Identification of MIMO systems with partially decoupled parameters

Physical models for multivariable systems generally exhibit a partial decoupling with respect to the parameters characterizing the system. The computational advantages of such decoupling are explored using a recently developed least squares-equation error technique which applies to a class of nonlinear differential systems with input-output data given over a fixed finite-time interval. It is shown how the partially decoupled parameterized differential operator equations can be used as a basis for formulating a finite sequence of lower dimensional function minimizations in lieu of a single high-dimensional parameter minimization problem. Simulation results are summarized for a helicopter example which illustrate the advantages of carrying out the finite sequence of lower dimensional function minimizations.