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Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems Angela Kunoth University of Cologne, Germany November 09, 2016 Angela Kunoth Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 1 Adaptive


  1. Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems Angela Kunoth University of Cologne, Germany November 09, 2016 Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 1

  2. Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems Angela Kunoth University of Cologne, Germany November 09, 2016 Main subjects: ◮ Control problem constrained by PDE ❀ system of coupled PDEs ◮ Variables: state, control, adjoint (or co-)state ◮ Efficient solution schemes based on adaptive wavelets ◮ Convergence and optimal complexity Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 1

  3. Optimization Problems: First Order Necessary Conditions Constrained minimization problem inf J ( y , u ) J : Y × U → R Y , U , Q Hilbert spaces ( y , u ) ∈Y×U K : Y × U → Q ′ subject to K ( y , u ) = 0 control u ∈ U , state y ∈ Y Assumption on K : for given u ∈ U , there exists unique state y ∈ Y Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 2

  4. Optimization Problems: First Order Necessary Conditions Constrained minimization problem inf J ( y , u ) J : Y × U → R Y , U , Q Hilbert spaces ( y , u ) ∈Y×U K : Y × U → Q ′ subject to K ( y , u ) = 0 control u ∈ U , state y ∈ Y Assumption on K : for given u ∈ U , there exists unique state y ∈ Y Solution approach: compute zeroes of first order Fr´ echet derivatives of Lagrangian functional L ( y , u , p ) := J ( y , u ) + �K ( y , u ) , p � Q′×Q L : Y × U × Q → R costate/adjoint p ∈ Q  L y ( y , u , p )   J y ( y , u ) + �K y ( y , u ) , p � Q′×Q  δ L ( y , u , p ) := L u ( y , u , p )  = 0 ⇐ ⇒ J u ( y , u ) + �K u ( y , u ) , p � Q′×Q  = 0     ❀   L p ( z , u , p ) K ( y , u ) Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 2

  5. Optimization Problems: First Order Necessary Conditions Constrained minimization problem inf J ( y , u ) J : Y × U → R Y , U , Q Hilbert spaces ( y , u ) ∈Y×U K : Y × U → Q ′ subject to K ( y , u ) = 0 control u ∈ U , state y ∈ Y Assumption on K : for given u ∈ U , there exists unique state y ∈ Y Solution approach: compute zeroes of first order Fr´ echet derivatives of Lagrangian functional L ( y , u , p ) := J ( y , u ) + �K ( y , u ) , p � Q′×Q L : Y × U × Q → R costate/adjoint p ∈ Q  L y ( y , u , p )   J y ( y , u ) + �K y ( y , u ) , p � Q′×Q  δ L ( y , u , p ) := L u ( y , u , p )  = 0 ⇐ ⇒ J u ( y , u ) + �K u ( y , u ) , p � Q′×Q  = 0     ❀   L p ( z , u , p ) K ( y , u ) Special case: J quadratic in y , u K linear in y , u = ⇒ necessary conditions for optimality are sufficient linear (Karush-Kuhn-Tucker (KKT) or saddle point) system ❀ K ∗     L yy L yu y � B ∗ � � ( y , u ) T � y A K ∗  = g L uy L uu u ⇐ ⇒ : = g ⇐ ⇒ : G q = g  u   B 0 p K y K u 0 p �C ∗ q , r � := � q , C r � A , B linear, continuous; A invertible on ker B ; im B = Q ′ = ⇒ G boundedly invertible Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 2

  6. Optimal Control Problem Constrained by a Parabolic PDE with Distributed Control Given y ∗ ( t , · ) f ω > 0 end time T > 0 initial condition y 0 � T � T 1 � y ( t , · ) − y ∗ ( t , · ) � 2 ω � u ( t , · ) � 2 minimize J ( y , u ) = Z dt + U dt 2 2 0 0 y ′ ( t ) + A ( t ) y ( t ) subject to = f ( t ) + u ( t ) a.e. t ∈ (0 , T ) =: I (PDE) y (0) = y 0 y ′ := ∂ ∂ t y y = y ( t , x ) state u = u ( t , x ) control U = Y ′ = H − 1 (Ω) control space Y = H 1 Z = Y = H 1 0 (Ω) state space 0 (Ω) observation space � A ( t ) : Y → Y ′ � A ( t ) v ( t , · ) , w ( t , · ) � := Ω ⊂ R d [ ∇ v ( t , x ) · ∇ w ( t , x ) + v ( t , x ) w ( t , x )] dx Ω A ( t ) 2nd order linear selfadjoint coercive & continuous operator on Y Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 3

  7. Optimal Control Problem Constrained by a Parabolic PDE with Distributed Control Given y ∗ ( t , · ) f ω > 0 end time T > 0 initial condition y 0 � T � T 1 � y ( t , · ) − y ∗ ( t , · ) � 2 ω � u ( t , · ) � 2 minimize J ( y , u ) = Z dt + U dt 2 2 0 0 y ′ ( t ) + A ( t ) y ( t ) subject to = f ( t ) + u ( t ) a.e. t ∈ (0 , T ) =: I (PDE) y (0) = y 0 y ′ := ∂ ∂ t y y = y ( t , x ) state u = u ( t , x ) control U = Y ′ = H − 1 (Ω) control space Y = H 1 Z = Y = H 1 0 (Ω) state space 0 (Ω) observation space � A ( t ) : Y → Y ′ � A ( t ) v ( t , · ) , w ( t , · ) � := Ω ⊂ R d [ ∇ v ( t , x ) · ∇ w ( t , x ) + v ( t , x ) w ( t , x )] dx Ω A ( t ) 2nd order linear selfadjoint coercive & continuous operator on Y PDE-constrained control problem requires repeated solution of PDE constraint ❀ y ′ ( t ) + A ( t ) y ( t ) = f ( t ) + u ( t ) y (0) = y 0 Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 3

