Title :
Identification of multi-input multi-output systems by observability range space extraction
Author_Institution :
MIT Space Eng. Res. Center, Cambridge, MA, USA
Abstract :
The observability range space extraction system identification technique, a time-domain technique for state-space model identification of linear multi-input multi-output systems, is discussed. It extracts the base vectors of the observability range space of a linear system from a semipositive definite data matrix and obtains a state-space model from these vectors. Input excitation conditions which are required by this technique to obtain a transfer function equivalent model are discussed. Identification errors due to measurement noises are analyzed, and the conditions for transfer-function equivalent identification in the presence of measurement noises are derived. Simulation results show that this technique is able to produce relatively accurate models in a colored noise environment and under low signal-to-noise-ratio conditions
Keywords :
identification; multivariable systems; observability; state-space methods; time-domain analysis; transfer functions; MIMO systems identification; colored noise environment; input excitation conditions; low S/NR; low signal-to-noise-ratio conditions; measurement noises; multi-input multi-output systems; observability range space; observability range space extraction; semipositive definite data matrix; state-space model identification; time-domain technique; transfer function equivalent model; Colored noise; Data mining; Linear systems; Noise measurement; Observability; System identification; Time domain analysis; Transfer functions; Vectors; Working environment noise;
Conference_Titel :
Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-0872-7
DOI :
10.1109/CDC.1992.371593