TY - JOUR
T1 - Experimental application of a method for hidden parameter tracking in a slowly changing, chaotic system
AU - Cusumano, J. P.
AU - Chelidze, D.
AU - Chatterjee, A.
PY - 1997/12/1
Y1 - 1997/12/1
N2 - Results are presented of an experimental application of a method for tracking hidden parameters in slowly changing chaotic systems. The method exploits the time scale separation between fast dynamic variables and a slow drifting parameter. Locally linear tracking models are constructed using data from the reference system sampled on a fast time scale, employing delay coordinate embedding. These reference models are used to track parameter drift. The method is successfully applied to a forced oscillator with a two-well potential. The effect of the choice of prediction time interval is studied. It is also observed that a simple correction for estimated modeling error gives a more sensitive tracking metric. For purposes of comparison with such model-based tracking methods, a heuristic method is also presented for detecting parameter changes using the autocorrelation function of the recorded time series. The relative merits of heuristic versus model-based techniques are discussed. Directions for future work are suggested.
AB - Results are presented of an experimental application of a method for tracking hidden parameters in slowly changing chaotic systems. The method exploits the time scale separation between fast dynamic variables and a slow drifting parameter. Locally linear tracking models are constructed using data from the reference system sampled on a fast time scale, employing delay coordinate embedding. These reference models are used to track parameter drift. The method is successfully applied to a forced oscillator with a two-well potential. The effect of the choice of prediction time interval is studied. It is also observed that a simple correction for estimated modeling error gives a more sensitive tracking metric. For purposes of comparison with such model-based tracking methods, a heuristic method is also presented for detecting parameter changes using the autocorrelation function of the recorded time series. The relative merits of heuristic versus model-based techniques are discussed. Directions for future work are suggested.
UR - http://www.scopus.com/inward/record.url?scp=0031374891&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0031374891&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:0031374891
VL - 7
SP - 45
EP - 54
JO - American Society of Mechanical Engineers, Tribology Division, TRIB
JF - American Society of Mechanical Engineers, Tribology Division, TRIB
ER -