Abstract
The problem of robust estimation for uncertain dynamical systems with a linear fractional dependence on uncertainties is considered. It is assumed that some of the parametric uncertainties affecting the system are available online and the estimator is scheduled on these parameters. The integral quadratic constraint (IQC) framework is considered for handling the uncertainties. Full-block static multipliers are used for capturing the properties of the measured parameters in the system while no structural or dynamic restrictions are placed on the multipliers used for the nonmeasured uncertainties. Sufficient existence conditions for constructing such robustly stabilizing, partially gain-scheduled estimators with guaranteed \({\mathcal{L}}_{2}\)-gain bounds are given in terms of finite dimensional linear matrix inequalities. A numerical example illustrates the advantages of gain-scheduling in robust estimation whenever possible.
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Acknowledgments
The authors would like to thank the German Research Foundation (DFG) for financial support of the project within the Cluster of Excellence in Simulation Technology (EXC 310/1) at the University of Stuttgart.
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Veenman, J., Scherer, C.W., Köse, I.E. (2012). Robust Estimation with Partial Gain-Scheduling Through Convex Optimization. In: Mohammadpour, J., Scherer, C. (eds) Control of Linear Parameter Varying Systems with Applications. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-1833-7_10
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DOI: https://doi.org/10.1007/978-1-4614-1833-7_10
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