Loading [MathJax]/jax/element/mml/optable/GeneralPunctuation.js
Research article Special Issues

Stochastic linear quadratic optimal tracking control for discrete-time systems with delays based on Q-learning algorithm

  • Received: 13 December 2022 Revised: 13 February 2023 Accepted: 20 February 2023 Published: 27 February 2023
  • MSC : 93E20, 93C05, 93C41, 93C55

  • In this paper, a reinforcement Q-learning method based on value iteration (Ⅵ) is proposed for a class of model-free stochastic linear quadratic (SLQ) optimal tracking problem with time delay. Compared with the traditional reinforcement learning method, Q-learning method avoids the need for accurate system model. Firstly, the delay operator is introduced to construct a novel augmented system composed of the original system and the command generator. Secondly, the SLQ optimal tracking problem is transformed into a deterministic one by system transformation and the corresponding Q function of SLQ optimal tracking control is derived. Based on this, Q-learning algorithm is proposed and its convergence is proved. Finally, a simulation example shows the effectiveness of the proposed algorithm.

    Citation: Xufeng Tan, Yuan Li, Yang Liu. Stochastic linear quadratic optimal tracking control for discrete-time systems with delays based on Q-learning algorithm[J]. AIMS Mathematics, 2023, 8(5): 10249-10265. doi: 10.3934/math.2023519

    Related Papers:

    [1] Ali Ahmad, Humera Rashid, Hamdan Alshehri, Muhammad Kamran Jamil, Haitham Assiri . Randić energies in decision making for human trafficking by interval-valued T-spherical fuzzy Hamacher graphs. AIMS Mathematics, 2025, 10(4): 9697-9747. doi: 10.3934/math.2025446
    [2] Doaa Al-Sharoa . (α1, 2, β1, 2)-complex intuitionistic fuzzy subgroups and its algebraic structure. AIMS Mathematics, 2023, 8(4): 8082-8116. doi: 10.3934/math.2023409
    [3] Tahir Mahmood, Ubaid Ur Rehman, Muhammad Naeem . A novel approach towards Heronian mean operators in multiple attribute decision making under the environment of bipolar complex fuzzy information. AIMS Mathematics, 2023, 8(1): 1848-1870. doi: 10.3934/math.2023095
    [4] Jun Jiang, Junjie Lv, Muhammad Bilal Khan . Visual analysis of knowledge graph based on fuzzy sets in Chinese martial arts routines. AIMS Mathematics, 2023, 8(8): 18491-18511. doi: 10.3934/math.2023940
    [5] Tareq M. Al-shami, José Carlos R. Alcantud, Abdelwaheb Mhemdi . New generalization of fuzzy soft sets: (a,b)-Fuzzy soft sets. AIMS Mathematics, 2023, 8(2): 2995-3025. doi: 10.3934/math.2023155
    [6] Muhammad Qiyas, Muhammad Naeem, Saleem Abdullah, Neelam Khan . Decision support system based on complex T-Spherical fuzzy power aggregation operators. AIMS Mathematics, 2022, 7(9): 16171-16207. doi: 10.3934/math.2022884
    [7] Shichao Li, Zeeshan Ali, Peide Liu . Prioritized Hamy mean operators based on Dombi t-norm and t-conorm for the complex interval-valued Atanassov-Intuitionistic fuzzy sets and their applications in strategic decision-making problems. AIMS Mathematics, 2025, 10(3): 6589-6635. doi: 10.3934/math.2025302
    [8] Tahir Mahmood, Azam, Ubaid ur Rehman, Jabbar Ahmmad . Prioritization and selection of operating system by employing geometric aggregation operators based on Aczel-Alsina t-norm and t-conorm in the environment of bipolar complex fuzzy set. AIMS Mathematics, 2023, 8(10): 25220-25248. doi: 10.3934/math.20231286
    [9] Atiqe Ur Rahman, Muhammad Saeed, Mazin Abed Mohammed, Alaa S Al-Waisy, Seifedine Kadry, Jungeun Kim . An innovative fuzzy parameterized MADM approach to site selection for dam construction based on sv-complex neutrosophic hypersoft set. AIMS Mathematics, 2023, 8(2): 4907-4929. doi: 10.3934/math.2023245
    [10] Muhammad Arshad, Muhammad Saeed, Khuram Ali Khan, Nehad Ali Shah, Wajaree Weera, Jae Dong Chung . A robust MADM-approach to recruitment-based pattern recognition by using similarity measures of interval-valued fuzzy hypersoft set. AIMS Mathematics, 2023, 8(5): 12321-12341. doi: 10.3934/math.2023620
  • In this paper, a reinforcement Q-learning method based on value iteration (Ⅵ) is proposed for a class of model-free stochastic linear quadratic (SLQ) optimal tracking problem with time delay. Compared with the traditional reinforcement learning method, Q-learning method avoids the need for accurate system model. Firstly, the delay operator is introduced to construct a novel augmented system composed of the original system and the command generator. Secondly, the SLQ optimal tracking problem is transformed into a deterministic one by system transformation and the corresponding Q function of SLQ optimal tracking control is derived. Based on this, Q-learning algorithm is proposed and its convergence is proved. Finally, a simulation example shows the effectiveness of the proposed algorithm.



