Copyright © 2012 Yu Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
An optimal input design method for parameter estimation in a discrete-time nonlinear system is presented in the paper to improve the observability and identification precision of model parameters. Determinant of the information matrix is used as the criterion function which is generally a nonconvex function about the input signals to be designed. To avoid the locally optimizing problem, a randomized design method is proposed by which a globally optimizing test plan other than input signals may be obtained. Then the randomized design can be approximated by a nonrandomized design about optimal inputs. An iterative algorithm integrated with dynamic programming is given and verified by a numerical example on experimental design for self-calibration tests of ISP system.