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Optimal Bounds for POD Approximations of Infinite Horizon Control Problems Based on Time Derivatives

Abstract

In this paper we consider the numerical approximation of infinite horizon problems via the dynamic programming approach. The value function of the problem solves a Hamilton–Jacobi–Bellman equation that is approximated by a fully discrete method. It is known that the numerical problem is difficult to handle by the so called curse of dimensionality. To mitigate this issue we apply a reduction of the order by means of a new proper orthogonal decomposition (POD) method based on time derivatives. We carry out the error analysis of the method using recently proved optimal bounds for the fully discrete approximations. Moreover, the use of snapshots based on time derivatives allows us to bound some terms of the error that could not be bounded in a standard POD approach. Some numerical experiments show the good performance of the method in practice.

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Optimal Bounds for POD Approximations of Infinite Horizon Control Problems Based on Time Derivatives

Author: De Frutos, Javier; García-Archilla, Bosco; Novo, Julia
Publisher: Springer
Year: 2025
DOI: 10.1007/s10915-025-02833-0
Source: https://idus.us.es/bitstreams/807ae755-9024-4eec-af3b-1df7ee620912/download
Jou nal o Scien i ic Compu ing (2025) 103:19
h ps://doi.o g/10.1007/s10915-025-02833-0
Op imal Bounds o POD App oxima ions o In ini e Ho izon
Con ol P oblems Based on Time De i a i es
Ja ie de F u os1
·Bosco Ga cía-A chilla2
·Julia No o3
Recei ed: 30 Oc obe 2023 / Re ised: 30 Janua y 2025 / Accep ed: 17 Feb ua y 2025 /
Published online: 1 Ma ch 2025
© The Au ho (s) 2025
Abs ac
In his pape we conside he nume ical app oxima ion o in ini e ho izon p oblems ia he
dynamic p og amming app oach. The alue unc ion o he p oblem sol es a Hamil on–
Jacobi–Bellman equa ion ha is app oxima ed by a ully disc e e me hod. I is known ha
he nume ical p oblem is di icul o handle by he so called cu se o dimensionali y. To
mi iga e his issue we apply a educ ion o he o de by means o a new p ope o hogonal
decomposi ion (POD) me hod based on ime de i a i es. We ca y ou he e o analysis
o he me hod using ecen ly p o ed op imal bounds o he ully disc e e app oxima ions.
Mo eo e , he use o snapsho s based on ime de i a i es allows us o bound some e ms o he
e o ha could no be bounded in a s anda d POD app oach. Some nume ical expe imen s
show he good pe o mance o he me hod in p ac ice.
Keywo ds Dynamic p og amming ·Hamil on–Jacobi–Bellman equa ion ·Op imal con ol ·
P ope o hogonal decomposi ion ·Snapsho s based on ime de i a i es ·E o analysis
1 In oduc ion
In his pape we conside he nume ical app oxima ion o op imal con ol p oblems. The
subjec is o impo ance o many applica ions such as ae ospace enginee ing, chemical
p ocessing and esou ce economics, among o he s.
The alue unc ion o an op imal con ol p oblem is ob ained in e ms o a i s -o de
nonlinea Hamil on–Jacobi–Bellman (HJB) pa ial di e en ial equa ion. A bo leneck in he
compu a ion o he alue unc ion comes om he need o app oach a nonlinea pa ial
di e en ial equa ion in dimension n, which is a challenging p oblem in high dimensions.
BJulia No o
julia.no [email p o ec ed]
Ja ie de F u os
[email p o ec ed]a.es
Bosco Ga cía-A chilla
[email p o ec ed]
1Ins i u o de In es igación en Ma emá icas (IMUVA), Uni e sidad de Valladolid, Valladolid, Spain
2Depa amen o de Ma emá ica Aplicada II, Uni e sidad de Se illa, Se ille, Spain
3Depa amen o de Ma emá icas, Uni e sidad Au ónoma de Mad id, Mad id, Spain
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19 Page 2 o 28 Jou nal o Scien i ic Compu ing (2025) 103 :19
Se e al me hods ha e been s udied in he li e a u e ying o mi iga e he so called cu se
o dimensionali y al hough i is s ill a di icul ask. As s a ed in [10], he ele ance o e i-
cien nume ical me hods can be seen by he ac ha me hods sol ing he HJB equa ion a e
a ely used in p ac ice due o he necessa y compu a ional e o . We men ion some ela ed
e e ences ha a e no in ended o be a comple e lis . In [14], a domain decomposi ion ech-
nique is conside ed. In [26] semi-Lag angian me hods a e s udied. The au ho s in [22] apply
da a-based app oxima e policy i e a ion me hods. A p ocedu e o he nume ical app oxima-
ion o high-dimensional HJB equa ions associa ed o op imal eedback con ol p oblems o
semilinea pa abolic equa ions is p oposed in [19]. In [9] a enso decomposi ion app oach
is p esen ed. In [10] an app oach based on low- ank enso ain decomposi ions is applied.
Me hods using spa se g ids o HJB equa ions a e p esen ed in [6]. The solu ion o HJB equa-
ions on a ee s uc u e was p esen ed in [2]. The au ho o [23,24] discusses an app oach o
ce ain nonlinea HJB PDEs which is no subjec o he cu se o dimensionali y. The app oach
u ilizes he max-plus algeb a. In [8] a da a-d i en app oach based on he knowledge o he
alue unc ion and i s g adien on sample poin s is de eloped. The au ho s o [3]p esen anew
app oach whe e he alue unc ion is compu ed using adial basis unc ions. Expanded li e -
a u e on he con ol o pa ial di e en ial equa ions using dynamic p og amming app oach
can be ound in he las wo e e ences.
In he p esen pape we concen a e on educed o de models based on p ope o hogonal
decomposi ion (POD) me hods. Ou wo k is ela ed o [1]. In his e e ence he au ho s
p opose wo di e en ways o apply POD me hods in he nume ical app oxima ion o he
ully-disc e e alue unc ion. In he i s app oach, he au ho s choose a se o nodes in he
o iginal domain ⊂Rnand p ojec hen on o a educed space  ⊂R wi h <n o ge a
new se o nodes. The p oblem in his p ocedu e is ha i p oduces a nonuni o m g id in which
he mesh diame e canno be p edic ed a p io i. Consequen ly, he me hod is no sui able o
implemen in p ac ice. Fu he mo e, al hough his is no e lec ed in he e o bounds in [1],
he e o also depends on he in e pola ion p ope ies o he a p io i unknown educed mesh
in  ⊂R . In he second app oach, he au ho s use a uni o m mesh o e he educed space
 . This second me hod can be implemen ed in p ac ice ( he nume ical expe imen s in [1]
a e ca ied ou wi h his me hod). Howe e , as he au ho s s a e, he compu a ion o an uppe
bound o he e o in his case is much mo e in ol ed and he e o bound p o ed in [1]has
some d awbacks see [1, Rema k 4.7, Rema k 4.9].
Recen ly in [7], a new e o analysis is in oduced in which a bound o size O(h+k)is
ob ained o he ully disc e e app oxima ions o in ini e ho izon p oblems ia he dynamic
p og amming app oach. In his e o bound, his he ime s ep while kis he spa ial mesh
diame e . This e o bound imp o es exis ing esul s in he li e a u e, whe e only O(k/h)
e o bounds a e p o ed, see [12,13].
To bound he e o in he i s me hod in [1] he au ho s ollow he echnique in [12,
Co olla y 2.4], [13, Theo em 1.3] ob aining a bound o he e o o size O(k/h).Fo he
