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

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 d...

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Bibliographic Details
Published in:International journal of control, automation, and systems 2020, Automation, and Systems, 18(8), , pp.1965-1974
Main Authors: Souza, Marina B. A., de Melo Honório, Leonardo, de Oliveira, Edimar José, Moreira, António Paulo G. M.
Format: Article
Language:English
Subjects:
Control
Cost analysis
Design parameters
Engineering
Excitation
Initial conditions
Lagrange multiplier
Mechatronics
Nonlinear systems
Numerical stability
Optimization
Parameter estimation
Recursive methods
Robotics
Signal generation
제어계측공학
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Summary: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. First, the limits over the parameters are tightly adjusted according to their confidence. A recursive approach runs the optimization methodology, analyzes the solution’s feasibility and marginal costs given by the Lagrange Multipliers, and selects a direction that could improve the system’s response. This approach improves the convergence and the assertiveness of the estimation process. To validate this approach, some cases, including a parameters estimation of a mobile robot nonlinear system, are tested.
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-019-0164-8