Loading [MathJax]/jax/output/SVG/jax.js
Research article Special Issues

A stochastic linear-quadratic differential game with time-inconsistency

  • Received: 14 September 2021 Revised: 14 December 2021 Accepted: 07 February 2022 Published: 11 May 2022
  • We consider a general stochastic linear-quadratic differential game with time-inconsistency. The time-inconsistency arises from the presence of quadratic terms of the expected state as well as state-dependent term in the objective functionals. We define an equilibrium strategy, which is different from the classical one, and derive a sufficient condition for equilibrium strategies via a system of forward-backward stochastic differential equation. When the state is one-dimensional and the coefficients are all deterministic, we find an explicit equilibrium strategy. The uniqueness of such equilibrium strategy is also given.

    Citation: Qinglong Zhou, Gaofeng Zong. A stochastic linear-quadratic differential game with time-inconsistency[J]. Electronic Research Archive, 2022, 30(7): 2550-2567. doi: 10.3934/era.2022131

    Related Papers:

    [1] Patarawadee Prasertsang, Thongchai Botmart . Improvement of finite-time stability for delayed neural networks via a new Lyapunov-Krasovskii functional. AIMS Mathematics, 2021, 6(1): 998-1023. doi: 10.3934/math.2021060
    [2] Jenjira Thipcha, Presarin Tangsiridamrong, Thongchai Botmart, Boonyachat Meesuptong, M. Syed Ali, Pantiwa Srisilp, Kanit Mukdasai . Robust stability and passivity analysis for discrete-time neural networks with mixed time-varying delays via a new summation inequality. AIMS Mathematics, 2023, 8(2): 4973-5006. doi: 10.3934/math.2023249
    [3] Boonyachat Meesuptong, Peerapongpat Singkibud, Pantiwa Srisilp, Kanit Mukdasai . New delay-range-dependent exponential stability criterion and H performance for neutral-type nonlinear system with mixed time-varying delays. AIMS Mathematics, 2023, 8(1): 691-712. doi: 10.3934/math.2023033
    [4] Yonggwon Lee, Yeongjae Kim, Seunghoon Lee, Junmin Park, Ohmin Kwon . An improved reachable set estimation for time-delay linear systems with peak-bounded inputs and polytopic uncertainties via augmented zero equality approach. AIMS Mathematics, 2023, 8(3): 5816-5837. doi: 10.3934/math.2023293
    [5] Rupak Datta, Ramasamy Saravanakumar, Rajeeb Dey, Baby Bhattacharya . Further results on stability analysis of Takagi–Sugeno fuzzy time-delay systems via improved Lyapunov–Krasovskii functional. AIMS Mathematics, 2022, 7(9): 16464-16481. doi: 10.3934/math.2022901
    [6] Yude Ji, Xitong Ma, Luyao Wang, Yanqing Xing . Novel stability criterion for linear system with two additive time-varying delays using general integral inequalities. AIMS Mathematics, 2021, 6(8): 8667-8680. doi: 10.3934/math.2021504
    [7] Xingyue Liu, Kaibo Shi . Further results on stability analysis of time-varying delay systems via novel integral inequalities and improved Lyapunov-Krasovskii functionals. AIMS Mathematics, 2022, 7(2): 1873-1895. doi: 10.3934/math.2022108
    [8] Xiao Ge, Xinzuo Ma, Yuanyuan Zhang, Han Xue, Seakweng Vong . Stability analysis of systems with additive time-varying delays via new bivariate quadratic reciprocally convex inequality. AIMS Mathematics, 2024, 9(12): 36273-36292. doi: 10.3934/math.20241721
    [9] Huahai Qiu, Li Wan, Zhigang Zhou, Qunjiao Zhang, Qinghua Zhou . Global exponential periodicity of nonlinear neural networks with multiple time-varying delays. AIMS Mathematics, 2023, 8(5): 12472-12485. doi: 10.3934/math.2023626
    [10] Wentao Le, Yucai Ding, Wenqing Wu, Hui Liu . New stability criteria for semi-Markov jump linear systems with time-varying delays. AIMS Mathematics, 2021, 6(5): 4447-4462. doi: 10.3934/math.2021263
  • We consider a general stochastic linear-quadratic differential game with time-inconsistency. The time-inconsistency arises from the presence of quadratic terms of the expected state as well as state-dependent term in the objective functionals. We define an equilibrium strategy, which is different from the classical one, and derive a sufficient condition for equilibrium strategies via a system of forward-backward stochastic differential equation. When the state is one-dimensional and the coefficients are all deterministic, we find an explicit equilibrium strategy. The uniqueness of such equilibrium strategy is also given.