    Let Ω={zRn:R1<|z|<R2,R1,R2>0}. In this work we study the existence of positive radial solutions for the following system of boundary value problems with semipositone second order elliptic equations:

    {Δφ+k(|z|)f(φ,ϕ)=0, zΩ,Δϕ+k(|z|)g(φ,ϕ)=0, zΩ,αφ+βφn=0, αϕ+βϕn=0, |z|=R1,γφ+δφn=0, γϕ+δϕn=0, |z|=R2, (1.1)

    where α,β,γ,δ,k,f,g satisfy the conditions:

    (H1) α,β,γ,δ0 with ργβ+αγ+αδ>0;

    (H2) kC([R1,R2],R+), and k is not vanishing on [R1,R2];

    (H3) f,gC(R+×R+,R), and there is a positive constant M such that

    f(u,v),g(u,v)M, u,vR+.

    Elliptic equations have attracted a lot of attention in the literature since they are closely related to many mathematical and physical problems, for instance, incineration theory of gases, solid state physics, electrostatic field problems, variational methods and optimal control. The existence of solutions for this type of equation in annular domains has been discussed in the literature, see for example, [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18] and the references therein. In [1] the authors used the fixed point index to study positive solutions for the elliptic system:

    {Δu+a(|x|)f(u,v)=0,Δv+b(|x|)g(u,v)=0,

    with one of the following boundary conditions

    u=v=0,|x|=R1,|x|=R2,u=v=0,|x|=R1,ur=vr=0,|x|=R2,ur=vr=0,|x|=R1,u=v=0,|x|=R2.

    In [2] the authors used the method of upper and lower solutions to establish the existence of positive radial solutions for the elliptic equation

    {Δu=f(|x|,u,|u|), xΩ,u|Ω=0,

    where Ω={xRN: |x|<1},N2, and f:[0,1]×R+×R+R is a continuous function.

    However, we note that in most of the papers on nonlinear differential equations the nonlinear term is usually assumed to be nonnegative. In recent years boundary value problems for semipositone equations (f(t,x)M,M>0) has received some attention (see [19,20,21,22,23,24,25,26,27,28,29,30,31,32]), and these equations describe and solve many natural phenomena in engineering and technical problems in real life, for example in mechanical systems, suspension bridge design, astrophysics and combustion theoretical models. In [19] the authors used a fixed point theorem to study the system for HIV-1 population dynamics in the fractional sense

    {Dα0+u(t)+λf(t,u(t),Dβ0+u(t),v(t))=0,t(0,1),Dγ0+v(t)+λg(t,u(t))=0,t(0,1),Dβ0+u(0)=Dβ+10+u(0)=0,Dβ0+u(1)=10Dβ0+u(s)dA(s),v(0)=v(0)=0,v(1)=10v(s)dB(s),

    where Dα0+,Dβ0+,Dγ0+ are the standard Riemann-Liouville derivatives, and f, g are two semipositone nonlinearities. In [28] the authors used the nonlinear alternative of Leray-Schauder type and the Guo-Krasnosel'skii fixed point theorem to study the existence of positive solutions for a system of nonlinear Riemann-Liouville fractional differential equations

    {Dα0+u(t)+λf(t,v(t))=0,0<t<1, λ>0,Dα0+v(t)+λg(t,u(t))=0,0<t<1, λ>0,u(j)(0)=v(j)(0)=0,0jn2,u(1)=μ10u(s)ds,v(1)=μ10v(s)ds,

    where f,g satisfy some superlinear or sublinear conditions:

    (HZ)1 There exist M>0 such that lim supz0g(t,z)z<M uniformly for t[0,1] (sublinear growth condition).

