Research article

Optimal feedback control for a class of fed-batch fermentation processes using switched dynamical system approach

  • Received: 29 October 2021 Revised: 22 February 2022 Accepted: 28 February 2022 Published: 09 March 2022
  • This paper considers an optimal feedback control problem for a class of fed-batch fermentation processes. Our main contributions are as follows. Firstly, a dynamic optimization problem for fed-batch fermentation processes is modeled as an optimal control problem of switched dynamical systems, and a general state-feedback controller is designed for this dynamic optimization problem. Unlike the existing switched dynamical system optimal control problem, the state-dependent switching method is applied to design the switching rule, and the structure of this state-feedback controller is not restricted to a particular form. Then, this problem is transformed into a mixed-integer optimal control problem by introducing a discrete-valued function. Furthermore, each of these discrete variables is represented by using a set of 0-1 variables. By using a quadratic constraint, these 0-1 variables are relaxed such that they are continuous on the closed interval [0,1]. Accordingly, the original mixed-integer optimal control problem is transformed intoa nonlinear parameter optimization problem. Unlike the existing works, the constraint introduced for these 0-1 variables are at most quadratic. Thus, it does not increase the number of locally optimal solutions of the original problem. Next, an improved gradient-based algorithm is developed based on a novel search approach, and a large number of numerical experiments show that this novel search approach can effectively improve the convergence speed of this algorithm, when an iteration is trapped to a curved narrow valley bottom of the objective function. Finally, numerical results illustrate the effectiveness of this method developed by this paper.

    Citation: Xiang Wu, Yuzhou Hou, Kanjian Zhang. Optimal feedback control for a class of fed-batch fermentation processes using switched dynamical system approach[J]. AIMS Mathematics, 2022, 7(5): 9206-9231. doi: 10.3934/math.2022510

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  • This paper considers an optimal feedback control problem for a class of fed-batch fermentation processes. Our main contributions are as follows. Firstly, a dynamic optimization problem for fed-batch fermentation processes is modeled as an optimal control problem of switched dynamical systems, and a general state-feedback controller is designed for this dynamic optimization problem. Unlike the existing switched dynamical system optimal control problem, the state-dependent switching method is applied to design the switching rule, and the structure of this state-feedback controller is not restricted to a particular form. Then, this problem is transformed into a mixed-integer optimal control problem by introducing a discrete-valued function. Furthermore, each of these discrete variables is represented by using a set of 0-1 variables. By using a quadratic constraint, these 0-1 variables are relaxed such that they are continuous on the closed interval [0,1]. Accordingly, the original mixed-integer optimal control problem is transformed intoa nonlinear parameter optimization problem. Unlike the existing works, the constraint introduced for these 0-1 variables are at most quadratic. Thus, it does not increase the number of locally optimal solutions of the original problem. Next, an improved gradient-based algorithm is developed based on a novel search approach, and a large number of numerical experiments show that this novel search approach can effectively improve the convergence speed of this algorithm, when an iteration is trapped to a curved narrow valley bottom of the objective function. Finally, numerical results illustrate the effectiveness of this method developed by this paper.



    Finsler geometry extends the classical Riemannian geometry by considering more general metric structures. A very important class of Finsler metrics is known as (α,β)-metrics, which were introduced by M. Matsumoto in 1972. An (α,β)-metric can be expressed as F=αϕ(s), where α is a Riemannian metric and s=βα, β is a 1-form. Randers metric, Kropina metric, exponential metric, Matsumoto metric, and cubic metric are important classes of (α,β)-metric [9].