second me hod in [1], he ac o 1/halso mul iplies all he e ms on he igh -hand side o
he a p io i e o bound.
In his pape we p esen a new app oach, simila o he second me hod in [1], bu wi h
snapsho s based on he alue a di e en imes o he ime de i a i e o he s a e o he
con olled nonlinea dynamical sys em, ins ead o alues o he s a e a di e en imes. This
new app oach is inspi ed in he ecen esul s in [15] whe e he au ho s p o e ha he use
o snapsho s based on ime de i a i es has he ad an age o p o iding poin wise es ima es
o he e o be ween a unc ion and i s p ojec ion on o he POD space.The idea o using
snapsho s app oaching he ime de i a i es is no new, al hough mos o he e e ences in
he li e a u e employ i s o de di e ence quo ien s (DQs) (i.e. i s o de di ided ini e
123
Jou nal o Scien i ic Compu ing (2025) 103 :19 Page 3 o 28 19
di e ences) ins ead o Gale kin ime de i a i es, as in [15] and he p esen pape . In [21]
he se o snapsho s (a di e en imes) is inc eased wi h DQs o ca y ou he e o analysis
o he case in which p ojec ions espec o he H1
0no m a e conside ed. In a mo e ecen
pape , [20], he au ho s show ha he use o DQs has he added p ope y o allowing o p o e
poin wise es ima es in ime. In a la e pape , [11], he au ho s p o e ha one does no need
o double he se o snapsho s wi h alues a di e en imes plus DQs since only DQs plus
a single ini ial alue a e enough o ge poin wise es ima es. This is a e y in e es ing esul
because one can wo k wi h he same numbe o snapsho s as in he s anda d case ( he one
wi h only alues o he s a es a di e en imes). In [15], he au ho s p o e ha his is also
he case wi h ime de i a i es. A se o snapsho s based on ime de i a i es plus he snapsho
a he ini ial ime (o he mean alue o he s a es) is able o p o ide poin wise in ime e o
es ima es. This is he idea we apply in he p esen pape . Mo eo e , we ca y ou a di e en
e o analysis based on he ecen esul s ob ained in [7] ha allow us o ge sha pe e o
bounds ee o 1/h ac o s. This is in ag eemen wi h he nume ical in es iga ions in he
li e a u e whe e he 1/hbeha iou in he e o bounds o ully disc e e me hods has ne e
been obse ed. Also, he use o snapsho s based on ime de i a i es allows us o gi e a bound
o some e ms ha could no be bounded wi h he s anda d app oach. Bo h ac s, he new
echnique used o bound he e o ha ollows ideas in [7] oge he wi h he use o snapsho s
based on ime de i a i es, a e he key ing edien s o ge e o bounds o he new me hod ha
a e op imal in e ms o he ime s ep hand he mesh diame e o he educed space k .As
usual, ou e o bounds o he POD me hod depend also on he size o he ail o eigen alues
in he singula alue decomposi ion.
The ou line o he pape is as ollows. In Sec .2we s a e he model p oblem and some
p elimina y esul s. In Sec .3we in oduce he POD app oxima ion and ca y ou he e o
analysis o he me hod. Finally, in Sec .4we show some nume ical expe imen s in which we
implemen he me hod we p opose in he pape . In he expe imen s o Sec .4we choose he
same nume ical es s as in [1] o compa e ou esul s wi h hose in his ela ed e e ence. The
me hod in oduced in he p esen pape seems o p oduce be e esul s han hose shown in
[1]. We inish he pape wi h some conclusions.
2 Model P oblem and S anda d Nume ical App oxima ion
In he sequel, ·deno es any no m associa ed o an inne p oduc and ·∞deno es he
maximum no m o ec o s in Rn,n≥1. We will also deno e by ·2 he s anda d euclidean
no m. In pa icula , in he nume ical expe imen s, we use a weigh ed no m ·sligh ly
di e en om he s anda d euclidean no m ·2.
Fo a nonlinea mapping
:Rn×Rm→Rn,
and a gi en ini ial condi ion y0∈Rnle us conside he con olled nonlinea dynamical
sys em
˙y( )= (y( ), u( )) ∈Rn, >0,y(0)=y0∈Rn,(1)
oge he wi h he in ini e ho izon cos unc ional
J(y,u)=∞
0
g(y( ), u( ))e−λ d .(2)
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19 Page 4 o 28 Jou nal o Scien i ic Compu ing (2025) 103 :19
In (2)λ>0 is a gi en weigh ing pa ame e and
g:Rn×Rm→R.
The se o admissible con ols is
Uad ={u∈U|u( )∈Uad o almos all ≥0},
whe e U=L2(0,∞;Rm)and Uad ⊂Rmis a compac con ex subse .
As in [1, Assump ion 2.1] we assume he ollowing hypo heses:
•The igh -hand side in (1) is con inuous and globally Lipschi z-con inuous in bo h he
i s and second a gumen s; i.e., he e exis s a cons an L >0 sa is ying
 (y,u)− (˜y,u)≤L y−˜y,∀y,˜y∈Rn,u∈Uad,(3)
 (y,u)− (y,˜u)≤L u−˜u,∀u,˜u∈Uad,y∈Rn.(4)
•The igh -hand side in (1) sa is ies ha he e exis s a cons an M >0 such ha he
ollowing bound holds
 (y,u)∞≤M ,∀y∈⊂Rn,u∈Uad,(5)
whe e is a bounded polyhed on such ha o su icien ly small h>0 he ollowing
inwa d poin ing condi ion on he dynamics holds
y+h (y,u)∈, ∀y∈, u∈Uad.(6)
•The unning cos gis con inuous and globally Lipschi z-con inuous in bo h he i s and
second a gumen s; i.e., he e exis s a cons an Lg>0 sa is ying
|g(y,u)−g(˜y,u)|≤Lgy−˜y,∀y,˜y∈Rn,u∈Uad,(7)
|g(y,u)−g(y,˜u)|≤Lgu−˜u,∀u,˜u∈Uad,y∈Rn.(8)
•Mo eo e , he e exis s a cons an Mg>0 such ha
|g(y,u)|≤Mg,∀(y,u)∈×Uad.(9)
F om he assump ions made on he e exis s a unique solu ion o (1)y=y(y0,u)de ined
on [0,∞) o e e y admissible con ol u∈Uad and o e e y ini ial condi ion y0∈Rn,see
[4, Chap e 3]. We de ine he educed cos unc ional as ollows:
ˆ
J(y0,u)=J(y(y0,u), u), ∀u∈Uad,y0∈Rn,(10)
whe e y(y0,u)sol es (1). Then, he op imal con ol can be o mula ed as ollows: o gi en
y0∈Rnwe conside
min
u∈Uad ˆ
J(y0,u).
The alue unc ion o he p oblem is de ined as :Rn→Ras ollows:
(y)=in ˆ
J(y,u)|u∈Uad,y∈Rn.(11)
This unc ion gi es he bes alue o e e y ini ial condi ion, gi en he se o admissible
con ols Uad. I is cha ac e ized as he iscosi y solu ion o he HJB equa ion co esponding
o he in ini e ho izon op imal con ol p oblem:
λ (y)+sup
u∈Uad {− (y,u)·∇ (y)−g(y,u)}=0,y∈Rn.(12)
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Jou nal o Scien i ic Compu ing (2025) 103 :19 Page 5 o 28 19
The solu ion o (12) is unique o su icien ly la ge λ,λ>max(Lg,L ),[4].
Le us conside i s a ime disc e iza ion whe e his a s ic ly posi i e s ep size. We
conside he ollowing semidisc e e scheme o (12):
h(y)=min
u∈Uad {(1−λh) h(y+h (y,u)) +hg(y,u)},y∈Rn.(13)
As i is well-known equa ion (13) ep esen s a nume ical app oxima ion ela ed o he HJB
equa ion (12) (see Rema k 7). The ollowing con e gence esul o he semidisc e e app ox-
ima ion [12, Theo em 2.3] equi es ha o (y,˜y,u)∈Rn×Rn×Uad
 (y+˜y,u)−2 (y,u)+ (y−˜y,u)≤C ˜y2,(14)
g(y+˜y,u)−2g(y,u)+g(y−˜y,u)≤Cg˜y2.(15)
Theo em 1 Le assump ions (3),(5),(6),(7),(9),(14)and (15)hold and le λ>
max(2Lg,L ).Le and hbe he solu ions o (12)and (13), espec i ely. Then, he e
exis s a cons an C ≥0, ha can be bounded explici ly, such ha he ollowing bound holds
sup
y∈Rn| (y)− h(y)|≤Ch,h∈[0,1/λ). (16)
As in [1] le us suppose ha he e exis s a bounded polyhed on ⊂Rnsuch ha o h>0
small enough (6) holds. We conside a ully-disc e e app oxima ion o (12). Le Sjms
j=1be
a amily o simplices which de ines a egula iangula ion o 
=
ms