    Over the last two decades, many researches used LKF method to get stability results for time-delay systems [1,2]. The LKF method has two important technical steps to reduce the conservatism of the stability conditions. The one is how to construct an appropriate LKF, and the other is how to estimate the derivative of the given LKF. For the first one, several types of LKF are introduced, such as integral delay partitioning method based on LKF [3], the simple LKF [4,5], delay partitioning based LKF [6], polynomial-type LKF [7], the augmented LKF [8,9,10]. The augmented LKF provides more freedom than the simple LKF in the stability criteria because of introducing several extra matrices. The delay partitioning based LKF method can obtain less conservative results due to introduce several extra matrices and state vectors. For the second step, several integral inequalities have been widely used, such as Jensen inequality [11,12,13,14], Wirtinger inequality [15,16], free-matrix-based integral inequality [17], Bessel-Legendre inequalities [18] and the further improvement of Jensen inequality [19,20,21,22,23,24,25]. The further improvement of Jensen inequality [22] is less conservative than other inequalities. However, The interaction between the delay partitioning method and the further improvement of Jensen inequality [23] was not considered fully, which may increase conservatism. Thus, there exists room for further improvement.

    This paper further researches the stability of distributed time-delay systems and aims to obtain upper bounds of time-delay. A new LKF is introduced via the delay partitioning method. Then, a less conservative stability criterion is obtained by using the further improvement of Jensen inequality [22]. Finally, an example is provided to show the advantage of our stability criterion. The contributions of our paper are as follows:

    The integral inequality in [23] is more general than previous integral inequality. For r=0,1,2,3, the integral inequality in [23] includes those in [12,15,21,22] as special cases, respectively.

    An augmented LKF which contains general multiple integral terms is introduced to reduce the conservatism via a generalized delay partitioning approach. For example, the tt1mhx(s)ds, tt1mhtu1x(s)dsdu1, , tt1mhtu1tuN1x(s)dsduN1du1 are added as state vectors in the LKF, which may reduce the conservatism.

    In this paper, a new LKF is introduced based on the delay interval [0,h] is divided into m segments equally. From the LKF, we can conclude that the relationship among x(s), x(s1mh) and x(sm1mh) is considered fully, which may yield less conservative results.

    Notation: Throughout this paper, Rm denotes m-dimensional Euclidean space, A denotes the transpose of the A matrix, 0 denotes a zero matrix with appropriate dimensions.

    Consider the following time-delay system:

    ˙x(t)=Ax(t)+B1x(th)+B2tthx(s)ds, (2.1)
    x(t)=Φ(t),t[h,0], (2.2)

    where x(t)Rn is the state vector, A,B1,B2Rn×n are constant matrices. h>0 is a constant time-delay and Φ(t) is initial condition.

    Lemma2.1. [23] For any matrix R>0 and a differentiable function x(s),s[a,b], the following inequality holds:

    ba˙xT(s)R˙x(s)dsrn=0ρnbaΦn(a,b)TRΦn(a,b), (2.3)

    where

    ρn=(nk=0cn,kn+k+1)1,
    cn,k={1,k=n,n0,n1t=kf(n,t)ct,k,k=0,1,n1,n1,
    Φl(a,b)={x(b)x(a),l=0,lk=0cl,kx(b)cl,0x(a)lk=1cl,kk!(ba)kφk(a,b)x(t),l1,
    f(l,t)=tj=0ct,jl+j+1/tj=0ct,jt+j+1,
    φk(a,b)x(t)={bax(s)ds,k=1,babs1bsk1x(sk)dskds2dss1,k>1.

    Remark2.1. The integral inequality in Lemma 2.1 is more general than previous integral inequality. For r=0,1,2,3, the integral inequality (2.3) includes those in [12,15,21,22] as special cases, respectively.

