Tensor networks for MIMO LPV system identification

Bilal Gunes, Jan-Willem van Wingerden, Michel Verhaegen
2018 International Journal of Control  
In this paper, we present a novel multiple input multiple output (MIMO) linear parameter varying (LPV) state-space refinement system identification algorithm that uses tensor networks. Its novelty mainly lies in representing the LPV sub-Markov parameters, data and state-revealing matrix condensely and in exact manner using specific tensor networks. These representations circumvent the 'curse-of-dimensionality' as they inherit the properties of tensor trains. The proposed algorithm is
more » ... imensionality'-free in memory and computation and has conditioning guarantees. Its performance is illustrated using simulation cases and additionally compared with existing methods. ARTICLE HISTORY
doi:10.1080/00207179.2018.1501515 fatcat:jwqlbnodendlbepyzn37ficaoe