j=1
Sj,k=max
1≤j≤ms
(diam Sj).
We assume we ha e ns e ices/nodes ˆy1,..., ˆynsin he iangula ion. Le Vkbe he space o
piecewise a ine unc ions om  o Rwhich a e con inuous in ha ing cons an g adien s
in he in e io o any simplex Sjo he iangula ion. Then, a ully disc e e scheme o he
HJB equa ions is gi en by
h,k(ˆyi)=min
u∈Uad (1−λh) h,k(ˆyi+h (ˆyi,u)) +hg(ˆyi,u),(17)
o any e ex ˆyi∈. The e exis s a unique solu ion o (17) in he space Vk,see[4, Theo em
1.1, Appendix A].
Fo he ully disc e e me hod i we assume ha he con ols a e Lipschi z-con inuous; i.e.,
he e exis s a posi i e cons an Lu>0 such ha
u( )−u(s)2≤Lu| −s|,(18)
hen i s o de o con e gence bo h in ime and space is p o ed in [7, Theo em 6].
Theo em 2 Assume condi ions (3)–(5),(7)–(9)and (18)hold. Assume λ>L wi h L=
CnL . Then, o 0≤h≤1/(2λ) he e exis posi i e cons an s C1=C1(λ, M ,Mg,L ,Lg)
and C2=C2(λ, L ,Lg,Lu)such ha
| (y)− h,k(y)|≤C1(h+k)+C2h,y∈.
Condi ion (18) can be weakened and one can s ill ge con e gence as p o ed in [7, Theo em
7]. Assume he ollowing con exi y assump ion in oduced in [5, (A4)] and deno ed by (CA)
as in [5,7],
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19 Page 6 o 28 Jou nal o Scien i ic Compu ing (2025) 103 :19
•(CA) Fo e e y y∈Rn,
{ (y,u), g(y,u), u∈Uad}
is a con ex subse o Rn+1.
Theo em 3 Assume condi ions (3),(4),(5),(7),(8),(9)and (CA) hold. Assume λ>L
wi h L de ined as in Theo em 2. Then, o 0≤h≤1/(2λ) he e exis posi i e cons an s
C1=C1(λ, M ,Mg,L ,Lg)and C2=C2(λ, M ,Mg,L ,Lg)such ha o y ∈
| (y)− h,k(y)|≤C1(h+k)+C2
1
(1+β)2λ2(log(h))2h1
1+β,β=√nL
λ.(19)
Le us obse e ha since βis smalle han 1, by weakening he egula i y equi emen s we
loose a mos hal an o de in he a e o con e gence in ime o he me hod up o a loga i hmic
e m.
3 POD App oxima ion o he Op imal Con ol P oblem Based on Time
De i a i es
In his sec ion we p esen a new app oach, simila o he second me hod in [1], bu wi h
snapsho s based on ime de i a i es a di e en imes. We also pe o m a comple ely di e en
e o analysis o he one appea ing in [1], inspi ed in he esul s in [7]and[15].
3.1 POD App oxima ion Based on Time De i a i es
Fo p∈Nle us choose di e en pai s (uν,yν
0)p
ν=1in U×.SinceU=L2(0,∞;Rm)
he con ols do no need o be cons an s, as hose aken in he nume ical expe imen s. By
yν=y(uν;yν
0),ν=1,...,p, we deno e he solu ions o (1) co esponding o hose chosen
ini ial condi ions and con ols.
Le us ix T>0andM>0and ake =T/Mand j=j ,j=0,...,M.Fo
N=M+1 we de ine he ollowing space
V=span zν
1,zν
2,...,zν
Np
ν=1,
wi h
zν
1=√N yν,yν=1
N
M

j=0
yν( j)
zν
j=τyν
( j−1), j=2,...,N,
so ha
V=span √N yν,τyν
( 1),...,τyν
( N)p
ν=1,
whe e he ac o τin on o he empo al de i a i es is a ime scale and i makes he snapsho s
dimensionally co ec . In he nume ical expe imen s we ake τ=1. The co ela ion ma ix
co esponding o he snapsho s is gi en by K=((ki,j)) ∈RpN×pN, wi h he en ies
ki,j=1
pN zi
k,zj
l,k,l=1,...,N,i,j=1,...,p,
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Jou nal o Scien i ic Compu ing (2025) 103 :19 Page 7 o 28 19
and whe e he e, and in he sequel, (·,·)deno es he inne p oduc in Rn o which he no m
||·||is associa ed. Le us deno e o simplici y
V=span w1,w
2,...,wpN:= z1
1,...z1
N,...,zp
1,...,zp
N.
Following [21], we deno e by λ1≥λ2,... ≥λd>0 he posi i e eigen alues o Kand by
1,..., d∈RpN i s associa ed eigen ec o s o euclidean no m 1. Then, he (o hono mal)
POD basis unc ions o Va e gi en by
ϕk=1
√pN
1
√λk
pN

j=1
j
kwj,k=1,...,d,(20)
whe e j
kis he j- h componen o he eigen ec o k. The ollowing e o es ima e is known
om [21, P oposi ion 1]
1
pN
pN

j=1





wj−

k=1
(wj,ϕ
k)ϕk




2
=
d

k= +1
λk,(21)
om which one can deduce o ν=1,...,p





yν−

k=1
(yν,ϕ
k)ϕk




2
+τ2
M+1
M

j=1





yν
( j)−

k=1
(yν
( j), ϕk)ϕk




2
≤p
d

k= +1
λk.(22)
In he sequel, we will deno e by
V =span{ϕ1,ϕ
2,...,ϕ
},1≤ ≤d,(23)
and by P Rn→V , he o hogonal p ojec ion on o V .Then(21) can be w i en as
1
pN
pN

