Discrete-Time Noncausal Linear Periodically Time-Varying Scaling for Robustness Analysis and Controller Synthesis (original) (raw)
2013
Since modeling of real plants inevitably gives rise to modeling errors regarded as uncertainties, considering robustness for the uncertainties is important in actual control problems. For tackling issues of analyzing robust stability of closed-loop systems in a less conservative fashion, the μ-analysis method is known to be effective. As an alternative approach to robust stability analysis, on the other hand, discrete-time noncausal linear periodically time-varying (LPTV) scaling has been proposed recently. This approach can be naturally introduced through the lifting-based treatment of systems, and the associated conservativeness can be reduced by increasing the period of lifting. This thesis is concerned with this lifting-based scaling approach. In this thesis, we first review the definition and properties of noncausal LPTV scaling. This scaling approach is a generalization of the conventional causal linear time-invariant (LTI) scaling, and coincides with the latter scaling when w...
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