    (HZ)2 There exists [θ1,θ2](0,1) such that lim infz+f(t,z)z=+ and lim infz+g(t,z)z=+ uniformly for t[θ1,θ2] (superlinear growth condition).

    Inspired by the aforementioned work, in particular [31,32,33,34], we study positive radial solutions for (1.1) when the nonlinearities f,g satisfy the semipositone condition (H3). Moreover, some appropriate concave and convex functions are utilized to characterize coupling behaviors of our nonlinearities. Note that our conditions (H4) and (H6) (see Section 3) are more general than that in (HZ)1 and (HZ)2.

    Using the methods in [1,4], we transform (1.1) into a system of ordinary differential equations involving Sturm-Liouville boundary conditions. Let φ=φ(r),ϕ=ϕ(r),r=|z|=ni=1z2i. Then (1.1) can be expressed by the following system of ordinary differential equations:

    {φ(r)+n1rφ(r)+k(r)f(φ(r),ϕ(r))=0, R1<r<R2,ϕ(r)+n1rϕ(r)+k(r)g(φ(r),ϕ(r))=0, R1<r<R2,αφ(R1)βφ(R1)=0, γφ(R2)+δφ(R2)=0,αϕ(R1)βϕ(R1)=0, γϕ(R2)+δϕ(R2)=0. (2.1)

    Then if we let s=R2r(1/tn1)dt,t=(ms)/m,m=R2R1(1/tn1)dt, (2.1) can be transformed into the system

    {φ(t)+h(t)f(φ(t),ϕ(t))=0,0<t<1,ϕ(t)+h(t)g(φ(t),ϕ(t))=0,0<t<1,αφ(0)βφ(0)=0,γφ(1)+δφ(1)=0,αϕ(0)βϕ(0)=0,γϕ(1)+δϕ(1)=0, (2.2)

    where h(t)=m2r2(n1)(m(1t))k(r(m(1t))). Consequently, (2.2) is equivalent to the following system of integral equations

    {φ(t)=10G(t,s)h(s)f(φ(s),ϕ(s))ds,ϕ(t)=10G(t,s)h(s)g(φ(s),ϕ(s))ds, (2.3)

    where

    G(t,s)=1ρ{(γ+δγt)(β+αs),0st1,(γ+δγs)(β+αt),0ts1, (2.4)

    and ρ is defined in (H1).

    Lemma 2.1. Suppose that (H1) holds. Then

    (i)

    ρ(γ+δ)(β+α)G(t,t)G(s,s)G(t,s)G(s,s), t,s[0,1];

    (ii)

    G(t,s)G(t,t), t,s[0,1].

    Proof. (i) In G(t,s), we fix the second variable s, we have

    G(t,s)=1ρ{(γ+δγt)(β+αs)(γ+δγs)(β+αs),0st1,(γ+δγs)(β+αt)(γ+δγs)(β+αs),0ts1.

    This implies that

    G(t,s)G(s,s),t,s[0,1].

    When ts, we have

    1ρ(γ+δγt)(β+αs)ρ1ρ1ρ(γ+δγt)(β+αt)(γ+δγs)(β+αs)1(β+α)(γ+δ).

    When ts, we have

    1ρ(γ+δγs)(β+αt)ρ1ρ1ρ(γ+δγt)(β+αt)(γ+δγs)(β+αs)1(β+α)(γ+δ).

    Combining the above we obtain

    G(t,s)G(t,t)G(s,s)ρ(β+α)(γ+δ).

    (ii) In G(t,s) we fix the first variable t, and we obtain

    G(t,s)=1ρ{(γ+δγt)(β+αs)(γ+δγt)(β+αt),0st1,(γ+δγs)(β+αt)(γ+δγt)(β+αt),0ts1.

