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Malgorzata Sumislawska Prof Keith J Burnham Coventry University

Parity equations-based unknown input reconstruction for Hammerstein-Wiener systems in errors-in-variables framework. Malgorzata Sumislawska Prof Keith J Burnham Coventry University. Motivation. Errors-in-variables (EIV) framework

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Malgorzata Sumislawska Prof Keith J Burnham Coventry University

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  1. Parity equations-based unknown input reconstruction for Hammerstein-Wiener systems in errors-in-variables framework MalgorzataSumislawska Prof Keith J Burnham Coventry University UKACC PhD Presentation Showcase

  2. Motivation • Errors-in-variables (EIV) framework • Input and output signalsare subjected to white, Gaussian, zero-mean, mutually uncorrelated measurement noise sequences • Long history of research on EIV framework in Control Theory and Applications Centre • Aim: reconstruct unknown input while minimising impact ----of measurement noise on unknown input estimate UKACC PhD Presentation Showcase

  3. Motivation • Hammerstein-Wiener (HW) system representation considered • Relatively simple model structure • Can approximate large class of nonlinear systems • Limited attention paid to HW systems in EIV framework N1(.) , N2(.) – static nonlinear functions UKACC PhD Presentation Showcase

  4. Problem solution • Knowing N1(.) and N2(.) calculate input and output to linear dynamic block • Input and output estimates to linear block affected by noise signals to be calculated UKACC PhD Presentation Showcase

  5. Problem solution • Knowing N1(.) and N2(.) calculate input and output to linear dynamic block • Input and output estimates to linear block affected by noise • Linear EIV setup with heteroscedastic noise, whose variance depends on operating point • Need for adaptive scheme UKACC PhD Presentation Showcase

  6. Problem solution • Influence of noise minimised using Lagrange multipliers optimisation method • Time-varying noise variances estimated from N1(.)and N2(.)using Taylor expansion • Experimental (Monte-Carlo simulation) results match theoretical calculations UKACC PhD Presentation Showcase

  7. Summary and future work • Summary • Novel approach for unknown input reconstruction developed • Effect of measurement noise minimised in adaptive manner • The work published in SumislawskaM., Larkowski, T., Burnham, K. J., ‘Unknown input reconstruction observer for Hammerstein-Wiener systems in the errors-in-variables', Proceedings of 16st IFAC Symposium on System Identification, Brussels, Belgium, 11-13 July 2012 • Future work • Coloured output noise • Multivariable case UKACC PhD Presentation Showcase

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