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Approaches to parameter identification for hybrid multilinear time invariant systems

Abstract:

Industrial buildings often have interacting continuous- and discrete-valued signals. Hybrid multilinear time invariant (MTI) models have been shown to be able to describe this hybrid dynamics appropriately for many cases. White box modelling methods from first principles have been used in this application domain before. The parameters of these models can be efficiently represented by higher order tensors. This paper introduces as alternatives black and grey box approaches for the parameter identification of MTI models from data. The methods are tested with the help of simulation data produced from a multilinear model of an industrial hall. It is assumed that all state variables are measured with additative noise and the input and disturbances are exactly measured, too. Two black box methods obtain either the full parameter tensor or a rank-r decomposition of it. Numerical examples using the industrial building model show the principle applicability of these approaches for real data.