    Theorem3.1. For given integers m>0,N>0, scalar h>0, system (2.1) is asymptotically stable, if there exist matrices P>0, Q>0, Ri>0,i=1,2,,m, such that

    Ψ=ξT1Pξ2+ξT2Pξ1+ξT3Qξ3ξT4Qξ4+mi=1(hm)2ATdRiAdmi=1rn=0ρnωn(timh,ti1mh)Ri×ωn(timh,ti1mh)<0, (3.1)

    where

    ξ1=[eT1ˉET0ˉET1ˉET2ˉETN]T,
    ξ2=[ATdET0ET1ET2ETN]T,
    ξ3=[eT1eT2eTm]T,
    ξ4=[eT2eT3eTm+1]T,
    ˉE0=hm[eT2eT3eTm+1]T,
    ˉEi=hm[eTim+2eTim+3eTim+m+1]T,i=1,2,,N,
    Ei=hm[eT1eTim+2eT2eTim+3eTmeTm(i+1)+1]T,i=0,1,2,,N,
    Ad=Ae1+B1em+1+B2mi=0em+1+i,
    ωn(timh,ti1mh)={eiei+i,n=0,nk=0cn,keicn,0ei+1nk=1cn,kk!e(k1)m+k+1,n1,
    ei=[0n×(i1)nIn×n0n×(Nm+1i)]T,i=1,2,,Nm+1.

    Proof. Let an integer m>0, [0,h] can be decomposed into m segments equally, i.e., [0,h]=mi=1[i1mh,imh]. The system (2.1) is transformed into

    ˙x(t)=Ax(t)+B1x(th)+B2mi=1ti1mhtimhx(s)ds. (3.2)

    Then, a new LKF is introduced as follows:

    V(xt)=ηT(t)Pη(t)+tthmγT(s)Qγ(s)ds+mi=1hmi1mhimhtt+v˙xT(s)Ri˙x(s)dsdv, (3.3)

    where

    η(t)=[xT(t)γT1(t)γT2(t)γTN(t)]T,
    γ1(t)=[tt1mhx(s)dst1mht2mhx(s)dstm1mhthx(s)ds],γ2(t)=mh[tt1mhtu1x(s)dsdu1t1mht2mht1mhu1x(s)dsdu1tm1mhthtm1mhu1x(s)dsdu1],,
    γN(t)=(mh)N1×[tt1mhtu1tuN1x(s)dsduN1du1t1mht2mht1mhu1t1mhuN1x(s)dsduN1du1tm1mhthtm1mhu1tm1mhuN1x(s)dsduN1du1],
    γ(s)=[x(s)x(s1mh)x(sm1mh)].

    The derivative of V(xt) is given by

    ˙V(xt)=2ηT(t)P˙η(t)+γT(t)Qγ(t)γT(thm)Qx(thm)+mi=1(hm)2˙xT(t)Ri˙x(t)mi=1hmti1mhtimh˙xT(s)Ri˙x(s)ds.

    Then, one can obtain

    ˙V(xt)=ϕT(t){ξT1Pξ2+ξT2Pξ1+ξT3Qξ3ξT4Qξ4+mi=1(hm)2ATdRiAd}ϕ(t)mi=1hmti1mhtimh˙xT(s)Ri˙x(s)ds, (3.4)
    ϕ(t)=[xT(t)γT0(t)γT1(t)γTN(t)]T,
    γ0(t)=[xT(t1mh)xT(t2mh)xT(th)]T.

    By Lemma 2.1, one can obtain

    hmti1mhtimh˙xT(s)Ri˙x(s)dsrl=0ρlωl(timh,ti1mh)Ri×ωl(timh,ti1mh). (3.5)

    Thus, we have ˙V(xt)ϕT(t)Ψϕ(t) by (3.4) and (3.5). We complete the proof.

    Remark3.1. An augmented LKF which contains general multiple integral terms is introduced to reduce the conservatism via a generalized delay partitioning approach. For example, the tt1mhx(s)ds, tt1mhtu1x(s)dsdu1, , tt1mhtu1tuN1x(s)dsduN1du1 are added as state vectors in the LKF, which may reduce the conservatism.

