ph.D. degree program.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Cuauhtemoc Morales-Cruz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Morales-Cruz, C., Ceccarelli, M., Portilla-Flores, E.A. (2021). Design Formulation for a Multi-criteria Optimization of Mechatronic Systems. In: Niola, V., Gasparetto, A. (eds) Advances in Italian Mechanism Science. IFToMM ITALY 2020. Mechanisms and Machine Science, vol 91. Springer, Cham. https://doi.org/10.1007/978-3-030-55807-9_94

Download citation

Publish with us

Policies and ethics