Skip to main content

Implementation of Dynamic Matrix Control Algorithm Using a Microcontroller with Fixed-Point Arithmetic

  • Conference paper
  • First Online:
Challenges in Automation, Robotics and Measurement Techniques (ICA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 440))

Included in the following conference series:

Abstract

The aim of this paper is to describe software implementation of the Dynamic Matrix Control (DMC) algorithm using a microcontroller with fixed-point arithmetic. A 32-bit RISC ARM platform is used, which is cheap, but quite a powerful hardware system. To prevent register overflow and drastic loss of precision, a partial shifting of values technique is performed. The DMC algorithm with fixed-point arithmetic is applied to a laboratory thermal process and the obtained results are compared with those of the DMC algorithm implemented in floating-point arithmetic.

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

Access this chapter

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Bamimore, A., Taiwo, O., King, R.: Comparison of two nonlinear model predictive control methods and implementation on a laboratory three tank system. In: Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, pp. 5242–5247 (2011)

    Google Scholar 

  2. Jerez, J.L., Constantinides, G.A., Kerrigan, E.C.: Towards a fixed point QP solver for predictive control. In: Proceedings of the 51st IEEE Annual Conference on Decision and Control, pp. 675–680 (2012)

    Google Scholar 

  3. Kayacan, E., Ramon, H., Saeys, W.: Learning in centralized nonlinear model predictive control: application to an autonomous tractor-trailer system. IEEE Trans. Control Syst. Technol. 23(1), 197–205 (2015)

    Google Scholar 

  4. Lin, C.-Y., Liu, Y.-C.: Precision tracking control and constraint handling of mechatronic servo systems using model predictive control. IEEE/ASME Trans. Mechatron. 17(4), 593–605 (2012)

    Article  Google Scholar 

  5. Longo, S., Kerrigan, E.C., Constantinides, G.A.: A predictive control solver for low-precision data representation. In: Proceedings of the European Control Conference, pp. 3590–3595 (2013)

    Google Scholar 

  6. Ławryńczuk, M.: Computationally Efficient Model Predictive Control Algorithms: A Neural Network Approach. Stud. Syst. Decis. Control 3 (2014). Springer, Heidelberg

    Google Scholar 

  7. Patrinos, P., Guiggiani, A., Bemporad, A.: Fixed-point dual gradient projection for embedded model predictive control. In: Proceedings of the European Control Conference, pp. 3602–3607 (2013)

    Google Scholar 

  8. Shi, J., Jiang, Q., Cao, Z., Zhou, H., Yang, Y.: Design method of PID-type model predictive iterative learning control based on the two-dimensional generalized predictive control scheme. In: Proceedings of the 12th International Conference on Control Automation Robotics and Vision, pp. 452–457 (2012)

    Google Scholar 

  9. Tatjewski, P.: Advanced Control of Industrial Processes: Structures and Algorithms. Springer, London (2007)

    Google Scholar 

  10. Tousain, R.L., Bosgra, O.H.: Efficient dynamic optimization for nonlinear model predictive control-application to a high-density poly-ethylene grade change problem. In: Proceedings of the 39th IEEE Conference on Decision and Control, vol. 1, pp. 760–765 (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Patryk Chaber .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Chaber, P. (2016). Implementation of Dynamic Matrix Control Algorithm Using a Microcontroller with Fixed-Point Arithmetic. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Challenges in Automation, Robotics and Measurement Techniques. ICA 2016. Advances in Intelligent Systems and Computing, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-29357-8_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-29357-8_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29356-1

  • Online ISBN: 978-3-319-29357-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics