Hierarchical Robust Analysis for Identified Systems in Network
For control engineers dealing with large-scale networked systems, this provides a hierarchical approach to robustness analysis that balances computational complexity and conservatism.
This work adapts hierarchical robustness analysis to networks of locally controlled uncertain systems with ellipsoidal parameter uncertainties from identification, addressing the trade-off between computation time and conservatism for large-scale systems.
This technical report considers worst-case robustness analysis of a network of locally controlled uncertain systems with uncertain parameter vectors belonging to the ellipsoid sets found by identification procedures. In order to deal with computational complexity of large-scale systems, an hierarchical robustness analysis approach is adapted to these uncertain parameter vectors thus addressing the trade-off between the computation time and the conservatism of the obtained result.