j=1
wj−P wj

2=
d

k= +1
λk.
The ollowing lemma is p o ed in [15, Lemma 3.2].
Lemma 1 Le T >0, =T/M, n=n , n =0,1,...M, le X be a Banach space,
z∈H2(0,T;X). Then, he ollowing es ima e holds
max
0≤k≤Nzk2
X≤3z2
X+12T2
M
M

n=1zn
2
X+16T
3( )2T
0z (s)2
Xds,(24)
whe e z=1
M+1M
j=0zj.
Using Lemma 1we can p o e poin wise es ima es o he p ojec ions on o V .
Lemma 2 The ollowing bounds hold o ν=1,...,p
max
0≤j≤Myν( j)−P yν( j)2≤3+24 T2
τ2p
d

k= +1
λk+16T
3( )2T
0yν
(s)2ds.
(25)
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19 Page 8 o 28 Jou nal o Scien i ic Compu ing (2025) 103 :19
P oo We a gue as in [15, Lemma 3.4]. Taking z=yν( j)−P yν( j)in (24) and applying
(22) ( aking in o accoun ha (M+1)/M≤2) yields
max
0≤n≤Myν( j)−P yν( j)2≤3+24 T2
τ2p
d

k= +1
λk
+16T
3( )2T
0yν
(s)−P yν
(s)2ds.
Now, since P is an o hogonal p ojec ion, we ha e yν
(s)−P yν
(s)2≤yν
(s)2and
he p oo is inished 
3.2 The POD Con ol P oblem
To mi iga e he cu se o dimensionali y, he idea o he POD me hod is o wo k on a space
o dimension wi h <n. To s a we need o in oduce some no a ion.We use a sligh ly
di e en no a ion om he one used in [1]. In pa icula , as s a ed below, P
c.isalwaysused
o deno e coe icien s and ϕis always used o he linea combina ion based on he POD basis
unc ions o he educed o de space. Mo e p ecisely: o any y∈⊂Rnle us deno e by
P
cy∈R he coe icien s o he p ojec ion o yon o V
P
cy={(y,ϕ
k)}
k=1.(26)
Fo any y ∈R le us deno e by ϕy ∈Rn he ec o whose coe icien s in he POD basis
a e he componen s o y , i.e.,
ϕy =

j=1
y
jϕj,(27)
whe e y
jis he jcomponen o he ec o y .
Fo and gin (1), (2)and(y ,u)∈R ×Uad we de ine
(y ,u)=P
c (ϕy ,u)∈R ,
g (y ,u)=g(ϕy ,u)∈R.(28)
To ha e an inwa d poin ing condi ion on he dynamics in he educed space, analogous o
(6), ollowing [1, Sec ion 4.2], we assume ha he e exis s a bounded polyhed on  ⊂R
sa is ying
P
cy∈ ,∀y∈. (29)
The ollowing lemma p o es ha he inwa d poin ing condi ion o  ollows om (29).
Lemma 3 Condi ion (29)implies ha
y +h (y ,u)∈ ,y =P
cy,y∈,
p o ided he s ep size h o P y−yis su icien ly small.
P oo We ollow [1, Rema k 4.5] o he p oo . We i s obse e ha
y +h (y ,u)=P
cy+hP
c (ϕy ,u).
Adding and sub ac ing hP
c (y,u)we ge
y +h (y ,u)=P
c(y+h (y,u)) +hP
c( (ϕy ,u)− (y,u)). (30)
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Jou nal o Scien i ic Compu ing (2025) 103 :19 Page 9 o 28 19
Applying condi ion (6)y+h (y,u)∈and applying (29) he i s e m on he igh -hand
side o (30) e i ies P
c(y+h (y,u)) ∈ . Then, we only need o show ha he second
e m on he igh -hand side o (30) is small enough o ho P y−ysu icien ly small.
Le us deno e by z= (ϕy ,u)− (y,u)∈Rn.SinceP
cz={(z,ϕ
k)}
k=1∈R , aking
in o accoun ha he unc ions ϕkde ine an o hono mal basis and ha P is a p ojec ion, we
ha e
P
cz2=P z≤z.
Applying he abo e inequali y oge he wi h (3), we ge
P
cz2
2=P
c( (ϕy ,u)− (y,u))2
2≤ (ϕy ,u)− (y,u)2
≤L2
ϕy −y2=L2
P y−y2,(31)
so ha he p oo is concluded. 
We can now de ine he educed o de p oblem we sol e in p ac ice. Fo and g de ined in
(28) and a gi en ini ial condi ion y
0∈R le us conside he con olled nonlinea dynamical
sys em
˙y ( )= (y ( ), u( )) ∈R , >0,y (0)=y
0∈R ,(32)
oge he wi h he in ini e ho izon cos unc ional
J (y ,u)=∞
0
g (y ( ), u( ))e−λ d .(33)
As in (10), we de ine he educed cos unc ional
ˆ
J (y
0,u)=J (y (y
0,u), u), ∀u∈Uad,y
0∈R ,(34)
whe e y (y
0,u)sol es (32). Then, he POD op imal con ol can be o mula ed as ollows:
o gi en y
0∈R we conside
min
u∈Uad ˆ
J (y
0,u).
The alue unc ion o he p oblem :R →Ris de ined as ollows:
(y )=in ˆ
J(y ,u)|u∈Uad,y ∈R .(35)
Rema k 1 I is easy o check ha he egula i y assump ions o and g analogous o hose
o and g,(3), (4), (5), (7), (8)and(9), hold om he de ini ion o and g and he
p ope ies being ue o and g.
To ge in p ac ice a ully disc e e app oxima ion in he educed space le us de ine S
jm
s
j=1
a amily o simplices which de ines a egula iangula ion o  .Weassumeweha ens
e ices/nodes in he iangula ion ˆy1
,..., ˆyns
∈ and
 =
m
s

