Efficient solution of nonlinear model predictive control by a restricted enumeration method

Authors

  • Jhon Alexander Isaza Hurtado Instituto Tecnológico Metropolitano de Medellín
  • Diego A Muñoz Universidad Pontificia Bolivariana
  • Hernán Álvarez Universidad Nacional de Colombia

DOI:

https://doi.org/10.29019/enfoqueute.v9n4.393

Keywords:

restricted enumeration method, nonlinear program (NLP), nonlinear model predictive control (NMPC), pH control

Abstract

This work presents an alternative method to solve the nonlinear program (NLP) for nonlinear model predictive control (NMPC) problems. The NLP is the most computational demanding task in NMPC, which limits the industrial implementation of this control strategy. Therefore, it is important to consider algorithms that can solve the nonlinear program, not only in real time but also guaranteeing feasibility. In this work, the restricted enumeration method is proposed as alternative to solve the NLP for NMPC problems, showing successful results for pH control in a sugar cane process plant. This method enumerates in restricted way a set of final control element possible positions around the current one. Next, it tests all positions in that set to find the best one, taken as the optimization solution.

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References

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Published

2018-12-21

How to Cite

Isaza Hurtado, J. A., Muñoz, D. A., & Álvarez, H. (2018). Efficient solution of nonlinear model predictive control by a restricted enumeration method. Enfoque UTE, 9(4), pp. 13 – 23. https://doi.org/10.29019/enfoqueute.v9n4.393

Issue

Vol. 9 No. 4 (2018)

Section

Automation and Control, Mechatronics, Electromechanics, Automotive

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