    To study the curvature characteristics is a central problem in Finsler geometry. The Ricci curvature and S-curvature are very important non-Riemannian quantities in the Finslerian manifold [2]. The Ricci curvature in Finsler geometry is a natural extension of the Ricci curvature in Riemannian geometry and is defined as the trace of the Riemann curvature [5]. The S-curvature is a mathematical quantity and measures the rate of change of volume form of a Finsler space along the geodesics. Recent studies in differential geometry, such as those on Ricci solitons and conformal structures, have highlighted the importance of Ricci-type curvatures in understanding the geometric flow and structure of manifolds [6,7,8]. In Finsler geometry, the study of curvature involves understanding the deviation from flatness. The projective Ricci curvature is one aspect of this analysis. The concept of projective Ricci curvature in Finsler geometry is introduced by X. Cheng [1] in 2017. Projective geometry deals with the properties that are invariant under projective transformations. The projective Ricci curvature measures the deviation of the Finsler metric from being projectively flat. Projective Ricci curvature has applications in various areas of mathematics and physics. It plays a crucial role in understanding the geometry of Finsler manifolds and connects to the problems in the calculus of variations, differential equations, and geometric optics.

    In 2020, H. Zhu [15] gave an expression of projective Ricci curvature for an (α,β)-metric. Later on, many geometers [4,12,13] have studied the geometric properties of projective Ricci curvature. In this article, we obtain the geometric properties and flatness condition of projective Ricci curvature for the cubic Finsler metric, which is defined as F=αϕ(s) with

    ϕ=(1+s)3, (1.1)

    i.e., F=(α+β)3α2. Cubic metric is Finsler metric for b2<14 [14].

    The following notations will be used to state our main result:

    2sjk=bj;kbk;j,2rjk=bj;k+bk;j,sjk=ajlskl,rjk=ajlrkl,sj=blslj=bkskj,rj=blrlj=bkrkj,rj0=rjkyk,r00=rjkyjyk,r=rjkbjbk=bjrj,sj0=sjkyk,s0=sjyj,r0=rjyj,bj=ajkbk,tjk=sjmsmk,tj=bmtmj=sisij, (1.2)

    where ";" denotes the covariant derivative with respect to the Levi-Civita connection of the Riemannian metric α.

    A 1-form β is said to be a Killing form if rij=0. The 1-form β is said to be a constant Killing form if it is a Killing form and constant length concerning α, equivalently rij=0 and si=0.

    In this paper we will use the following lemma:

    Lemma 1.1. If α2=0(modβ), that is, aijyiyj contains bi(x)yi as a factor, then the dimension is equal to two and b2 vanishes. In this case, we have δ=di(x)yi satisfying α2=βδ and dibi=2.

    We first prove the following result:

    Theorem 1.1. For the cubic Finsler metric F=(α+β)3α2 on an n-dimensional (n>2) Finsler manifold M, the S-curvature vanishes if and only if β is a constant Killing form.

    Next, we obtain the flatness condition for the projective Ricci curvature as

    Theorem 1.2. If the n-dimensional (n>2) Finsler space with cubic metric F=(α+β)3α2 is projective Ricci-flat (PRic=0), then β is parallel with respect to the Riemannian metric α.

    In view of the above result, we obtain

    Corollary 1.1. If the n-dimensional (n>2) Finsler space with cubic metric F=(α+β)3α2 is projective Ricci flat then, it vanishes the S-curvature. Therefore, the Riemannian metric of α is Ricci flat (Ricα=0).

    We also prove the following result:

    Theorem 1.3. The n-dimensional (n>2) Finsler space with cubic metric F=(α+β)3α2 is weak PRic-curvature if and only if it is a PRic-flat metric.

    Let F be an n-dimensional Finsler manifold, and let Gj be the geodesic coefficients of F, which are defined as

    Gj=14gjl[2(F2)xkylyk(F2)xl],yϵTxM.

    The geodesic coefficients of an (α,β)-metric are given as [3]

    Gj=Gjα+αQsj0+(r002αQs0)(Ψbj+Θyjα), (2.1)

    where Giα denotes the geodesic coefficients of the Riemannian metric α and

    Q=ϕϕsϕ,ψ=ϕ"2ϕ(ϕsϕ+(Bs2)ϕ"),Θ=ϕϕs(ϕϕ"+ϕϕ)2ϕ(ϕsϕ+(Bs2)ϕ"). (2.2)

    For any xϵM and yϵTxM{0}, the Riemann curvature Ry is defined as

    Ry(v)=Rjk(y)vkxj,v=vjxj,

    where

    Rjk=2Gjxk+2Gi2Gjyiyk2GjxiykyiGjyiGiyk.

