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Finite element pde constrained optimization — Examples
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Absolute Continuity and the Sharp Fundamental Theorem of Calculus
- Areas of Elementary Plane Figures
- Banach Valued Integration and the Radon Nikodym Property
- Binary Operations, Monoids, Groups and Subgroups
- Bounded Linear Operators and Quotient Spaces
- Bounded Variation and the Riemann–Stieltjes Integral
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Lp Spaces and Test-Function Conventions
- Complex Norms and Realification
- Complexification, Realification and Real Structures
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Density Separability and Convolution in Lᵖ
- Determinants of Matrices over a Commutative Ring
- Differentiation of Monotone Functions and the Vitali Covering Theorem
- Distributions Test Functions and Differentiation
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Dual Spaces Adjoint Operators and Annihilators
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Finite element pde constrained optimization
- Foundations of the Real Numbers for Analysis
- Fubini and Change of Variables
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Hilbert Space Geometry and Riesz Representation
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Lax--Milgram and Weak Elliptic Solutions
- Lebesgue Measure on Euclidean Space
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Mixed Partials, Taylor Formulae, and Extrema
- Modes of Convergence Egorov and Lusin
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Normed and Banach Spaces
- Norming and Separation under Hahn–Banach
- Order, Zorn's Lemma, and the Axiom of Choice
- Orthonormal Bases, Parseval and Fourier Series
- Outer Measure and the Caratheodory Extension Theorem
- Pointwise Extended-Real Function Products
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Product Measures and the Fubini Tonelli Theorems
- Properties of the Integral and the Working FTC
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Schwartz Space and the Plancherel Theorem
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Signed and Complex Measures Hahn and Jordan
- Simple Field Extensions and the Construction of the Complex Numbers
- Smooth Approximation and Sobolev Extension
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Analytic Hahn Banach Theorem
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Complex Exponential and Euler's Formula
- The Derivative and the Mean Value Theorems
- The Exponential Function
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Lᵖ Spaces Holder Minkowski and Riesz Fischer
- The Maximal Function and Lebesgue Differentiation
- The Radon Nikodym Theorem and Lebesgue Decomposition
- The Riemann Integral in Rᵐ and Jordan Content
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
- Weak Derivatives and Sobolev Spaces
2 · Summary
The distributed example constructs a smooth box-feasible heat source, state, and adjoint with an exact nonzero optimum. The boundary-control example derives the endpoint trace functional and explains why its control space and operator differ from an interior source. The bang-bang example minimizes a separate linear functional over an box; it does not obtain that result by substituting into a formula that divides by .
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
A distributed heat source has an exact box-constrained optimum
Statement
Assume Countable Choice. Let , , , and . Let be the load functional , set , , , and . Put and , which solve the state equation. Set and . Define . Then is the unique optimal control, and its adjoint is .
Facts & Assumptions
Given: The one-dimensional coercive elliptic control problem, the admissible box , and the exactly defined target .
The state and adjoint equations have unique weak solutions under the bounded coercive form hypotheses (Well-posedness of elliptic control state and adjoint equations).
For , an admissible satisfying for every is the unique minimizer (Existence, uniqueness, and variational inequality for elliptic PDE control).
Verification
The form is the full inner product, so it is bounded and coercive with constants one, and . Since , , and , integration by parts first for compactly supported smooth tests and then by density gives for every ; uniqueness in [F1] identifies the state. Since and has zero boundary values, the same argument verifies the adjoint equation.
The load identity gives for every , hence . Since , it is admissible, and . Thus its variational inequality holds with equality for every admissible comparison control, and [F2] makes the unique minimizer.
A boundary flux control uses the H1 trace and a different control operator
Statement
Assume the Axiom of Choice. For , realize by its unique absolutely continuous representatives, with norm . For a smooth state satisfying , , and , integration by parts gives the weak boundary load . The boundary control parameter is a scalar, equivalently for counting measure. For , its trace functional is not representable by an interior density ; for , both loads include the zero functional. Thus the boundary control space and its trace operator must be specified separately from the distributed-control space .
Facts & Assumptions
Given: The Axiom of Choice, the interval, the energy space , and the one-dimensional weak formulation of a Neumann boundary load.
The Axiom of Choice is assumed (The Axiom of Choice).
The control box Closed pointwise box of L2 controls consists of equivalence classes in an space over its declared measure domain; changing the domain changes the control space.
Under the Axiom of Choice, every class has a unique absolutely continuous representative on (One-dimensional functions have unique absolutely continuous representatives).
The Axiom of Choice implies Dependent Choice and Countable Choice (AC implies DC implies countable choice).
For absolutely continuous functions, integration by parts gives when Countable Choice and Dependent Choice hold (Integration by parts for absolutely continuous functions).
Cauchy--Schwarz gives (Cauchy–Schwarz: , with equality exactly for dependent pairs).
Verification
By [F2], has an absolutely continuous representative. By [F3], the hypotheses of [F4] hold. Applying [F4] to and gives . Cauchy--Schwarz [F5] yields . Applying [F4] to and for a smooth state gives . Thus the boundary control operator is bounded on .
Let . Then , , and . If and for every with some , Cauchy--Schwarz [F5] gives , a contradiction. For , represents the same zero functional. The boundary input space is nevertheless the scalar space, while the distributed input space in [F1] is ; their operators and control sets must be specified separately.
The alpha-zero linear box problem has a bang-bang active set
Statement
On with box , consider the separate unregularized linear functional , where . Its minimizer is for and for ; the value at the single switching point is immaterial in . This is a bang-bang control (it takes only endpoint values a.e.) and is not an instance of the strong-convexity theorem.
Facts & Assumptions
Given: The box, the linear objective, and Lebesgue measure on .
The feasible controls satisfy almost everywhere (Closed pointwise box of L2 controls).
A box projection clips pointwise, but the linear objective is a distinct problem and has no Tikhonov term (The L2 projection onto a pointwise box is clipping).
A nonnegative measurable function has integral zero exactly when it vanishes almost everywhere (A nonnegative measurable function has integral exactly when it vanishes almost everywhere).
Verification
If , then , so for every , with equality only when . If , then , so , with equality only when .
Integrating the pointwise inequalities gives . The gap is nonnegative almost everywhere and integrable; if equality holds, [F3] makes it zero almost everywhere. Since away from the single point , equality forces the stated endpoint values almost everywhere, so the minimizer is unique as an equivalence class. It is bang-bang by construction. Because , the strict-convexity and unique-control conclusions that use are not invoked.
The exact box projection formula from [F2] concerns clipping a point to the interval; this example instead minimizes a linear integrand and reaches the interval endpoints according to the sign of . Thus this is a separate limiting/example branch, not a consequence of substituting into a formula that divides by .