j=1
S
j,k =max
1≤j≤m
s
(diam S
j).
Le Vk be he space o piecewise a ine unc ions om  o Rwhich a e con inuous in
 ha ing cons an g adien s in he in e io o any simplex S
jo he iangula ion. As in [1,
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19 Page 16 o 28 Jou nal o Scien i ic Compu ing (2025) 103 :19
Sec ion 1.2], he con ols could no be unique bu one can selec he con ol wi h minimum
no m. Now, le us obse e ha o he disc e e alue unc ion i holds
h,k(ˆyi+h (ˆyi,ui
h,k)) = h,k(ˆyi)+h (yi,ui
h,k)·∇ h,k(ˆyi)+O(h2). (52)
Taking in o accoun ha
h,k(ˆyi)=(1−λh) h,k(ˆyi+h (ˆyi,ui
h,k)) +hg(ˆyi,ui
h,k), (53)
and inse ing (52)in o(53)wege
h,k(ˆyi)=(1−λh) h,k(ˆyi)+h (yi,ui
h,k)·∇ h,k(ˆyi)+O(h2)
+hg(ˆyi,ui
h,k).
And hen
λh h,k(ˆyi)=h (ˆyi,ui
h,k)·∇ h,k(ˆyi)+hg(ˆyi,ui
h,k)+O(h2).
F om which
λ h,k(ˆyi)= (ˆyi,ui
h,k)·∇ h,k(ˆyi)+g(ˆyi,ui
h,k)+O(h).
Now, since
λ ( ˆyi)= (ˆyi,ui)·∇ (ˆyi)+g(ˆyi,ui), (54)
and h,k(ˆyi)→ (ˆyi), o h,k→0 we ob ain
(ˆyi,ui
h,k)·∇ h,k(ˆyi)+g(ˆyi,ui
h,k)→ (ˆyi,ui)·∇ (ˆyi)+g(ˆyi,ui). (55)
A guing as in [13, Sec ion 1.2], le us de ine
L(y,u)=1
λ( (y,u)·∇ (y)+g(y,u)),
and le us associa e wi h ya (unique) con ol u(y)such ha
L(y,u(y)) =min
u∈Uad
L(y,u)= (y).
Assume
∇ h,k(ˆyi)→∇ (ˆyi)(56)
(which we ha e no p o ed) and ui
h,k→ui o h,k→0. Then, on he one hand, om (55),
L(ˆyi,ui
h,k)→L(ˆyi,ui),
and, on he o he
L(ˆyi,ui
h,k)→L(ˆyi,ui)
which implies ui=uiand ui
h,k→ui o h,k→0. Finally, le us obse e ha he a gumen
in [13, Sec ion 1.2] had al eady p o ed ha o any ixed hand k→0 he ully disc e e
con ols ui
h,kcon e ge o he co esponding semi-disc e e ime con ol de ined in (13), o
ha alue o h.
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Jou nal o Scien i ic Compu ing (2025) 103 :19 Page 17 o 28 19
4 Nume ical Expe imen s
We now p esen some nume ical expe imen s. We closely ollow hose in [1] so ha he new
me hod we p opose can be compa ed wi h he me hod in [1]. The au ho s in [1] apply s a e
snapsho s in he educed o de me hod ins ead o snapsho s based on ime de i a i es. We
obse e ha , as explained in de ail in he in oduc ion, in he las case i is no necessa y
o conside bo h, s a e snapsho s and ime de i a i es, since i has al eady been p o ed ha
only wi h ime de i a i es op imal bounds can be ob ained. We obse e ha we ha e chosen
he closed-loop con ol ype app oach ins ead o he open-loop con ol ype app oach in he
p esen pape . Also, he heo y o he p esen pape de elops he i s app oach. We do no
compa e he p esen me hod wi h me hods based on he i s app oach since ou aim is jus
o p opose, analyze and check in p ac ice a new me hod ha could be be e o no (p obably
depending on he examples) han o he me hods in he li e a u e. The nume ical expe imen s
o his sec ion show ha ou me hod wo ks ine in p ac ice and is able o p o ide accu a e
app oxima ions.
We i s no ice ha due o nume ical easons we ha e o choose a ini e ime ho izon,
so we selec a su icien ly la ge e>0, which, in he expe imen s ha ollow, i was ixed
o e=3. As in [1], we conside he ollowing con ec ion- eac ion-di usion equa ion
z −εzxx +γzx+μ(z3−z)=ub in I×(0, e),
z(·,0)=z0in I,
z(·, )=0in∂I×(0, e),
(57)
wi h ε=1/10, and whe e I=(0,a)is an open in e al, z:I×[0, e]→Rdeno es he s a e,
and γand μa e posi i e cons an s. The con ols ubelong o he closed, con ex, bounded
se Uad =L2(0, e,[ua,ub]), o eal alues ua<ub. The cos unc ional o minimize is
gi en by
 e
0
e−λ z(·, ,u)2
L2(I)+1
100 |u( )|2d ,(58)
whe ewese λ=1. No ice hen ha in (58) he aim is o d i e he s a e o ze o.
We use a ini e-di e ence me hod on a uni o m g id o size x=l/Nwi h N=100 on
he in e al I=(0,l) o disc e ize (57) in space o ob ain a sys em o o dina y di e en ial
equa ions (ODEs). To ob ain he snapsho s, he ODE sys em is in eg a ed in ime using
Ma lab’s command ode15s, which uses he nume ic di e en ia ion o mulae (NDF) [25],
wi h su icien ly small ole ances o he local e o s (below 10−12). The snapsho s we e
ob ained on a uni o m ( ime) g id o diame e 1/20. The ime de i a i es we e ob ained by
e alua ing he igh -hand-side o he sys em o ODEs.
As in [1], equa ion (36)
h,k(yi
)=min
u∈Uad (1−λh)
h,k(yi
+h (yi
,u)) +hg (yi
,u),i=1,...,ns,
was sol ed by ixed-poin i e a ion, he s opping c i e ium being ha wo consecu i e i e a es
di e in he maximum no m in less han a gi en ole ance TOL , ini ially se o TOL =
5×10−4. Fo he i s i e a e we choose a amily o cons an con ols ul,l=1,...,pand
a any poin o he mesh yi
(ini ial condi ion) we compu e he app oxima e solu ion o (32)
co esponding o his ini ial condi ion and con ol ul. Then, we compu e he alue o he
unc ional cos (33). Finally, he alue o he ini ial i e a e a yi
is he minimum be ween he
alues o he unc ional cos o l=1,...,p.
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19 Page 18 o 28 Jou nal o Scien i ic Compu ing (2025) 103 :19
Once (36) is sol ed, he op imal con ol
u
h,k(yi
)=a gminu∈Uad (1−λh)
h,k(yi
+h (yi
,u)) +hg (yi
,u),(59)
is ob ained a any mesh poin yi
,i=1,...,ns. Then, he subop imal eedback ope a-
o  (y)is compu ed by in e pola ion. This means ha o y∈we p ojec on o he POD
space o ge P yand hen
P y=
ns