    The trace of Riemann curvature is called Ricci curvature Ric=Rmm, which is a mathematical object that regulates the rate at which a metric ball's volume in a manifold grows. A Finsler metric F is called an Einstein metric if Ricci curvature satisfies the equation Ric(x,y)=(n1)γF2, where γ=γ(x) is a scalar function.

    In 1997, Z. Shen [11] discussed S-curvature, which measures the average rate of change of (TxM;Fx) in the direction yϵTxM and is defined as

    S(x,y)=Gmymym(logσF)xm,

    where σF is defined as

    σF=Vol(Bn)Vol{yiϵRn|F(x,y)<1},

    and Vol denotes the Euclidean volume, and Bn(1) denotes the unit ball in Rn.

    The expression of S-curvature for an (α,β)-metric is given as [10]

    S=(s0+r0)(2ψΠ)α1Φ2Δ2(r002αQs0), (2.3)

    where

    Π=f(b)bf(b),Δ=1+sQ+(Bs2)Qs,B=b2,Φ=(QsQs)(nΔ+1+sQ)(Bs2)(1+sQ)Qss. (2.4)

    The projective Ricci curvature is first defined by X. Cheng [1] as

    PRic=Ric+n1n+1S|mym+n1(n+1)2S2, (2.5)

    where "|" denotes the horizontal covariant derivative with respect to the Berwald connections of F. A Finsler space F is called weak projective Ricci curvature if

    PRic=(n1)[3θF+γ]F2, (2.6)

    where γ=γ(x) is a scalar function and θ=θi(x)yi is a 1-form. If γ= constant, then F is called constant projective Ricci curvature. If θ=0, then F is called isotropic projective Ricci curvature PRic = (n1)γF2.

    In 2020, H. Zhu [15] gave an expression of the projective Ricci curvature for the (α,β)-metrics as

    PRic=Ricα+1n+1[r200α2V1r00s0αV2r00r0αV3+r00|0αV4+s20V5+r00rV64r20V7+2r0s0V8]+(r00rii+r00|bbiri0|0r0iri0)V9+r0isi0V10+s0|0V11+s0isi0V12+αrs0V13+αsjsj0V14+α[4n+1risi02s0|b2riis0+3r0isi+bisi|0]V15+αsi0|iV16+α2sisiV17+α2sijsjiV18+r0|0V19+2(n1)n+1[Ψsα(r002αQs0)(Bs2)+2Ψ(r0+s0)]ρ0+(n1)[2Ψ(r002αQs0)ρb2αQρksk0+ρ20+ρ0|0], (2.7)

