Journal
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume 66, Issue 11, Pages 5592-5598Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2021.3052751
Keywords
Estimation; Dynamic scheduling; Uncertainty; Linear systems; Symmetric matrices; Linear matrix inequalities; Measurement uncertainty; Dynamic multipliers; estimation; gain scheduling; linear matrix inequalities (LMIs); robust control
Funding
- Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy [EXC 2075 - 390740016]
- Stuttgart Center for Simulation Science (SimTech)
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A convex solution to the robust gain-scheduled estimation problem with integral quadratic constraints and dynamic D-scalings is provided in this work, closing an important gap in current methods. Novel synthesis criteria in terms of linear matrix inequalities are introduced for the design of nominal gain-scheduled estimators, which can be directly combined with existing results on robust estimation. The benefits of this design approach are illustrated through a numerical example.
We provide a convex solution to the robust gain-scheduled estimation problem based on integral quadratic constraints with dynamic D-scalings for both the uncertain and the scheduled component. This closes an important gap since, so far, merely static scalings could be used for the scheduled component in estimation problems. To this end, we provide novel synthesis criteria in terms of linear matrix inequalities for the design of nominal gain-scheduled estimators that allow for a direct combination with available results on robust estimation. We illustrate the benefit of our design approach by means of a numerical example.
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