Title :
On regularized feedback update of distributed-parameter systems in control and nonlinear estimation applications
Author :
Gorinevsky, Dimitry
Author_Institution :
Honeywell-Meas., North Vancouver, BC, Canada
Abstract :
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
Keywords :
discrete time systems; distributed parameter systems; feedback; feedforward neural nets; function approximation; linear systems; memoryless systems; parameter estimation; process control; stability; batch process; cross-directional control; discrete time systems; distributed-parameter systems; feedback update; iterative learning control; linear systems; memoryless systems; nonlinear function estimation; optimality criterion; radial basis function network; robustness; web manufacturing process; Control systems; Coordinate measuring machines; Feedback; Manufacturing processes; Motion control; Nonlinear control systems; Robustness; Shape control; Time measurement; Vectors;
Conference_Titel :
American Control Conference, 1997. Proceedings of the 1997
Print_ISBN :
0-7803-3832-4
DOI :
10.1109/ACC.1997.610900