    where

    V1=4sΨs+(4ΨΨssΨ2s)(Bs2)22(Ψss+6sΨΨs)(Bs2)n2+1n+1Ψ2s(Bs2)2,V2=4[2Ψ(ΨQss+2QΨss+QsΨs)Q(Ψs)2](Bs2)2+4[2(QsQs)(Ψs)2(1+10sQ)ΨΨs2ΨQss2QΨssQsΨs+ΨBs](Bs2)+2Qss+8Ψs4QΨ+4sΨQs+20sQΨs+(n1)[4((Ψ)2QssQ(Ψs)2)(Bs2)2+4((QsQs)(Ψ)2)+Ψ(ΨsQss)(Bs2)+2s(QsΨ+QΨs)2QΨ+Qss]+8n+1Ψs[ΨQΨs(Bs2)](Bs2),V3=2Ψs2(3ΨΨsΨBs)(Bs2)(n1)(12Ψ(Bs2))Ψs+4n+1ΨΨs(Bs2),V4=2Ψs(Bs2),V5=(n1){4[2QΨ2QssΨ2(Qs)2Q2(Ψs)2](Bs2)2+4[2QΨ(QΨ2sQsΨQss+Ψs)+Ψ(Qs)2+QsΨB](Bs2)4QΨ(s2QΨ3sQs+2Q)+4sQ(QΨs+ΨB)+8QsΨ+2QQss(Qs)2+4ΨB}+4[4QΨ(ΨQss+QΨss+QsΨs)2(Qs)2Ψ2Q2(Ψs)2](Bs2)2+8[QΨ(4sQsΨ4sQΨs+2QΨ2QssΨs)+(Qs)2ΨQ2ΨssQQsΨs+QΨBs+QsΨB](Bs2)+24sQ2Ψs8QΨ(s2QΨ3sQs+2Q)+8sQΨB+4Ψ(Ψ+4Qs)+4QQss+16QΨs2(Qs)28n+1[ΨQΨs(Bs2)]2,
    V6=4[(n+1)ΨB+2(Ψ)2],V7=n2+n+2n+1Ψ2+2ΨB,V8=(n1)[2(2QsΨ2+2QΨΨs+QsΨB)(Bs2)+2sQ(2Ψ2+ΨB)2QΨs+2ΨB]+4[2QsΨ23QΨΨs+QΨBs+QsΨB](Bs2)+4sQ(2Ψ2+ΨB)+4Ψ2+4QΨs4ΨB8n+1Ψ[ΨQΨs(Bs2)],V9=2Ψ,V10=2[2QsΨ(Bs2)2sQΨΨ+Qs+4n+1QΨs(Bs2)],V11=2QsΨ(Bs2)+2Ψ(1+2Q)Qs+4n+1[QΨs(Bs2)Ψ],V12=2Qs2Q(QsQs),V13=8Q[ΨB+2n+1Ψ2],V14=2n+1Q[(n3)Ψ+4QΨs(Bs2)],V15=2QΨ,V16=2Q,V17=4Q2Ψ,V18=Q2,V19=2(n1)n+1Ψ,ρ=lnσασn+1,ρ0=ρxiyi. (2.8)

    For Eq (1.1), we obtain the following values:

    Q=312s,Qs=6(12s)2,Qss=24(12s)3,ψ=31+6Bs8s2,ψs=3+48s(1+6Bs8s2)2,ψss=18(3+16B+8s+64s2)(1+6Bs8s2)3,ψB=18(1+6Bs8s2)2,ψBs=36+576s(1+6Bs8s2)2,Θ=3(14s))2(1+6Bs8s2),Θs=9+72B48s+96s22(1+6Bs8s2)2,ΘB=9(1+4s)2(1+6Bs8s2)2,Δ=1+6Bs8s2(12s)2,Φ=(3(15s6s2+B(8+6n+8s24ns)+n(15s4s2+32s3)(12s)4. (3.1)

    By using Eqs (2.1) and (3.1), we obtain the spray coefficient Gj for the cubic metric as

    Gj=Gjα+12α(12s)(1+6Bs8s2)[(6+36B6s48s2)α2sj0+[18αs0(4s1)+3r00(16s+8s2)]yj6αbj[6s0+(2s1)r00]]. (3.2)

    In view of Eqs (2.5) and (3.1) and using Mathematica program, we obtain the S-curvature for the cubic Finsler metric as

    S=12(α2β)(α2+6Bα2αβ8β2)2[2r0(α2β)((1+6B)α2αβ8β2)[αβΠ8β2Π+α2(6+Π+6BΠ)]2s0[3α2((1+3n+6B(2+3n))α33(3+5n+8B(2+3n))α2β6(1+2n)αβ2+32(1+3n)β3)+(α2β)((1+6B)α2+αβ+8β2)2Π]+3r00(α2β)[(1+n+B(8+6n))α3(58B+5n+24Bn)α2β2(3+2n)αβ2+32nβ3]]. (3.3)

    Now, we are in the position to prove Theorem 1.1.

