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On regularized feedback update of distributed-parameter systems in control and nonlinear estimation applications

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1 Author(s)
D. Gorinevsky ; Honeywell-Meas., North Vancouver, BC, Canada

This paper considers control of discretized linear distributed-parameter no-memory systems. It demonstrates that there is a need to regularize the optimality criterion in a feedback update design. It is shown that robustness of the update to a modelling error is proportional to the square root of the regularization parameter. Three applied control problems are discussed: 1) cross-directional control of the web manufacturing process; 2) iterative learning control of a batch process or repetitive motion; and 3) estimation of a nonlinear function of a single argument by using a radial basis function network

Published in:

American Control Conference, 1997. Proceedings of the 1997  (Volume:3 )

Date of Conference:

4-6 Jun 1997