Robust multi-objective feedback design with linear guaranteed-cost bounds
P Dorato, L Menini, CA Treml - Automatica, 1998 - Elsevier
This paper considers the problem of designing a state-feedback control law which
“minimizes” multiple quadratic performance objectives in the presence of uncertain linear
plant dynamics. Vector optimization techniques are used to minimize upper-bounds on each
performance objective (guaranteed-cost). By exploiting the linear uncertainty bound
introduced by Bernstein (1987), the vector optimization problem is scalarized and Pareto
optimal solutions are computed. The theory is applied to a numerical example with two …
“minimizes” multiple quadratic performance objectives in the presence of uncertain linear
plant dynamics. Vector optimization techniques are used to minimize upper-bounds on each
performance objective (guaranteed-cost). By exploiting the linear uncertainty bound
introduced by Bernstein (1987), the vector optimization problem is scalarized and Pareto
optimal solutions are computed. The theory is applied to a numerical example with two …
Robust Multi-Objective Feedback Design with Linear Guaranteed-Cost Bounds.
P Dorato, L Menini, CA Treml - IFAC Proceedings Volumes, 1996 - Elsevier
This paper considers the problem of designing a state-feedback control law which"
minimizes" multiple quadratic performance objectives in the presence of uncertain linear
plant dynamics. Vector optimization techniques are used to minimize upper-bounds on each
performance objective (guaranteed-cost). By exploiting the linear uncertainty bound
introduced by (Bernstein, 1987), the vector optimization problem is scalarized and Pareto
optimal solutions are computed. The theory is applied to a numerical example with two …
minimizes" multiple quadratic performance objectives in the presence of uncertain linear
plant dynamics. Vector optimization techniques are used to minimize upper-bounds on each
performance objective (guaranteed-cost). By exploiting the linear uncertainty bound
introduced by (Bernstein, 1987), the vector optimization problem is scalarized and Pareto
optimal solutions are computed. The theory is applied to a numerical example with two …
Showing the best results for this search. See all results