    Remark3.2. For r=0,1,2,3, the integral inequality (3.5) includes those in [12,15,21,22] as special cases, respectively. This may yield less conservative results. It is worth noting that the number of variables in our result is less than that in [23].

    Remark3.3. Let B2=0, the system (2.1) can reduces to system (1) with N=1 in [23]. For m=1, the LKF in this paper can reduces to LKF in [23]. So the LKF in our paper is more general than that in [23].

    This section gives a numerical example to test merits of our criterion.

    Example 4.1. Consider system (2.1) with m=2,N=3 and

    A=[011001],B1=[0.00.10.10.2],B2=[0000].

    Table 1 lists upper bounds of h by our methods and other methods in [15,20,21,22,23]. Table 1 shows that our method is more effective than those in [15,20,21,22,23]. It is worth noting that the number of variables in our result is less than that in [23]. Furthermore, let h=1.141 and x(0)=[0.2,0.2]T, the state responses of system (1) are given in Figure 1. Figure 1 shows the system (2.1) is stable.

    Table 1.  hmax for different methods.
    Methods hmax NoDv
    [15] 0.126 16
    [20] 0.577 75
    [21] 0.675 45
    [22] 0.728 45
    [23] 0.752 84
    Theorem 3.1 1.141 71
    Theoretical maximal value 1.463

     | Show Table
    DownLoad: CSV
    Figure 1.  The state trajectories of the system (2.1) of Example 4.1.

    In this paper, a new LKF is introduced via the delay partitioning method. Then, a less conservative stability criterion is obtained by using the further improvement of Jensen inequality. Finally, an example is provided to show the advantage of our stability criterion.

    This work was supported by Basic Research Program of Guizhou Province (Qian Ke He JiChu[2021]YiBan 005); New Academic Talents and Innovation Program of Guizhou Province (Qian Ke He Pingtai Rencai[2017]5727-19); Project of Youth Science and Technology Talents of Guizhou Province (Qian Jiao He KY Zi[2020]095).

    The authors declare that there are no conflicts of interest.