    Thus

    G(t,s)G(t,t),t,s[0,1].

    Lemma 2.2. Suppose that (H1) holds. Let ϑ(t)=G(t,t)h(t),t[0,1]. Then

    κ1ϑ(s)10G(t,s)h(s)ϑ(t)dtκ2ϑ(s),

    where

    κ1=ρ(γ+δ)(β+α)10G(t,t)ϑ(t)dt, κ2=10ϑ(t)dt.

    Proof. From (H1) and Lemma 2.1(i) we have

    10G(t,s)h(s)ϑ(t)dt10G(s,s)h(s)ϑ(t)dt=κ2ϑ(s)

    and

    10G(t,s)h(s)ϑ(t)dt10ρ(γ+δ)(β+α)G(t,t)G(s,s)h(s)ϑ(t)dt=κ1ϑ(s).

    Note we study (2.3) to obtain positive solutions for (1.1). However here the nonlinear terms f,g can be sign-changing (see (H3)). Therefore we study the following auxiliary problem:

    u(t)=10G(t,s)h(s)˜f(u(s))ds, (2.5)

    where G is in (2.4) and ˜f satisfies the condition:

    (H2) ˜fC(R+,R), and there exists a positive constant M such that

    ˜f(u)M, uR+.

    Let w(t)=M10G(t,s)h(s)ds,t[0,1]. Then w is a solution of the following boundary value problem:

    {u(t)+h(t)M=0,0<t<1,αu(0)βu(0)=0,γu(1)+δu(1)=0. (2.6)

    Lemma 2.3. (i) If u satisfies (2.5), then u+w is a solution of the equation:

    u(t)=10G(t,s)h(s)˜F(u(s)w(s))ds, (2.7)

    where

    ˜F(u)={˜f(u)+M,u0,˜f(0)+M,u<0. (2.8)

    (ii) If u satisfies (2.7) with u(t)w(t),t[0,1], then uw is a positive solution for (2.5).

    Proof. We omit its proof since it is immediate.

    Let E=C[0,1], . Then (E, \|\cdot\|) is a Banach space. Define a set on E as follows:

    P = \{u\in E: u(t)\ge 0, \forall t\in [0, 1]\},

    and note P is a cone on E . Note, E^2 = E\times E is also a Banach space with the norm: \|(u, v)\| = \|u\|+\|v\| , and P^2 = P\times P a cone on E^2 . In order to obtain positive radial solutions for (1.1), combining with (2.5)–(2.7), we define the following operator equation:

    \begin{equation} A(\varphi, \phi) = (\varphi, \phi), \end{equation} (2.9)

    where A(\varphi, \phi) = (A_1, A_2)(\varphi, \phi) , A_i(i = 1, 2) are

    \begin{equation} \left\{\begin{aligned} A_1(\varphi, \phi)(t) & = \int_{0}^{1} G(t, s) h(s) \mathcal {F}_1(\varphi(s)-w(s), \phi(s)-w(s)) \mathrm{d} s, \\ A_2(\varphi, \phi)(t) & = \int_{0}^{1} G(t, s) h(s) \mathcal {F}_2(\varphi(s)-w(s), \phi(s)-w(s)) \mathrm{d} s, \end{aligned}\right. \end{equation} (2.10)

    and

    \mathcal {F}_1(\varphi, \phi) = \begin{cases}f(\varphi, \phi)+M, \varphi, \phi\ge 0, \\ f(0, \phi)+M, \varphi < 0, \phi\ge 0, \\ f(\varphi, 0)+M, \varphi\ge 0, \phi < 0, \\ f(0, 0)+M, \varphi, \phi < 0, \end{cases}
    \mathcal {F}_2(\varphi, \phi) = \begin{cases}g(\varphi, \phi)+M, \varphi, \phi\ge 0, \\ g(0, \phi)+M, \varphi < 0, \phi\ge 0, \\ g(\varphi, 0)+M, \varphi\ge 0, \phi < 0, \\ g(0, 0)+M, \varphi, \phi < 0. \end{cases}

    Lemma 2.4. Define P_0 = \left\{\varphi\in P: \varphi(t)\ge \frac{\rho}{(\gamma+\delta)(\beta+\alpha)}G(t, t)\|\varphi\|, t\in [0, 1]\right\} . Then A_i(P\times P)\subset P_0, i = 1, 2 .

