Title :
System identification with binary-valued sensors
Author :
Le Yi Wang ; Zhang, Ji-Feng
Author_Institution :
Dept. of Electr. & Comput. Eng., Wayne State Univ., Detroit, MI, USA
Abstract :
The problem of system identification is investigated for plants which are equipped only with binary-valued sensors. Optimal identification errors, time complexity, optimal input design, and impact of disturbances and unmodelled dynamics on identification accuracy and complexity are explored. It is revealed that switching sensors impose fundamental limitations on identification accuracy and time complexity, and carry distinct features beyond identification with regular sensors. Furthermore, it is shown that the time complexity of such identification problems is intimately related to the Kolmogorov ε-entropy of parameter uncertainty sets
Keywords :
computational complexity; dynamics; parameter estimation; sensors; Kolmogorov ϵ-entropy; Optimal identification errors; binary-valued sensors; disturbances impact; identification accuracy; identification complexity; optimal input design; parameter uncertainty sets; switching sensors; system identification; time complexity; unmodelled dynamics impact; Application software; Automotive engineering; Costs; Gas detectors; Sensor phenomena and characterization; Sensor systems; Signal to noise ratio; System identification; Uncertain systems; Vehicle dynamics;
Conference_Titel :
American Control Conference, 2001. Proceedings of the 2001
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-6495-3
DOI :
10.1109/ACC.2001.945672