2019 18th European Control Conference (ECC) 2019
DOI: 10.23919/ecc.2019.8795669
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Safe approximations of chance constrained sets by probabilistic scaling

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Cited by 12 publications
(20 citation statements)
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“…Remark 2 motivates the approach presented in the next section, which builds upon the results presented in Alamo et al (2019). We show how the probabilistic scaling approach directly leads to approximations of user-chosen complexity, which can be directly used in applications instead of creating the need for a post-processing step to reduce the complexity of the sampled set.…”
Section: Sample-based Techniquesmentioning
confidence: 78%
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“…Remark 2 motivates the approach presented in the next section, which builds upon the results presented in Alamo et al (2019). We show how the probabilistic scaling approach directly leads to approximations of user-chosen complexity, which can be directly used in applications instead of creating the need for a post-processing step to reduce the complexity of the sampled set.…”
Section: Sample-based Techniquesmentioning
confidence: 78%
“…The probabilistic scaling approach was presented in the conference papers (Alamo, Mirasierra, Dabbene, & Lorenzen, 2019;Mammarella, Alamo, Dabbene, & Lorenzen, 2020) and it is based on recent results on order statistics (Alamo, Manzano, & Camacho, 2018). The present work extends Alamo et al (2019), Mammarella et al (2020) in several directions. First, we perform here a thorough mathematical analysis of probabilistic scaling.…”
Section: Introductionmentioning
confidence: 89%
“…Proposition 1: Let n ≥ m, K ∈ N and δ K ∈ ∆ K be any given K-multisample with associated pairs of matrices {(A(δ (j) ), B(δ (j) )) j∈K }. Given any C-polytope S ⊆ X , the set L δ K in ( 10) is nonempty only if, for all (i, j) ∈ V × K, there exists an invertible submatrix G Q∪P ∈ R m×m of G(δ (j) ), with row indices as in Lemma 2, and subvector l Q∪P of l(δ (j) ), satisfying the conditions in (12).…”
Section: B On the Nonemptiness Of L δ Kmentioning
confidence: 99%
“…Then, G I = col(H Q , F B P ) and l I = col(1 |Q| , 1 |P| −(F A(δ)v) P ), for any v ∈ vert(S). Finally, the conditions in (12) follow by splitting inequalities (G) k G −1 I l I ≤ l k , ∀k ∈ A \ I, between the two sets Q and P, and noting that (G) k = (H) k and l k = 1 for any k ∈ {1, . .…”
Section: Appendixmentioning
confidence: 99%
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