    Proof. We only prove it for A_1 . If \varphi, \phi\in P , note the non-negativity of \mathcal {F}_1 (denoted by \mathcal {F}_1(\cdot, \cdot) ), from Lemma 2.1(i) we have

    \int_{0}^{1} \frac{\rho}{(\gamma+\delta)(\beta+\alpha)}G(t, t)G(s, s) h(s) \mathcal {F}_1(\cdot, \cdot) \mathrm{d} s \le A_1(\varphi, \phi)(t) \le \int_{0}^{1} G(s, s) h(s) \mathcal {F}_1(\cdot, \cdot) \mathrm{d} s.

    This implies that

    A_1(\varphi, \phi)(t) \ge \int_{0}^{1} \frac{\rho}{(\gamma+\delta)(\beta+\alpha)}G(t, t)G(s, s) h(s) \mathcal {F}_1(\cdot, \cdot) \mathrm{d} s\ge \frac{\rho}{(\gamma+\delta)(\beta+\alpha)}G(t, t) \|A_1(\varphi, \phi)\|.

    Remark 2.1. (i) w(t) = M\int_{0}^{1} G(t, s) h(s) \mathrm{d} s\in P_0 ;

    (ii) Note (see Corollary 1.5.1 in [35]):

    If k(x, y, u):\widetilde{G}\times \widetilde{G}\times \mathbb R\to \mathbb R is continuous ( \widetilde{G} is a bounded closed domain in \mathbb R^n ), then K is a completely continuous operator from C(\widetilde{G}) into itself, where

    K\psi(x) = \int_{\widetilde{G}}k(x, y, \psi(y))\mathrm{d} y.

    Note that G(t, s), h(s), \mathcal {F}_i(i = 1, 2) are continuous, and also A_i , A are completely continuous operators, i = 1, 2 .

    From Lemma 2.3 if there exists (\varphi, \phi)\in P^2\backslash\{(0, 0)\} such that (2.9) holds with (\varphi, \phi)\ge (w, w) , then \varphi(t), \phi(t)\ge w(t), t\in [0, 1] , and (\varphi-w, \phi-w) is a positive solution for (2.3), i.e., we obtain positive radial solutions for (1.1). Note that \varphi, \phi\in P_0 , and from Lemma 2.1(ii) we have

    \varphi(t)-w(t)\ge \frac{\rho}{(\gamma+\delta)(\beta+\alpha)}G(t, t)\|\varphi\|-M\int_{0}^{1} G(t, t) h(s) \mathrm{d} s,
    \phi(t)-w(t)\ge \frac{\rho}{(\gamma+\delta)(\beta+\alpha)}G(t, t)\|\phi\|-M\int_{0}^{1} G(t, t) h(s) \mathrm{d} s.

    Hence, if

    \|\varphi\|, \|\phi\|\ge \frac{M(\gamma+\delta)(\beta+\alpha)}{\rho}\int_{0}^{1} h(s) \mathrm{d} s ,

    we have (\varphi, \phi)\ge (w, w) . As a result, we only need to seek fixed points of (2.9), when their norms are greater than \frac{M(\gamma+\delta)(\beta+\alpha)}{\rho}\int_{0}^{1} h(s) \mathrm{d} s .

    Let E be a real Banach space. A subset X \subset E is called a retract of E if there exists a continuous mapping r: E \rightarrow X such that r(x) = x, \ x \in X . Note that every cone in E is a retract of E . Let X be a retract of real Banach space E . Then, for every relatively bounded open subset U of X and every completely continuous operator A: \overline{U} \rightarrow X which has no fixed points on \partial U , there exists an integer i(A, U, X) satisfying the following conditions:

    (i) Normality: i(A, U, X) = 1 if A x \equiv y_0 \in U for any x \in \overline{U} .

    (ii) Additivity: i(A, U, X) = i\left(A, U_1, X\right)+i\left(A, U_2, X\right) whenever U_1 and U_2 are disjoint open subsets of U such that A has no fixed points on \overline{U} \backslash\left(U_1 \cup U_2\right) .

