Lemma 2.1, p.4 — is -Lipschitz
ProvedMonoInclCLC.lemma_2_1closed-loop-controlcontinuous-time-optimizationmonotone-inclusionp2o-gran-per-chapterp2o-plan-paperp2o-v1
Let be a real Hilbert space and a maximal monotone operator with . For an integer let for , and . Then, for all and all ,
This is the Lipschitz estimate in the state variable that later controls the feedback law along a trajectory.
Differences from the source:
- encoding: the resolvent (I + λA)⁻¹ as an operator determined by A → a family J with IsResolvent l A (J l) for every l > 0; reason: for maximal monotone A such a map exists (Minty) and is unique (monotonicity), so no instance changes
Preamble
import Mathlib import Definitions.Def_ThreeOpSplitting_Convergence_MonotoneOperators import Definitions.Def_MonoInclCLC_phi open InnerProductSpace ThreeOpSplitting.Convergence
Formal statement
namespace MonoInclCLC
/-- **Lemma 2.1** (Lin, Jordan, *Monotone Inclusions, Acceleration and Closed-Loop Control*, arXiv:2111.08093v4, Lemma 2.1, p.4): for `p ≥ 2`,
`|ϕ(λ, x₁) - ϕ(λ, x₂)| ≤ λ^(1/(p-1)) ‖x₁ - x₂‖` for all `x₁, x₂` and all `λ > 0`.
**Formalization Note.** `J l` is the resolvent `(I + l A)⁻¹` for `l > 0`. The standing assumptions of p.3 (`A` maximal monotone, `A⁻¹(0) ≠ ∅`) are hypotheses. -/
theorem lemma_2_1 {H : Type*} [NormedAddCommGroup H] [InnerProductSpace ℝ H] [CompleteSpace H]
(A : H → Set H) (hA : IsMaximalMonotone A) (hzer : (zer A).Nonempty)
(J : ℝ → H → H) (hJ : ∀ l : ℝ, 0 < l → IsResolvent l A (J l))
(p : ℕ) (hp : 2 ≤ p)
(x₁ x₂ : H) (l : ℝ) (hl : 0 < l) :
|phi J p l x₁ - phi J p l x₂| ≤ l ^ (1 / ((p : ℝ) - 1)) * ‖x₁ - x₂‖ := by sorry
end MonoInclCLC
Source
Lin, Jordan, Monotone Inclusions, Acceleration and Closed-Loop Control, arXiv:2111.08093v4, Lemma 2.1, p.4
Human review
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.