    Proof of Theorem 1.1. First we prove the converse part.

    Let us assume that β is a constant Killing form i.e., s0=0 and r00=0; putting this in Eq (3.3) vanishes the S-curvature.

    For the if part, let us take S=0; then Eq (3.3) becomes

    t0+t1α+t2α2+t3α3+t4α4+t5α5=0, (3.4)

    where

    t0=64β4(4βΠr0+4βΠs03nr00),t1=4β3(16βΠr016βΠs0+3(3+10n)r00),t2=(192β392β3Π384Bβ3Π)r0+(192β3576nβ392384Bβ3Π)s0+(12β248Bβ2+18nβ2+144Bnβ2)r00,t3=(72β2+22β2Π+144Bβ2Π)r0+(36β2+72nβ2+22β2Π+144Bβ2Π)s0+(21β24Bβ21nβ108Bnβ)r00,t4=(36β144Bβ+8βΠ+72BβΠ+144B2βΠ)r0+(54β288Bβ+90nβ+432Bnβ+8βΠ+72BβΠ+144B2βΠ)s0+(3+24B+3n+18Bn)r00,t5=(12+72B2Π24BΠ72B2Π)r0+(672B18n108Bn2Π24BΠ72B2Π)s0.

    Taking the rational and irrational parts of Eq (3.4), we obtain

    t0+α2(t2+α2t4)=0, (3.5)
    t1+α2(t3+α2t5)=0. (3.6)

    From Eqs (3.5) and (3.6), we can say that α2 will divide t0 as well as t1. In view of Lemma 1.1,α2 is coprime with β for n>2. Solving Eqs (3.5) and (3.6), we get, respectively,

    4βΠ(r0+s0)3nr00=γ1α2,forγ1=γ1(x),

    and

    16βΠ(r0+s0)3(10n+3)r00=γ2α2,forγ2=γ2(x).

    From the above equations, we obtain

    r00=cα2,and thenr0=cβ, (3.7)

    for some scalar function c=c(x) on M.

    Putting the above values in Eq (3.4) and simplifying, we get

    256Πβ5(cβ+s0)=α2(....),

    where (...) denotes the polynomial term in α and β. Here also α2 does not divide β5 and (cβ+s0). Therefore, cβ+s0=0. Differentiating it with respect to yi, we obtain cbi+si=0, which, on contracting by bi, gives c=0, implying s0=0 and r00=0. Which means β is a constant Killing form.

    This completes, the proof of Theorem 1.1.

    In this section we obtain the projective Ricci curvature for the aforesaid metric.

    Proof of Theorem 1.2. For this, we first obtain all the values of Eq (2.8) by using Eq (3.1) and the Mathematica program as

