In:
International Journal of Bifurcation and Chaos, World Scientific Pub Co Pte Ltd, Vol. 11, No. 04 ( 2001-04), p. 1079-1113
Abstract:
This paper presents a new state-space self-tuning control scheme for adaptive digital control of continuous-time multivariable nonlinear stochastic and chaotic systems, which have unknown system parameters, system and measurement noises, and inaccessible system states. Instead of using the moving average (MA)-based noise model commonly used for adaptive digital control of linear discrete-time stochastic systems in the literature, an adjustable auto-regressive moving average (ARMA)-based noise model with estimated states is constructed for state-space self-tuning control of nonlinear continuous-time stochastic systems. By taking advantage of a digital redesign methodology, which converts a predesigned high-gain analog tracker/observer into a practically implementable low-gain digital tracker/observer, and by taking the non-negligible computation time delay and a relatively longer sampling period into consideration, a digitally redesigned predictive tracker/observer has been newly developed in this paper for adaptive chaotic orbit tracking. The proposed method enables the development of a digitally implementable advanced control algorithm for nonlinear stochastic and chaotic hybrid systems.
Type of Medium:
Online Resource
ISSN:
0218-1274
,
1793-6551
DOI:
10.1142/S0218127401002559
Language:
English
Publisher:
World Scientific Pub Co Pte Ltd
Publication Date:
2001
SSG:
11
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