i=1
μiyi
,
(y)=
ns

i=1
μiu
h,k(yi
),
whe e he coe icien s μisa is y 0 ≤μi≤1, ns
i=1μi=1.
Wi h his, he closed-loop sys em
y( )= (y( ),  (y( ))), y(0)=y0,(60)
is in eg a ed, again, using he NDF o mulae as implemen ed in Ma lab’s command ode15s
wi h he same ole ances as in he compu a ion o he snapsho s. We will see below ha e y
di e en app oxima ions o he solu ion o (60) can be ob ained wi h di e en alues o he
ole ance TOL o he ixed-poin i e a ion sol ing (36)(seeFig.3), so ha we sol ed his
equa ion o dec easing alues o TOL , each one 5 imes smalle han he p e ious one
un il he ela i e e o be ween he solu ions o (60) co esponding o wo consecu i e alues
o TOL was below 10% (i usually u ned ou o d op d ama ically om abo e 10% o less
han 0.01%). He e and in he sequel, by he ela i e e o o a quan i y ˆywi h espec o y
we mean y−ˆy/max(|y|,10−3). Fo he op imal HJB s a es, o e e y alue o ime o
which he solu ion o (60) was compu ed, we compu ed he maximum o he ela i e e o s
o he componen s o y( ). Fo Tes 2 in Sec . 4.2, due o he discon inous ini ial da um, i
p o ed impossible o d i e he ela i e e o o wo op imal HJB s a es compu ed wi h wo
di e en ole ances TOL below 10%, so ha we checked ha he alue o he ela i e e o s
measu ed in he no m (63) below was smalle han 10%.
Wi h espec o he compu a ional cos o sol ing (59) by ixed-poin i e a ion, i is ob i-
ously p opo ional o he numbe o i e a ions. In he expe imen s below, hese alues we e
1382 o all alues o in Tes 1 below, 362, 263 and 242 o =2,3,4, espec i ely, in
Tes 2 below, and 365, 1103 and 1539 o =3,4,5 in Tes 3 in Sec . 4.3 below. On each
i e a ion, he bulk o he cos is inding he nonnega i e scala s μi
j,j=1,...,ns, such ha
yi
+h (yi
,u)=μi
1y1
+···+μi
nsyns
, which was 70% o he cos o he i e a ion o =5
in Tes 3 in Sec .4.3, 79% o =4 in Tes 2, and 95% o =4 in Tes 1 in Sec . 4.1,
ollowed by he cos o ob aining (yi
,u),i=1,...,ns, which was 4% o =4inTes s
1 and 2 below o 28% o =5 in Tes 3 in Sec .4.3. We no e ha cos o ob aining (yi
,u)
can be subs an ially diminished using app op ia e enso s o by means o echniques like
disc e e empi ical ine pola ion, which, o simplici y, we did no use in ou codes.
4.1 Tes 1: Semilinea Equa ion
As in [1], we conside (57) wi h γ=0andμ=1, a=1andb(x)=z0(x)=2x(1−x).
I is easy o check ha he uncon olled solu ion con e ges, as →∞ o a non-null s eady
s a e (see also [1, Fig. 6.1]), and ha he null solu ion is uns able.
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Jou nal o Scien i ic Compu ing (2025) 103 :19 Page 19 o 28 19
Fo he ini e-di e ence app oxima ion, we conside y:[0, e]→RN−1wi h componen s
yj( )≈z(xj, ),xj=jx,j=1,...,N−1, x=1/N, solu ion o
Cy =1
10 Ay +C(F(y)+uB)(61)
whe e he componen s o Fand Ba e, espec i ely Fj=yj(1−y2
j),Bj=2xj(1−xj),
j=1,...,N−1, and Aand Ca e (N−1)×(N−1) idiagonal ma ices ma ices gi en
by
A=1
(x)2
⎡
⎢
⎢
⎢
⎢
⎢
⎣
−21
1−21
.........
1−21
1−2
⎤
⎥
⎥
⎥
⎥
⎥
⎦
,C=1
12
⎡
⎢
⎢
⎢
⎢
⎢
⎣
10 1
1101
.........
1101
110
⎤
⎥
⎥
⎥
⎥
⎥
⎦
,(62)
so ha he ini e-di e ence disc e iza ion (61) is ou h-o de con e gen . The no m we
conside in RN−1is gi en by
y2=x
N−1

