On-line identification of non-linear hysteretic structural systems using a variable trace approach

2001 ◽  
Vol 30 (9) ◽  
pp. 1279-1303 ◽  
Author(s):  
Jeng-Wen Lin ◽  
Raimondo Betti ◽  
Andrew W. Smyth ◽  
Richard W. Longman
Keyword(s):  
Structural Systems ◽  
Line Identification ◽  
Non Linear ◽  
On Line

On-Line Identification of Hysteretic Systems

1998 ◽  
Vol 65 (1) ◽  
pp. 194-203 ◽  
Author(s):  
A. G. Chassiakos ◽  
S. F. Masri ◽  
A. W. Smyth ◽  
T. K. Caughey
Keyword(s):  
Adaptive Estimation ◽  
Structural Systems ◽  
Simulation Studies ◽  
Restoring Force ◽  
Hysteretic Systems ◽  
Line Identification ◽  
Wide Range ◽  
On Line ◽  
Identification Approach ◽  
Hereditary Nature

Using adaptive estimation approaches, a method is presented for the on-line identification of hysteretic systems under arbitrary dynamic environments. The availability of such an identification approach is crucial for the on-line control and monitoring of nonlinear structural systems to be actively controlled. In spite of the challenges encountered in the identification of the hereditary nature of the restoring force of such nonlinear systems, it is shown through the use of simulation studies and experimental measurements that the proposed approach can yield reliable estimates of the hysteretic restoring force under a very wide range of excitation levels and response ranges.

Identification of Non-Linear Multi-Variable Systems Subjected to Random Input Signals

1974 ◽  
Vol 7 (6) ◽  
pp. 217-223 ◽  
Author(s):  
Donald Bell
Keyword(s):  
Correlation Method ◽  
Operating Point ◽  
System A ◽  
Line Identification ◽  
Input Signals ◽  
Non Linear ◽  
Coupling Dynamics ◽  
On Line ◽  
Process Operation ◽  
Made In

In the optimal control of any physical process about its operating point, a requirement of prime importance is the identification of the process parameters. This requires the realisation of both the static and dynamic characteristics of the control system. A method of identifying multi-variable non-linear systems is presented in this paper. The method uses correlation techniques around the tracked operating point of the system. The correlation method uses several uncorrelated maximal length (pseudo-random) sequences of small amplitude as test signals. This facilitates on-line identification during the normal process operation. A further advantage of this method is that a system identification may be made in the presence of noise and other inherent disturbances. The technique is first applied to a multi-variable system containing cubic non-linearities and then to one containing four hysteresis elements. Finally, an identification was made of the non-linear cross-coupling dynamics between the roll and yaw axes of an aircraft.

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