Title :
Improved direct identification of linear systems in closed-loop operation
Author_Institution :
Sch. of Quantitative Methods & Math. Sci., Univ. of Western Sydney, Penrith South DC, NSW, Australia
Abstract :
An efficient method for direct closed-loop identification of linear systems was recently proposed. A crucial condition utilized in establishing this method is that the system pure time delay must be strictly greater than the order of the noise model. One eminent characteristic of the results presented in this paper is that the previous imposed condition is obliterated so that the method can be used for unbiased direct closed-loop identification of linear systems with arbitrary time delay (including without time delay). Moreover, an important relationship of the proposed method with the instrumental variable methods is founded, providing a good insight into the proposed method. The performance of the proposed method is also illustrated by simulation results in comparison with other identification methods.
Keywords :
autoregressive moving average processes; closed loop systems; delay systems; identification; linear systems; ARMAX model; closed-loop system; delay systems; direct closed-loop identification; linear systems; noise model; time delay; Adaptive control; Australia; Biological system modeling; Control systems; Delay effects; Economic forecasting; Linear systems; Open loop systems; Parameter estimation; Predictive models;
Conference_Titel :
Decision and Control, 2002, Proceedings of the 41st IEEE Conference on
Print_ISBN :
0-7803-7516-5
DOI :
10.1109/CDC.2002.1184504