Model Predictive Control of Nonlinear MIMO Systems Based on Adaptive Orthogonal Polynomial Networks

Authors

  • Marko T. Milojkovic Faculty of Electronic Engineering, University of Nis, Serbia
  • Andjela D. Djordjevic Faculty of Electronic Engineering, University of Nis, Serbia
  • Stanisa Lj. Peric Faculty of Electronic Engineering, University of Nis, Serbia
  • Miroslav B. Milovanovic Faculty of Electronic Engineering, University of Nis, Serbia
  • Zoran H. Peric Faculty of Electronic Engineering, University of Nis, Serbia
  • Nikola B. Dankovic Faculty of Electronic Engineering, University of Nis, Serbia

DOI:

https://doi.org/10.5755/j02.eie.28780

Keywords:

Adaptive polynomial neural network, Generalized orthogonal functions, Model predictive control, Twin-rotor aero-dynamic system

Abstract

This paper considers a new design of model predictive control based on specific models in the form of adaptive orthogonal polynomial networks, built around a specially tailored basis of generalized orthogonal functions. Polynomial model has a single layer structure and a smaller number of model parameters than classical neural networks, usually used for model predictive control design, leading to lower complexity and shorter calculation time. Desired property of adaptability of the model is achieved by using additional variable factors inside the orthogonal basis. The designed controller was applied in control of twin-rotor aero-dynamic system as a representative of nonlinear multiple input-multiple output systems and compared to the other state-of-the-art control algorithms.

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Published

2021-04-29

How to Cite

Milojkovic, M. T., Djordjevic, A. D., Peric, S. L., Milovanovic, M. B., Peric, Z. H., & Dankovic, N. B. (2021). Model Predictive Control of Nonlinear MIMO Systems Based on Adaptive Orthogonal Polynomial Networks. Elektronika Ir Elektrotechnika, 27(2), 4-10. https://doi.org/10.5755/j02.eie.28780

Issue

Vol. 27 No. 2 (2021)

Section

AUTOMATION, ROBOTICS

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