Reason: Proof of the cost limit along the approximate Kalman policy: cost expansion plus completion of squares, the policy identity u = G eps, term-by-term convergence via the filter-error covariance lemma, the covariance-deviation lemma, and the N-uniform fourth-moment bounds; remainder handled by the moduli with a Markov/Cauchy-Schwarz split.
Proof
Throughout, fix the fluctuation LQG data and, for each N, the driving system and projected solution of the statement; superscripts N are suppressed when no confusion can arise. Write E for the expectation of the N-th probability space, ztβ=(stβ,atβ)βRl+m, Οtβ=Nβ1/2β£ztββ£, and ΞΊ=1+supNβE[β£s0Nββ£4], finite by (I2). Fix, by conclusion 1 of the policy lemma and boundedness of continuous functions, entry bounds CZβ for Ztβ and cWβ for WtβRtβ1βWtβ€β on [0,T]; the entries of WtβRtβ1βWtβ€β are continuous, as finite sums of products of the continuous entries of Z, B, V, Rβ1 (conclusion 1 of the policy lemma and (H2)). By conclusion 1 of the policy lemma, its matrices Qtβ, Vtβ, Rtβ, Wtβ, and F^ are given by the same defining formulas as those of the completion-of-squares theorem, and the family Z of (H2) satisfies the Riccati equation of hypothesis (H2) of that theorem; so both that theorem and the cost expansion theorem are available for each fixed N, their common hypothesis A=β«[0,T]βE[β£atββ£2]dt<β holding by part (a) of the filter error covariance lemma. By part (d) of that lemma there is a real C1β, independent of N, with
for every N (the second bound obtained from the first, together with E[β£β β£2]β€1+E[β£β β£4] applied to the four summands of the first display and ΞΊβ₯1, as in part (d) of that lemma); in particular E[β£ztββ£2]β€2(4+C1β)ΞΊ and E[β£ztββ£4]β€8(E[β£stββ£4]+E[β£atββ£4])β€16C1βΞΊ for all t and N. Finally, the limit integrand tβ¦Ztββ Ξtββ+(WtβRtβ1βWtβ€β)β Ξ tβ is continuous, being a finite sum of products of continuous functions (conclusions 1 and 2 of the policy lemma and (H2)), which proves the first assertion.
Step 1: expansion and completion of squares. Fix N. By parts (b) and (c) of the cost expansion theorem, JN[hN] is finite, LQG[(s),(a)] is a well-defined real number, and
with RNβ obeying the modulus bound of its part (c). By part (c) of the completion-of-squares theorem, with utβ=atβ+Rtβ1βWtβ€βstβ and esβ its linearization residual,
all terms finite. In particular each N(JN[hN]βJMF)+βΞ³βP0Ξ³βΞΆNΞ³β is a well-defined real number. We treat the four pieces in Steps 2--5.
Step 2: initial term.E[s0ββ Z0βs0β]=βΞ³,Ξ΄βZ0Ξ³Ξ΄βE[s0N,Ξ³βs0N,Ξ΄β]ββΞ³,Ξ΄βZ0Ξ³Ξ΄βΞ 0Ξ³Ξ΄β=Z0ββ Ξ 0β as Nββ, by (I1) and linearity (a finite sum of convergent sequences).
Step 3: control term. By conclusion 4(a) of the policy lemma, atβ=N1/2(Ξ±tββAtβ)=βRtβ1βWtβ€βs^tNβ on the regular event, hence almost surelyutβ=Rtβ1βWtβ€β(stββs^tNβ)=GtβΞ΅tNβ. Therefore, for every s,
By part (e) of the filter error covariance lemma, the supremum is at most C(maxΞ³,Ξ΄ββ£E[s0N,Ξ³βs0N,Ξ΄β]βΞ 0Ξ³Ξ΄ββ£+Nβ1/2(1+E[β£s0Nββ£4]))β€C(maxΞ³,Ξ΄ββ£E[s0N,Ξ³βs0N,Ξ΄β]βΞ 0Ξ³Ξ΄ββ£+Nβ1/2ΞΊ), which tends to 0 by (I1) and (I2). Hence β«E[usββ Rsβusβ]dsββ«[0,T]β(WsβRsβ1βWsβ€β)β Ξ sβds.
with the constant cΞβ of that lemma and S+Aβ€2T(4+C1β)ΞΊ by (0.1). This tends to 0, and β«[0,T]ββΞ³,Ξ΄βZsΞ³Ξ΄βΞΞ³Ξ΄(Ssβ,Asβ)ds=β«[0,T]βZsββ Ξsββds by the definition of the pairing.
Step 5: residual term. By part (b) of the completion-of-squares theorem, β£esββ£β€ceβNβ1/2(β£ssββ£2+β£asββ£2)=ceβNβ1/2β£zsββ£2 with ceβ=23βl3/2(l+m)K. Since β£xβ Zsβyβ£β€CZβ(βΞ³ββ£xΞ³β£)(βΞ΄ββ£yΞ΄β£)β€lCZββ£xβ£β£yβ£, and pointwise β£ssββ£β£zsββ£2β€β£zsββ£3β€1+β£zsββ£4,
Step 6: the remainder vanishes. Let ΞΈ>0. By part (a) of the cost expansion theorem there is Ξ΄β>0 with ΟLβ(u)β€ΞΈ, Οbβ(u)β€ΞΈ, and ΟGβ(u)β€ΞΈ for all uβ[0,Ξ΄β], and globally ΟLββ€2Kcβ, Οbββ€6lK, ΟGββ€2Kcβ. Let CPβ be the co-state bound of that theorem and write ΟΛ=2Kcβ+CPβ6lK. Splitting the time integral of its part (c) on the events {Οtββ€Ξ΄β} and {Οtβ>Ξ΄β} (the moduli being nondecreasing) and using monotonicity,
where 1Eβ denotes the indicator of the event E and we used d(Ξ£Tβ,STβ)=Nβ1/2β£sTββ£. By the Cauchy-Schwarz inequality and Markov's inequality applied to the nonnegative variable β£ztββ£2 at level N(Ξ΄β)2,
using C1β(4+C1β)ββ€4+C1β (since C1ββ€4+C1β) and 42ββ€6; using (0.1), and the same bound holds for the terminal term with β£sTββ£ in place of β£ztββ£. Hence, with (0.1) again,
Step 7: conclusion. Combining Steps 1--6, the sequence N(JN[hN]βJMF)+βΞ³βP0Ξ³βΞΆNΞ³β is, for each N, the sum of four terms converging respectively to Z0ββ Ξ 0β, β«[0,T]β(WsβRsβ1βWsβ€β)β Ξ sβds, β«[0,T]βZsββ Ξsββds, and 0, plus the remainder RNββ0. The limit identity follows, the two integrals combining by linearity of the integral into the integral of the continuous integrand recorded in the statement. β