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Adaptive Observer for Nonlinearly Parameterised Hammerstein System with Sensor Delay - Applied to Ship Emissions Reduction

Nielsen, Kræn Vodder; Blanke, Mogens; Eriksson, Lars
Journal article, Peer reviewed
Accepted version
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2016_OxygenObserver_kvn_mb_le.pdf (1.214Mb)
URI
http://hdl.handle.net/11250/2453202
Date
2017
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  • Institutt for teknisk kybernetikk [2245]
  • Publikasjoner fra CRIStin - NTNU [20888]
Original version
10.1109/TCST.2017.2715004
Abstract
Taking offspring in a problem of ship emission reduction by exhaust gas recirculation control for large diesel engines, an underlying generic estimation challenge is formulated as a problem of joint state and parameter estimation for a class of multiple-input single-output Hammerstein systems with first order dynamics, sensor delay and a bounded time-varying parameter in the nonlinear part. The paper suggests a novel scheme for this estimation problem that guarantees exponential convergence to an interval that depends on the sensitivity of the system. The system is allowed to be nonlinear parameterized and time dependent, which are characteristics of the industrial problem we study. The approach requires the input nonlinearity to be a sector nonlinearity in the time-varying parameter. Salient features of the approach include simplicity of design and implementation. The efficacy of the adaptive observer is shown on simulated cases, on tests with a large diesel engine on test bed and on tests with a container vessel.
Publisher
IEEE
Journal
IEEE Transactions on Control Systems Technology

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