    V1=1(1+n)(16B+s+8s2)4[3(6B(6(1+n)+8(1+n)s+(36(37+n)n)s24(45+n(37+8n))s3256(4+n(3+n))s4)+s(4(1+n)92(1+n)s+92(1+n)s2+(238+n(241+3n))s3+32(23+n(20+3n))s4+256(14+n(11+3n))s5)+3B2(66+24s(1+32s)+(n+16ns)2+n(65+8s(1+64s))))],
    V2=1(1+n)(1+2s)(16B+s+8s2)4[6(5+192B+1224B26n+186Bn+1206B2nn218Bn254B2n26(3(5+6n+n2)+12B2(10+n+9n2)+B(16+41n+51n2))s+3(99104nn236B(125n+n2)+384B2(8+n+3n2))s2+2(508+675n+245n2+12B(244125n+105n2))s36(330+183n45n2+64B(70+23n+15n2))s496(3611n+23n2)s5+2048(8+3n+n2)s6)],
    V3=3(1+16s)(6B(3+5n)+n(2+2s26s2)+3(1+s4s2)n2(1+s+2s2))(1+n)(16B+s+8s2)3,
    V4=6(1+16s)(B+s2)(16B+s+8s2)2,
    V5=1(1+n)(1+2s)3(16B+s+8s2)4[36(67n+n2(63+n(82+35n))s+15(8+3n(3+n))s2+(849+n(1354+785n))s3(2562+n(2351+1123n))s46(398+495n+771n2)s5+64(45+n(7+100n))s6+2048(3+n(7+2n))s7216B3(1+n)2(1+8s)+9B2(74+9n(9+n)144s6n(47+37n)s+48(1+n(11+8n))s2+160(2+3n(5+n))s3)+6B(13+13n+2n2(70+n(109+89n))s+(151+55n(1+2n))s2+2(178+n(317+505n))s38(47+n(136+199n))s41024(1+n(5+n))s5))],
    V6=72n(1+6Bs8s2)2,V7=9(23n+n2)(1+n)(1+6Bs8s2)2,
    V8=1(1+n)(1+2s)(1+6Bs8s2)3[18(7+n(8+3n)33s+3n(4+3n)s+6(10+(75n)n)s2256(1+2n)s36B(1+n2n2+4(14+(23+n)n)s))],
    V9=61+6Bs8s2,
    V10=6(1+n+6B(3+n))+18(1+4B(15+n)+n)s+36(3+n)s296(11+n)s3(1+n)(1+2s)(16B+s+8s2)2,
    V11=12(1+3B3s60Bs3s2+64s3)(1+n)(1+2s)(16B+s+8s2)2,V12=6(18s)(1+2s)3,
    V13=432n(1+n)(1+2s)(16B+s+8s2)2, (4.1)
    V14=18(3+6Bn6Bn+3(3+4B(19+n)+n)s+6(1+n)s216(15+n)s3)(1+n)(1+2s)2(16B+s+8s2)2,
    V15=18(1+2s)(16B+s+8s2),V16=612s,
    V17=108(1+2s)2(16B+s+8s2),V18=9(1+2s)2,V19=6(1+n)(1+n)(1+6Bs8s2).

    Plugging all the values of the above Eq (4.1) into Eq (2.7) and simplifying by the using Mathematica program, we obtain the projective Ricci curvature for the aforesaid metric as

    PRic=1(1+n)2(α2β)3((1+6B)α2+αβ+8β2)4i=13i=0αiti,

    where

    t0=2048β9(3r200(14+n(11+3n))+8(1+n)β(3r00|0+2(1+n)Ricαβ)+8β(2(1+n)(1+n)2β(ρ20+ρ0|0))3(1+n2)ρ0r00),
    t1=256β8(3r200(145+n(112+33n))+4(1+n)β(57r00|0+32(1+n)Ricαβ)+4β(32(1+n)(1+n)2β(ρ20+ρ0|0))57(1+n2)ρ0r00),t13=9(1+6B)3(12sksk+sikski+6Bsikski)(1+n)2. (4.2)

    Next, we obtain the flatness condition under which the projective Ricci curvature vanishes.

    Let the projective Ricci curvature PRic=0, which implies U(α,β)=0, where

    U(α,β)=t0+αt1+α2t2+......+α13t13. (4.3)

    Using Mathematica, we can see that

    U(α,β)=14(67n+n2)(α2β)3(α+β)2(α+16β)2(r00(α2β)6s0α2)2mod[(1+6B)α2αβ8β2].

