An Identification Method With Direct Acquisition of Reduced Order Model From a Steplike Response

2004 ◽  
Vol 126 (4) ◽  
pp. 746-752 ◽  
Author(s):  
Manabu Kosaka ◽  
Hiroshi Uda ◽  
Hiroshi Shibata

In this paper, we propose a deterministic off-line identification method performed by using input and output data with a constant steady-state output response. The method can directly acquire any order of reduced model without knowing the real order of a plant, in such a way that the intermediate parameters are uniquely determined so as to be orthogonal with respect to 0-N-tuple integral values of output error and irrelevant to the unmodeled dynamics. From the intermediate parameters, the co-efficients of a rational transfer function are calculated. In consequence, the method can be executed for any linear single-input single-output plant without knowing or estimating its order at the beginning. The effectiveness of the method is illustrated by numerical simulations and also by applying it to a two-mass system.

Author(s):  
D. K. Sambariya ◽  
Omveer Sharma

In this paper the Routh Approximation method is explored for getting the reduced order model of a higher order model. The reduced order modeling of a large system is necessary to ease the analysis of the system. The approach is examined and compared to single-input single-output (SISO) and multi-input multi-output (MIMO) systems. The response comparison is considered in terms of step response parameters and graphical comparisons. It is reported that the reduced order model using proposed Routh Approximation (RA) method is almost similar in behavior to that of with original systems.


2005 ◽  
Vol 24 (2) ◽  
pp. 125-134
Author(s):  
Manabu Kosaka ◽  
Hiroshi Uda ◽  
Eiichi Bamba ◽  
Hiroshi Shibata

In this paper, we propose a deterministic off-line identification method performed by using input and output data with a constant steady state output response such as a step response that causes noise or vibration from a mechanical system at the moment when it is applied but they are attenuated asymptotically. The method can directly acquire any order of reduced model without knowing the real order of a plant, in such a way that the intermediate parameters are uniquely determined so as to be orthogonal with respect to 0 ∼ N-tuple integral values of output error and irrelevant to the unmodelled dynamics. From the intermediate parameters, the coefficients of a rational transfer function are calculated. In consequence, the method can be executed for any plant without knowing or estimating its order at the beginning. The effectiveness of the method is illustrated by numerical simulations and also by applying it to a 2-mass system.


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