j=1
y2
j.(63)
Le as obse e ha his no m is an app oxima ion o he in eg al 1
0y(x)2dx o a unc ion
wi h alues yja he spa ial mesh nodes.
To compu e he snapsho s, as in [1], o cons an con ols u∈Usnap ={−1,0,1},we
ob ained he solu ions y(n)=y( n)o (61)e e y1/20 ime uni s, ha is, o n=n/20,
n=1,...20 e, and hen he ime de i a i es y(n)
we e compu ed om iden i y (61). Fo
he educed spaces, we conside he cases o POD basis wi h only =2,3 and 4 elemen s,
also as in [1]. The POD app oxima ion y was hen he mean o he snapsho s plus a linea
combina ion o he POD basis. The con ol se Uad is gi en by 41 con ols equally dis ibu ed
in [−1,1].
As in [1], o de ine he domain  , we compu e he p ojec ions o all he snapsho s. Wi h
his p ocedu e we ob ain a se o poin s in R . Then, we de ine an hype cube con aining his
se o poin s. The aim o his p ocedu e, in iew o Lemma 3, is ha he se  de ined in
his way sa is ies he in a iance condi ion
y +h (y ,u)∈ ,y ∈ ,u∈Uad.(64)
The se  o =4wasgi enby
 =[−0.87,0.41]×[−0.01,0.02]×[−0.01,0.01]×[−0.01,0.01].
Fo his se we checked ha condi ion (64) holds.
We no ice ha ou se  is conside able smalle han he co esponding se in [1](see
[1, 6.1. Tes 1]) whe e he au ho s use he s anda d euclidean no m in Rn a he han he
no m (63) we use he e. Since he domain is smalle we also conside pa i ions o  smalle
han hose in [1]. We ake maximum diame e k =0.01, and, as in [1], we choose h=0.1k .
In Fig. 1we ha e ep esen ed on op he op imal solu ion (le ) o =4, he di e ence
be ween op imal solu ion wi h 4 and 2 POD basis unc ions ( op middle) and he di e ence
be ween op imal solu ion wi h 4 and 3 POD basis unc ions ( op igh ). On bo om we ha e
ep esen ed he op imal con ols o =2, 3 and 4.
We obse e ha we ge much be e esul s han hose in [1], al hough (apa om using
a di e en se o snapsho s) in ou me hod, bo h he ini e-di e ence me hod and he ime
123
19 Page 20 o 28 Jou nal o Scien i ic Compu ing (2025) 103 :19
Fig. 1 Tes 1: Op imal HJB s a es compu ed wi h =4 POD basis unc ions ( op-le ), di e ence be ween
op imal solu ion wi h 4 and 2 POD basis unc ions ( op-middle), di e ence be ween op imal solu ion wi h 4
and 3 POD bases ( op- igh ). Op imal HJB con ols wi h =4,3,2 (bo om). The ed c osses co espond o
he alues o he con ols ha we ha e joined by a blue line
Fig. 2 Tes 1: Value o he cos
unc ional (58) on he op imal
HJB s a es o =2,3,4. The
ed c osses co espond o he
alues o he cos alues ha a e
joined by a pd line
Fig. 3 Tes 1: Rela i e e o be ween he op imal HJB s a es wi h =4 co esponding o sol ing (36)by
ixed poin i e a ion wi h ole ances TOL =5×10−4and TOL =1×10−4(le ), TOL =1×10−4
and TOL =2×10−5(cen e), and op imal HJB con ols ( igh )
in eg a o ha we use a e mo e accu a e han hose in [1]. We also no ice ha he e is li le
disc epancy be ween he alues o he op imal HJB s a es o he di e en alues o ha we
ied. We also compu ed he alues o he cos unc ional (58) on he op imal HJB s a es o
he h ee alues o . The alues a e shown in Fig. 2. I can be seen ha he alues dec ease
wi h and ha hey di e in he nin h signi ican digi .
As men ioned abo e he e can be a signi ican di e ence be ween he op imal HJB s a es
compu ed wi h solu ions ob ained by sol ing (36) wi h di e en ole ances TOL .InFig.3we
show he ela i e e o be ween he op imal HJB s a es co esponding o ole ances TOL =
5×10−4and TOL =1×10−4(le ), and be ween his one and ha co esponding o TOL =
2×10−5(cen e). The igh plo shows he co esponding op imal HJB con ols. Figu e 3
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Jou nal o Scien i ic Compu ing (2025) 103 :19 Page 21 o 28 19
Table 1 Rela i e e o s o he
op imal HJB s a es and con ols
o =3 compu ed
wi h x=1/N,N=25
and N=50, wi h espec o
hose compu ed wi h N=100
Ny Ra e  (y) a e
25 7.24 ×10−51.99 ×10−5
50 4.25 ×10−64.09 1.17 ×10−64.09
Fig. 4 Tes 1: Resul s o di e en alues o k ; ela i e e o s be ween HJB s a es ( op le ) and con ols
(bo om le ) wi h espec o o k =0.005; HBJ con ols (cen e) and alues o he cos unc ional (58) ( igh )
shows he impo ance o sol ing (36) accu a ely in o de o ob ain good op imal HJB s a es,
hus, jus i ying ha we compu ed he (app oxima ions o he) solu ion o (36) wi h dec easing
alues o TOL un il he ela i e e o o he co esponding op imal HJB es a es was below
10%.
Following he sugges ion o one o he e iewe s, we checked i he op imal con ol
compu ed wi h x=1/100 s abilizes he same PDE compu ed on ine meshes. We ied
his o =4andx=1/400 and 1/800, and he con olled solu ions con e ged o ze o as
as as in he case x=1/100. Gi en he accu acy wi h which we had compu ed he con ols
o x=1/100 and he accu acy o he disc e iza ion i sel , we did no expec o he wise.
The esul s abo e sugges ha , o his p oblem, i is enough wi h =3. Fo his alue
o we now check he e ec o he ini e-di e ence mesh in he op imal HJB s a es. In
Table 1we show he ela i e e o s o he op imal HJB s a es compu ed wi h N=25
and N=50 wi h espec o ha compu ed wi h N=100, as well as he ela i e e o s o
he co esponding con ols. Fo he con ols, we show in Table 1 he maximum o all alues
o ∈{0,0.05,0.1,...,3}o he ela i e e o s, and o he s a es we show he maximum
on hesame alueso o he maximum o he ela i e e o s o he s a e on all he alues
o he co esponding spa ial g id. They con i m ha he ini e-di e ence disc e iza ion is o
o de 4. Due o he excellen accu acy ob ained wi h x=1/50, he esul s ha ollow a e
done wi h ha alue o x.
We now check he e ec o di e en alues k o he diame e o he pa i ion o  .Todo
his, we compa e he esul s ob ained wi h =3, x=1/50 and k =0.02,0.01,0.005. In
o de no o spoil he be e accu acy ob ained wi h he smalle alue o k we ook Uad wi h
161 con ols equally dis ibu ed in [−1,1] o k =0.005, and, o simpli y compu a ions wi h
only 11 con ols o k =0.02 (we also y wi h 21 and 41 con ols, bu , al hough we do no
ha e a p esen an explana ion o i , using only 11 con ols wi h k =0.02 ga e somewha
be e esul s). The esul s can be seen in Fig. 4. The plo s on he le show he (maximum
o he 51 poin s o he spa ial g id o he) ela i e e o s o he op imal HJB s a es ( op) and
hei con ols (bo om) o k =0.02 and k =0.01 wi h espec o hose o k =0.005,
while he plo in he cen e shows he HJB con ols. The e o s, as expec ed, a e smalle
o k =0.01 han o k =0.02, excep o he con ols o ∈[1.8,2.55]whe e hey
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19 Page 22 o 28 Jou nal o Scien i ic Compu ing (2025) 103 :19
Fig. 5 Tes 1: Resul s o POD basis ex ac ed om snapsho s (x=1/50, =3); Rela i e e o s o HJB
s a e (le ) and con ol (cen e) wi h espec o he case whe e POD basis is aken om ime de i a i es; HBJ
con ol ( igh )
a e sligh ly la ge . We also no ice ha , o k =0.01, he ela i e e o s emain below 10%
excep o ∈[1.5.2.2](whe e hey emain below 18%) in he case o he e o s in he
op imal HJB s a es and ∈[1.8,3] o he con ols. No ice, howe e , ha he la ges e o s
ake place whe e bo h he s a es and he con ols a e close o ze o ( ecall he plo s in Fig. 1),
we e i is di icul o ob ain small ela i e e o s. Maybe his is he eason o he simila
alues o he cos unc ional (58) o he h ee alues o k , which a e shown on he igh plo
in Fig. 4; he ela i e e o s (wi h espec o k =0.005) o k =0.02 and k =0.01 a e
0.081% and 0.0023%, espec i ely.
One may wonde wha is he esul i he snapsho s a e used o ob ain he POD basis as in
[1] ins ead o he ime de i a i es as in he p esen pape . Thus, we epea ed ou compu a ions
bu eplacing he ime de i a i es by he snapsho s minus hei mean. We did no ind any
signi ican di e ence. In Fig. 5we show he esul s co esponding o x=1/50, =3, he
se  being
 =(−0.42,0.9)×(−0.01,0.02)×(−0.01,0.01).
The op imal HJB con ol is shown on he igh -plo , while he o he wo plo s show he
ela i e e o s o he HJB s a e (le ) and i s con ol (cen e) wi h espec o he esul s when
he POD basis is aken om he ime de i a i es, =3andx=1/100. We see ha he
ela i e e o s a e below 0.1%, and hus, no di e ence can be seen be ween he igh -plo