  8. Necessary and Sufficient Conditions for Optimality Optimal control problem constrained by parabolic PDE System of parabolic PDEs coupled globally in time (and space) ❀ y ′ ( t ) + A ( t ) y ( t ) = f ( t ) + u ( t ) a.e. t ∈ I y (0) = y 0 ω ˜ R − 1 u ( t ) + p ( t ) = 0 a.e. t ∈ I − p ′ ( t ) + A ( t ) T p ( t ) ˜ = R ( y ∗ ( t ) − y ( t )) a.e. t ∈ I p ( T ) = 0 Riesz operator ˜ R defined by � v , ˜ Rw � Y × Y ′ := ( v , w ) Y for all v , w ∈ Y Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 4

  9. Necessary and Sufficient Conditions for Optimality Optimal control problem constrained by parabolic PDE System of parabolic PDEs coupled globally in time (and space) ❀ y ′ ( t ) + A ( t ) y ( t ) = f ( t ) + u ( t ) a.e. t ∈ I y (0) = y 0 ω ˜ R − 1 u ( t ) + p ( t ) = 0 a.e. t ∈ I − p ′ ( t ) + A ( t ) T p ( t ) ˜ = R ( y ∗ ( t ) − y ( t )) a.e. t ∈ I p ( T ) = 0 Riesz operator ˜ R defined by � v , ˜ Rw � Y × Y ′ := ( v , w ) Y for all v , w ∈ Y Obstructions for numerical solution: • convential time discretizations: time-marching methods need storage of y ( t i ) , u ( t i ) , p ( t i ) for all discrete times 0 = t 0 , . . . , T = t N ❀ • in each time step: solve elliptic PDE large linear system of equations ❀ iterative solver need preconditioning in (conjugate) gradient method ❀ ❀ • singularities in data/domain: adaptive (FE) mesh(es) for y ( t i ) , u ( t i ) , p ( t i ) for all t i one mesh for all variables, refinement/coarsening ? [Oeltz ’06], [Meidner, Vexler ’07], . . . convergence ? complexity ?? Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 4

  10. Necessary and Sufficient Conditions for Optimality Optimal control problem constrained by parabolic PDE System of parabolic PDEs coupled globally in time (and space) ❀ y ′ ( t ) + A ( t ) y ( t ) = f ( t ) + u ( t ) a.e. t ∈ I y (0) = y 0 ω ˜ R − 1 u ( t ) + p ( t ) = 0 a.e. t ∈ I − p ′ ( t ) + A ( t ) T p ( t ) ˜ = R ( y ∗ ( t ) − y ( t )) a.e. t ∈ I p ( T ) = 0 Riesz operator ˜ R defined by � v , ˜ Rw � Y × Y ′ := ( v , w ) Y for all v , w ∈ Y Obstructions for numerical solution: • convential time discretizations: time-marching methods need storage of y ( t i ) , u ( t i ) , p ( t i ) for all discrete times 0 = t 0 , . . . , T = t N ❀ • in each time step: solve elliptic PDE large linear system of equations ❀ iterative solver need preconditioning in (conjugate) gradient method ❀ ❀ • singularities in data/domain: adaptive (FE) mesh(es) for y ( t i ) , u ( t i ) , p ( t i ) for all t i one mesh for all variables, refinement/coarsening ? [Oeltz ’06], [Meidner, Vexler ’07], . . . convergence ? complexity ?? Solution Ansatz here: full weak space-time form of parabolic PDE constraint Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 4

  11. Variational Space-Time Form for a Single Parabolic Evolution PDE [Ladyshenskaya et al 1967], [Wloka ’82], [Dautray, Lions ’92], [Schwab, Stevenson ’09], [Chegini, Stevenson ’11], [Stapel ’11] . . . y ′ ( t ) + A ( t ) y ( t ) = f ( t ) a.e. t ∈ I (PDE) y (0) = y 0 solution space: Lebesgue-Bochner space Y := ( L 2 ( I ) ⊗ Y ) ∩ ( H 1 ( I ) ⊗ Y ′ ) ֒ → C 0 ( I ) ⊗ L 2 (Ω) with norm � w � 2 Y := � w � 2 L 2( I ) ⊗ Y + � w ′ � 2 H 1( I ) ⊗ Y ′ � v � 2 Q := � v 1 � 2 L 2( I ) ⊗ Y + � v 2 � 2 test space: Q := ( L 2 ( I ) ⊗ Y ) × L 2 (Ω) with norm L 2(Ω) bilinear form b ( · , · ) : Y × Q → R � � w ′ ( t , · ) , v 1 ( t , · ) � + � A ( t ) w ( t , · ) , v 1 ( t , · ) � b ( w , ( v 1 , v 2 )) := � � dt + � w (0 , · ) , v 2 � =: � Bw , v � I right hand side � � f , v � := � f ( t , · ) , v 1 ( t , · ) � dt + � y 0 , v 2 � I ❀ given f ∈ Q ′ , find y ∈ Y : (PDE) By = f Existence and uniqueness of solution: Theorem � Bw � Q′ ∼ � w � Y for all w ∈ Q mapping property (MP) Formulations with 1/2 time derivatives on R : [Fontes ”99], [Larsson, Schwab ’15] Angela Kunoth — Adaptive Wavelet Methods for Parabolic PDE-Constrained Control Problems 5

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