    Therefore

    (...)[(1+6B)α2αβ8β2])14(67n+n2)(α2β)3(α+β)2(α+16β)2(r00(α2β)6s0α2)2=0,

    where (....) are polynomial in α and β. As B<14, therefore ((1+6B)α2αβ8β2) does not divide (α2β)3 or (α+β)2 or (α+16β)2. Therefore ((1+6B)α2αβ8β2) will divide (r00(α2β)6s0α2)2; then ((1+6B)α2αβ8β2) will also divide (r00(α2β)6s0α2), i.e.,

    (r00(α2β)6s0α2)=(c1+αc0)((1+6B)α2αβ8β2),

    where c1 is a 1-form and c0 is a scalar. Taking the rational and irrational parts of the above equation, we obtain

    2βr006α2s0=c1α2(1+6B)8β2c1c0α2β, (4.4)

    and

    r00=c0α2(1+6B)βc18c0β2. (4.5)

    Solving the above equations, we get c1=85βc0, and then (4.5) gives

    r00=c0[α2(1+6B)325β2]. (4.6)

    Substituting the above values into Eq (4.4), we obtain

    (4B1)c0β+10s0=0. (4.7)

    Differentiating the above equation with respect to yi gives (4B1)c0bi+si=0, which, on contracting by bi, we obtain c0=0. Then from Eqs (4.6) and (4.7), we obtain

    r00=0,s0=0. (4.8)

    In view of (4.8), Eq (4.3) becomes

    3α2(2s0ksk0(α8β)+(3sikskiα2+2sk0;k(α2β))(α2β))+Ricα(α2β)3(n1)(α2β)2((α2β)ρ20+6α2sk0ρk(α2β)ρ0|0)=0,

    which can be rewritten as

    (α2β){6α2s0ksk0+9α4sikski6α2sk0;k(α2β)Ricα(α2β)2+(n1)(α2β)[6α2sk0ρk(α2β)ρ20(α2β)ρ0|0]}=36s0ksk0α2β.

    Since (α2β) does not divide α2 or β, therefore (α2β) will divide s0ksk0. Thus

    s0ksk0=(d1+αd0)(α2β),

    where d1 is a 1-form and d0 is a scalar. Taking the rational and irrational parts of the above equation and solving, we obtain

    s0ksk0=d0(α24β2). (4.9)

    If d00 then one can conclude by the above equation that α is not positive definite, which is not possible. Therefore, d0=0. This implies that

    sik=0, (4.10)

    i.e., β is closed. In view of Eqs (4.8) and (4.10), we obtain bi;k=0, then 1-form β is parallel with respect to α.

    This completes the proof of Theorem 1.2.

    Now, we obtain the condition for the weak projective Ricci curvature of a cubic Finsler metric.

    Proof of Theorem 1.3. Let F be a cubic Finsler metric with weak projective Ricci curvature. Then from Eq (2.6) we obtain

    (n1)[3θ(α+β)3α2+γ(α+β)6]=α4(1+n)2(α2β)3((1+6B)α2αβ8β2)4i=13i=0αiti. (4.11)

    For the cubic metric, we have B<14, which implies that α4 does not divide (α2β)3 or ((1+6B)α2αβ8β2)4 or 3θ(α+β)3α2. Consequently, it follows that α2 must divide γ(α+β)6. However, such division is only possible if γ=0. Combining this result with Eq (4.11), then we deduce that 3θ(α+β)3 is divided by α2. This is impossible unless θ=0. Then F reduces to a projective Ricci-flat metric.

    The converse is obvious. This completes the proof.

    Example 4.1. The Finsler metric 1|y|2(|y|+<a,y>)3 for a=constant is projectively Ricci flat.

    Projective Ricci curvature is a concept in differential geometry that generalizes the notion of Ricci curvature. It has various applications in the fields of general relativity, optimal transformation theory, complex geometry, Weyl geometry, Einstein metrics, and many more. In this article, we have proved that if the cubic metric F=(α+β)3α2 is projective Ricci flat (PRic=0), then β is parallel with respect to Riemannian metric α, and then from Eq (2.3), the S-curvature vanishes. Therefore, from Eq (2.5), we obtain that the Riemannian metric α is also Ricci-flat, which is Corollary 1.1.

    M. K. Gupta and S. Sharma wrote the framework and the original draft of this manuscript. Y. Li and Y. Xie reviewed and validated the manuscript. All authors have read and agreed to the final version of the manuscript.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    The authors declare no conflict of interest.



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