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Recursive Approach of Sub-Optimal Excitation Signal Generation and Optimal Parameter Estimation

Marina B. A. Souza, Leonardo de Melo Honório, Edimar José de Oliveira*, and António Paulo G. M. Moreira
International Journal of Control, Automation, and Systems, vol. 18, no. 8, pp.1965-1974, 2020

Abstract : Optimal Input Design (OID) methodologies are developed to find a signal that could best estimate a set of parameters of a given model. Their application in constrained nonlinear systems, especially when the search space limits or the initial conditions are unknown, may present several difficulties due to the numerical instability related to the optimization processes. A good choice over the parameters possible ranges is a trade-off among numerical stability, search space size, and effectiveness, and it is hardly found. To deal with this problem, this paper proposes a series of changes in the Sub-Optimal Excitation Signal Generation and Optimal Parameter Estimation (SOESGOPE) methodology.

Keyword : Nonlinear systems, optimal parameter design, parameter identification, recursive method.

 
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