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Linear coercive elliptic PDE control problem and reduced objective
Definition
Let be a bounded Lipschitz domain, , and . Use the real integral pairing on . Equip with the standard full Sobolev inner product and norm Here is the closure of in the norm of Zero-boundary Sobolev space as a norm closure. Under Countable Choice, and are real Hilbert spaces; the local proof of completeness of is included in Well-posedness of elliptic control state and adjoint equations ↗. The inclusion is continuous with .
Let be bounded and measurable, with its real integral inner product, and let be the pointwise box of Closed pointwise box of L2 controls. Under Countable Choice, is a real Hilbert space by with the integral pairing is a Hilbert space. Let be bilinear, bounded with constant , and coercive with constant in the stated norm; symmetry is not assumed. Let be bounded and linear, and fix , , and .
For every , the state is required to satisfy
The reduced objective, defined on all of and minimized over , is
A spatially varying coefficient, boundary control, variational crimes, finite-element control discretization, and parabolic evolution are separate hypotheses or branches; none is implicit in this definition. The state well-definedness is supplied by Well-posedness of elliptic control state and adjoint equations ↗.
Depends on
- Bounded, coercive and symmetric sesquilinear forms
- A bounded linear operator between normed spaces
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
- The dual space X^* of a normed space and its dual norm
- Hilbert space
- The space $L^p(\mu)$ as the quotient by null functions
- $L^2$ with the integral pairing is a Hilbert space
- Closed pointwise box of L2 controls
- Zero-boundary Sobolev space as a norm closure
Used by
- Finite-budget active-set SQP with a certified KKT-system residual status Algorithm
- Finite-budget projected-gradient loop with state-adjoint residual certificates Algorithm
- The optimal elliptic control is the clipped negative adjoint Corollary
- A distributed heat source has an exact box-constrained optimum Example
- State and adjoint Strang bounds give a reduced-gradient error certificate Lemma
- A certified projected-gradient residual bounds distance to the control-mesh optimum Theorem
- Conditional O(h2) variational control error under H2 regularity and full uniform L2 estimates Theorem
- Existence, uniqueness, and variational inequality for elliptic PDE control Theorem
- Piecewise-constant control with shape-regular finite elements has O(h) error Theorem
- Reduced gradient and coercive Hessian for linear elliptic tracking control Theorem
- Well-posedness of elliptic control state and adjoint equations Theorem
Dependency tree · two levels
41 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Hannes Meinlschmidt, Optimization with Partial Differential Equations, FAU lecture notes (standard reference, not scraped)