    [1] R. H. Stroz, Myopia and inconsistency in dynamic utility maximization, Rev. Econ. Stud., 23 (1955), 165–180. https://doi.org/2295722
    [2] E. Phelps, R. A. Pollak, On second-best national saving and game-equilibrium growth, Rev. Econ. Stud., 35 (1968), 185–199. https://doi.org/2296547
    [3] E. Phelps, The indeterminacy of game-equilibrium growth, in Altruism, Morality and Economic theory, Russell Sage Foundation, NewYork, 1975, 87–105.
    [4] P. Krusell, A. Smith, Consumption-savings decisions with quasi-geometric discounting, Econometrica, 71 (2003), 365–375. https://doi.org/10.1111/1468-0262.00400 doi: 10.1111/1468-0262.00400
    [5] C. Harris, D. Laibson, Dynamic choices of hyperbolic consumers, Econometrica, 69 (2001), 935–957. https://doi.org/10.1111/1468-0262.00225 doi: 10.1111/1468-0262.00225
    [6] L. Karp, Non-constant discounting in continuous time, J. Econ. Theory, 132 (2007), 577–568. https://doi.org/10.1016/j.jet.2005.07.006 doi: 10.1016/j.jet.2005.07.006
    [7] L. Karp, I. H. Lee, Time-consistent policies, J. Econ. Theory, 112 (2003), 353–364. https://doi.org/10.1016/S0022-0531(03)00067-X
    [8] I. Ekeland, From ramsey to thom: a classical problem in the calculus of variations leading to an implicit differential equation, Discrete and Continuous Dynamical Systems, 28 (2010), 1101–1119. https://doi.org/10.3934/dcds.2010.28.1101 doi: 10.3934/dcds.2010.28.1101
    [9] I. Ekeland, A. Lazrak, Being serious about non-commitment: subgame perfect equilibrium in continuous time, arXiv: math/0604264.
    [10] I. Ekeland, A. Lazrak, Equlibrium policies when preferences are time-inconsistent, arXiv: math/0808.3790.
    [11] I. Ekeland, A. Lazrak, The golden rule when preferences are time-inconsistent, Math. Financial Econ., 4 (2010), 29–55. https://doi.org/10.1007/s11579-010-0034-x doi: 10.1007/s11579-010-0034-x
    [12] I. Ekeland, Y. Long, Q. Zhou, A new class of problems in the calculus of variations, Regul. Chaotic Dyn., 258 (2013), 553–584. https://doi.org/10.1134/S1560354713060014 doi: 10.1134/S1560354713060014
    [13] I. Ekeland, L. Karp, R. Sumaila, Equilibrium management of fisheries with overlapping altruistic generations, 2011. Available from: http://www.ceremade.dauphine.fr/~ekeland/Articles/Karp.pdf.
    [14] J. Yong, A deterministic linear quadratic time-inconsistent optimal control problems, Math. Control. Relat. Fields, 1 (2011), 83–118. https://doi.org/10.3934/mcrf.2011.1.83 doi: 10.3934/mcrf.2011.1.83
    [15] I. Ekeland, T. Pirvu, Investment and consumption without commitment, Math. Financial Econ., 2 (2008), 57–86. https://doi.org/10.1007/s11579-008-0014-6 doi: 10.1007/s11579-008-0014-6
    [16] S. R. Grendadier, N. Wang, Investment under uncertianty and time-inconsistent preferences, J. Financ. Econ., 84 (2007), 2–39. https://doi.org/10.1016/j.jfineco.2006.01.002 doi: 10.1016/j.jfineco.2006.01.002
    [17] T. Björk, A. Murgoci, A theorey of markovian time inconsistent stochastic control problem, Financ. Stoch., 18 (2014), 545–592. https://doi.org/10.1007/s00780-014-0234-y doi: 10.1007/s00780-014-0234-y
    [18] T. Björk, A. Murgoci, X. Zhou, Mean-variance portfolio optimization with state-dependent risk aversion, Math. Financ., 24 (2014), 1–24. https://doi.org/10.1111/j.1467-9965.2011.00515.x doi: 10.1111/j.1467-9965.2011.00515.x
    [19] S. Basak, G. Chabakauri, Dynamic mean-variance asset allocation, Rev. Econ. Stud., 23 (2010), 2970–3016. https://doi.org/10.1093/rfs/hhq028 doi: 10.1093/rfs/hhq028
    [20] Y. Hu, H. Jin, X. Zhou, Time-inconsistent stochastic linear-quadratic control, SIAM J. Control Optim., 50 (2012), 1548–1572. https://doi.org/10.1137/110853960 doi: 10.1137/110853960
    [21] Y. Hu, H. Jin, X. Zhou, Time-inconsistent stochastic linear–quadratic control: Characterization and uniqueness of equilibrium, SIAM J. Control Optim., 55 (2017), 1261–1279. https://doi.org/10.1137/15M1019040 doi: 10.1137/15M1019040
    [22] A. Bensoussan, K. C. J. Sung, S. C. P. Yam, Linear-quadratic time-inconsistent mean field games, Dyn. Games Appl., 3 (2013), 537–552. https://doi.org/10.1007/s13235-013-0090-y doi: 10.1007/s13235-013-0090-y
    [23] J. Martín-Solano, Group inefficiency in a common property resource game with asymmetric players, Econ. Lett., 136 (2015), 214–217. https://doi.org/10.1016/j.econlet.2015.10.002 doi: 10.1016/j.econlet.2015.10.002
    [24] X. Zhou, J. Yong, Stochastic controls: Hamiltonian Systems and HJB Equations, Springer-Verlag, NewYork, 1999.
    [25] S. Peng, A general stochastic maximm principle for optimal control problems, SIAM J. Control Optim., 28 (1990), 966–979. https://doi.org/10.1137/0328054 doi: 10.1137/0328054
  • This article has been cited by:

    1. Yanyan Sun, Xiaoting Bo, Wenyong Duan, Qun Lu, Stability analysis of load frequency control for power systems with interval time-varying delays, 2023, 10, 2296-598X, 10.3389/fenrg.2022.1008860
    2. Xiao Ge, Xinzuo Ma, Yuanyuan Zhang, Han Xue, Seakweng Vong, Stability analysis of systems with additive time-varying delays via new bivariate quadratic reciprocally convex inequality, 2024, 9, 2473-6988, 36273, 10.3934/math.20241721
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1869) PDF downloads(74) Cited by(1)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog