Journal
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
Volume 19, Issue 18, Pages 1976-1992Publisher
WILEY
DOI: 10.1002/rnc.1390
Keywords
networked control systems (NCSs); limited feedback information; randomly missing outputs; adaptive control; Kalman filter
Funding
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Canadian Foundation of Innovation (CFI)
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This paper investigates the problem of adaptive control for networked control systems with unknown model parameters and randomly missing outputs. In particular, for a system with the autoregressive model with exogenous input placed in a network environment, the randomly missing output feature is modeled as a Bernoulli process. Then, an output estimator is designed to online estimate the missing output measurements, and further a Kalman filter-based method is proposed for parameter estimation. Based on the estimated output and the available output, and the estimated model parameters, an adaptive control is designed to make the output track the desired signal. Convergence properties of the proposed algorithms are analyzed in detail. Simulation examples illustrate the effectiveness of the proposed method. Copyright (C) 2008 John Wiley & Sons, Ltd.
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