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Bilinear System Identification by Minimal-Order State Observers

Vicario, Francesco; Phan, Minh Q.; Longman, Richard W.; Betti, Raimondo

Bilinear systems offer a promising approach for nonlinear control because a broad class of nonlinear problems can be reformulated and approximated in bilinear form. System identification is a technique to obtain such a bilinear approximation for a nonlinear system from input-output data. Recent discrete-time bilinear model identification methods rely on Input-Output-to-State Representations (IOSRs) derived via the interaction matrix technique. A new formulation of these methods is given by establishing a correspondence between interaction matrices and the gains of full-order bilinear state observers. The new interpretation of the identification methods highlights the possibility of utilizing minimal-order bilinear state observers to derive new IOSRs. The existence of such observers is discussed and shown to be guaranteed for special classes of bilinear systems. New bilinear system identification algorithms are developed and the corresponding computational advantages are illustrated via numerical examples.


Also Published In

Spaceflight Mechanics 2015: Proceedings of the 25th AAS/AIAA Space Flight Mechanics Meeting

More About This Work

Academic Units
Mechanical Engineering
Published Here
January 5, 2016


This work was presented at the 25th AAS/AIAA Space Flight Mechanics Meeting, Williamsburg, VA, January 2015. The paper (identified as paper AAS 15-341) was then published as part of the conference proceedings in the Advances in the Astronautical Sciences, Vol. 155, 2015, pp. 1175-1192 (published by Univelt).

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