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Unfalsified control based on the controller parameterisation

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  • R.S. Sánchez-Peña
  • P. Colmegna
  • F. Bianchi

Abstract

This paper presents an implementation of the unfalsified control (UC) method using the Riccati-based parameterisation of H∞${\mathcal {H}}_\infty$ controllers. The method provides an infinite controller set to (un)falsify the real-time data streams seeking for the best performance. Different sets may be designed to increase the degrees of freedom of the set of controller candidates to perform UC. In general, a set of m central controllers could be designed, each one seeking different objectives and all with their own parameterisation as a function of a stable and bounded transfer matrix. For example, one controller parameterisation could be designed to solve the robust stability of a model set which covers the physical system, therefore guaranteeing feasibility. The implementation requires the online optimisation of either quadratic fractional or quadratic problems, depending on the selection of the cost function. A multi-input, multi-output (MIMO) time-varying model of a permanent magnet synchronous generator illustrates the use of this technique.

Suggested Citation

  • R.S. Sánchez-Peña & P. Colmegna & F. Bianchi, 2015. "Unfalsified control based on the controller parameterisation," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(15), pages 2820-2831, November.
    • Handle: RePEc:taf:tsysxx:v:46:y:2015:i:15:p:2820-2831
    DOI: 10.1080/00207721.2013.879251
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    Cited by:

    1. Xiaofei Zhang & Hongbin Ma, 2019. "Data-Driven Model-Free Adaptive Control Based on Error Minimized Regularized Online Sequential Extreme Learning Machine," Energies, MDPI, vol. 12(17), pages 1-17, August.

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