in Fig. 5and he cen e plo in Fig. 1. We also no ice ha ou esul s when he POD basis is
aken om he snapsho s a e be e han hose in [1]. We belie e ha his is due o he highe
accu acy o ou compu a ions ( ou h-o de con e gen ini e-di e ence me hod ins ead o a
second-o de con e gen one, NDF wi h small ole ances o compu e he snapsho s ins ead
o implici Eule me hod, dense se s Uad o he con ol a iable, smalle ole ance TOL in
he ixed poin me hod o sol e (36), e c).
The ac ha e y simila esul s a e ob ained when he POD basis is aken om he
snapsho s o he ime de i a i es should no be su p ising. As shown in [18], we he be e
esul s a e ob ained i he POD basis is ex ac ed om he snapsho s o om hei di e ence
quo ien s is case-dependen and, as shown in [16], e y simila esul s a e usually ob ained
when he POD basis is aken om he ime de i a i es o he snapsho s di e ence quo ien s.
The ad an age o using ime de i a i es o di e ence quo ien s o he POD basis is mo e om
he heo e ical side, since i allows o p o e op imal con e gence o he POD me hods wi h
less assump ions han when he POD basis is ex ac ed om he snapsho s. Mo e ecen ly,
in [17], i has been p o ed ha using only snapsho s o he POD basis, i is possible o
p o e e o es ima es o he co esponding POD me hods wi h con e gence a es as close
o op imal as he smoo hness o he solu ion om whe e he snapsho s a e aken allows. In
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Jou nal o Scien i ic Compu ing (2025) 103 :19 Page 23 o 28 19
iew o he ecen esul s in [17], he analysis in he p esen pape can be easily adap ed o
co e also he case whe e POD basis is aken om he snapsho s.
4.2 Tes 2: Ad ec ion–Di usion Equa ion
As in [1], we now conside (57) wi h γ=1andμ=0, I=(0,2)and z0(x)=
max(0,0.5sin(π x)).We akebas he cha ac e is ic unc ion o he in e al (1/2,1).To
compu e he POD basis we compu e he ime de i a i es o he s a es o cons an con ols
u=−2.2,−1.1,0. The semidisc e iza ion was done wi h a s anda d ini e di e ence me hod
dyj
d =yj+1−2yj+yj−1
10(x)2−yj+1−yj−1
2x+b(xj), j=1,...,N−1,y0=yN=0,
which is second o de con e gen in p oblems wi h su icien ly smoo h solu ions.
Since he ini ial s a e z0does no possess second-o de de i a i es in L2, we no ice hen ha
he ime de i a i e z blows up when →0. Fo his eason, a e he spa ial disc e iza ion by
ini e di e ences, we eplaced he ime de i a i e a =0 by he di e ence quo ien (y(1)−
y(0))/ o s a es a =0and = . Pe haps also o lack bounded ime de i a i es
a =0 and he mo e dissipa i e na u e o he implici Eule me hod, we ound ha , in
he compu a ion o he op imal HBJ s a es and con ols, be e esul s we e ob ained i he
implici Eule me hod wi h  =1/20 was used ins ead o he NDF wi h small ole ances.
Also, o easons ha we do no unde s and a p esen , we ound ha be e esul s we e
ob ained when he POD app oxima ion was a linea combina ion o he POD basis plus he
ini ial condi ion y0, ins ead o a linea combina ion o he POD basis plus he mean as in he
p e ious sec ion.
In he p e ious es we had an in a iance se so ha we did no need o impose any
bounda y condi ion o sol ing (36). In his es we ound i impossible o ind a se 
sa is ying condi ion (64) bo h when he POD basis is aken om he s a es and om hei
ime de i a i es. In his las case he se  o =4 we used in he expe imen s was
 =(−0.5,0.7)×(−0.3,1.5)×(−0.3,0.2)×(−0.05,0.15).
To o e come he lack o in a iance o his se , whene e o a e ex yi
we had yi
+
h (yi
,u)/∈ , we simply eplaced yi
+h (yi
,u)by i s closes poin on ∂ .This
esul ed in changing he alue o yi
+h (yi
,u)in less han 2% in he i s wo coo dina es
in he POD basis and 15% in he emaining ones, excep o some nega i e alues o he
ou h coo dina e whe e e o s up o 60% we e encoun e ed. Fo example, an e o o 15%
in he hi d coo dina e means ha o some alues o yi
+h (yi
,u) he hi d coo dina e
could be in he se [−0.345,0.23]ins ead o [−0.3,0.2]. Ne e heless, as we will see below,
he esul s ob ained wi h he POD app oxima ion in his es we e excellen .
Since his p oblem is linea -quad a ic, he solu ion o HJB equa ion can be compu ed by
sol ing Ricca i equa ion. In Fig. 6we show he uncon olled solu ion (le ), he op imal LQR
s a e (middle) and he op imal LQR con ol ( igh ).
In Fig.7we ha e ep esen ed on op he op imal solu ion (le ) o =4, he di e ence
be ween op imal solu ion wi h 4 and 2 POD basis unc ions ( op middle) and he di e ence
be ween op imal solu ion wi h 4 and 3 POD basis unc ions ( op igh ). On he bo om pa we
ha e ep esen ed he op imal con ols o =2, 3 and 4. Also in his case, he imp o emen
wi h espec o he esul s in [1] is ema kable. In pa icula , he op imal con ols in Fig.7
compa e e y well wi h he op imal LQR con ol o Fig.6e en o he case wi h only =2
basis unc ions in ou POD me hod.
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19 Page 24 o 28 Jou nal o Scien i ic Compu ing (2025) 103 :19
Fig. 6 Tes 2: Uncon olled solu ion (le ), he op imal LQR s a e (middle) and he op imal LQR con ol ( igh )
Fig. 7 Tes 2: Op imal HJB s a es compu ed wi h =4 POD basis unc ions ( op-le ), di e ence be ween
op imal solu ion wi h 4 and 2 POD basis unc ions ( op middle), di e ence be ween op imal solu ion wi h 4
and 3 POD basis unc ions ( op- igh ). Op imal HJB con ols wi h =4,3,2 (bo om)
To conclude, in Fig. 8(le ) we show he di e ence be ween he op imal LQR s a e and
he op imal HJB s a e compu ed wi h =4 POD basis unc ions. On he igh , we show he
ela i e e o s uHJB −uLQR/max(10−3,uLQR)o he op imal HJB con ols wi h espec
o he op imal LQR con ol o =2,3 and 4. I can be seen a e y good ag eemen be ween
HJB and LQR op imal s a es. Wi h espec o he op imal con ols, we no ice ha whe eas
wi h =3and =4 POD basis unc ions he e o s do no exceed 30% and, indeed, hey
s ay below 10% mos o he ime, his is no he case o =2 POD basis unc ions, whe e
e o s a e abo e 100% o mo e han hal he ime in e al. Howe e , le us obse e ha we
a e conside ing ela i e e o s on he igh o Fig.8and ha es ic ing ou sel es o he ime
in e al in which he op imal con ol is su icien ly away om ze o he e o s o =2a e
also below 35%.
Again, he esul s he e (which co espond o k =0.1) compa e a ou ably wi h hose in
he li e a u e. As in he p e iouis es , we checked o =4 i he op imal con ol compu ed
wi h x=1/100 s abilizes he same PDE disc e ized wi h =1/400 and 1/800 wi h
simila esul s as in he p e ious sec ion.
4.3 Tes 3: A Two-Dimensional Reac ion–Di usion Equa ion
We ex end (57) o wo dimensions. In pa icula , we conside ,
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Jou nal o Scien i ic Compu ing (2025) 103 :19 Page 25 o 28 19
Fig. 8 Tes 2: ela i e e o s uHJB −uLQR/max(10−3,uLQR)o he op imal HJB con ols wi h espec
o he op imal LQR con ol (le ) and di e ence be ween he op imal LQR s a e and he op imal HJB s a e
compu ed wi h =4 POD basis unc ions ( igh )
Fig. 9 Tes 3: Uncon olled solu ion a =0,1.5,3
z −εz+(z3−z)=ub in ×(0, e),
z(·,0)=z0in ,
z(·, )=0in∂ ×(0, e),
(65)
wi h ε=1/10, =[0,1]×[0,1]and z:×[0, e]deno es he s a e. The con ol u
belongs o Uad =L2(0, e,[ua,ub]), wi h ua=−1andub=1. The cos unc ion is as (58)
bu wi h he s a e measu ed in L2() ins ead o L2(I), ha is
 e
0
e−λ z(·, ,u)2
L2() +1
100 |u( )|2d ,
wi h λ=1 as be o e. Simila ly o Sec .4.1,we akeb(x,y)=z0(x,y)=4x(1−x)y(1−y)
and e=3. In Fig. 9we show he uncon olled solu ion a he ini ial ime, a = e/2
and = e.
Fo he ini e-di e ence app oxima ion, we conside y:[0, e]→R(N−1)2wi h compo-
nen s yk( )≈z(xk, ),whe e, o k=(j−1)(N−1)+i,i,j=1,...,N−1, xk=(xi,yj),
and xi=ix,yj=jy,x=y=1/N, solu ion o
ˆ
Cy
=1
10 ˆ
Ay +ˆ
C(ˆ
F(y)+uˆ
B)(66)
whe e he componen s o ˆ
Fand ˆ
Ba e, espec i ely ˆ
Fk=yk(1−y2
k),ˆ
Bk=4xi(1−xi)yj(1−
yj),k=(j−1)(N−1)+i,i,j=1,...,N−1, and ˆ
Aand ˆ
Ca e (N−1)2×(N−1)2
ma ices gi en by ˆ
A=I⊗A+A⊗I,ˆ
C=I⊗C+C⊗I,whe eIis he iden i y o o de
N−1, ⊗ ep esen s he K onecke p oduc o ma ices, and Aand Ca e he ma ices in (62)
so ha , as in Sec .4.1, he ini e-di e ence disc e iza ion (66) is ou h-o de con e gen . The
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