    (iii) Homotopy invariance: i(H(t, \cdot), U, X) is independent of t (0 \leq t \leq 1) whenever H:[0, 1] \times \overline{U} \rightarrow X is completely continuous and H(t, x) \neq x for any (t, x) \in[0, 1] \times \partial U .

    (iv) Permanence: i(A, U, X) = i(A, U \cap Y, Y) if Y is a retract of X and A(\overline{U}) \subset Y .

    Then i(A, U, X) is called the fixed point index of A on U with respect to X .

    Lemma 2.5. (see [35,36]). Let E be a real Banach space and P a cone on E . Suppose that \Omega\subset E is a bounded open set and that A:\overline{\Omega}\cap P\to P is a continuous compact operator. If there exists \omega_{0}\in P\backslash \{0\} such that

    \omega-A\omega\neq \lambda\omega_{0}, \forall \lambda\geq0, \omega\in\partial\Omega\cap P,

    then i(A, \Omega\cap P, P) = 0 , where i denotes the fixed point index on P .

    Lemma 2.6. (see [35,36]). Let E be a real Banach space and P a cone on E . Suppose that \Omega\subset E is a bounded open set with 0\in\Omega and that A:\overline{\Omega}\cap P\to P is a continuous compact operator. If

    \omega-\lambda A\omega\neq0, \forall \lambda\in[0, 1], \omega\in\partial\Omega\cap P,

    then i(A, \Omega\cap P, P) = 1 .

    Denote \mathcal {O}_{M, h} = \frac{M(\gamma+\delta)(\beta+\alpha)}{\rho}\int_{0}^{1} h(s) \mathrm{d} s , B_\zeta = \{u\in E: \|u\| < \zeta\}, \zeta > 0, B_\zeta^2 = B_\zeta\times B_\zeta . We list our assumptions as follows:

    (H4) There exist p, q\in C(\mathbb R^+, \mathbb R^+) such that

    (i) p is a strictly increasing concave function on \mathbb R^+ ;

    (ii) \liminf_{v\to \infty}\frac{f(u, v)}{p(v)}\ge 1 , \liminf_{u\to \infty}\frac{g(u, v)}{q(u)}\ge 1 ;

    (iii) there exists e_1\in (\kappa_1^{-2}, \infty) such that \liminf_{z\to\infty}\frac{p(\mathcal {L}_{G, h}q(z))}{z}\ge e_1\mathcal {L}_{G, h} , where \mathcal {L}_{G, h} = \max_{t, s\in [0, 1]}G(t, s)h(s) .

    (H5) There exists Q_i\in \left(0, \frac{\mathcal {O}_{M, h}}{\kappa_2}\right) such that

    \mathcal {F}_i(u-w, v-w)\le Q_i, u, v\in [0, \mathcal {O}_{M, h}], i = 1, 2.

    (H6) There exist \zeta, \eta\in C(\mathbb R^+, \mathbb R^+) such that

    (i) \zeta is a strictly increasing convex function on \mathbb R^+ ;

    (ii) \limsup_{v\to \infty}\frac{f(u, v)}{\zeta(v)}\le 1 , \limsup_{u\to \infty}\frac{g(u, v)}{\eta(u)}\le 1 ;

    (iii) there exists e_2\in (0, \kappa_2^{-2}) such that \limsup_{z\to\infty}\frac{\zeta(\mathcal {L}_{G, h}\eta(z))}{z}\le e_2\mathcal {L}_{G, h} .

    (H7) There exists \widetilde{Q}_i\in \left(\frac{\mathcal {O}_{M, h}}{\kappa_2\mathcal L_G}, \infty\right) such that

    \mathcal {F}_i(u-w, v-w)\ge \widetilde{Q}_i, u, v\in [0, \mathcal {O}_{M, h}], i = 1, 2,

    where \mathcal L_G = \max_{t\in [0, 1]} \frac{\rho}{(\gamma+\delta)(\beta+\alpha)}G(t, t) .

    Remark 3.1. Condition (H4) implies that f grows p(v) -superlinearly at \infty uniformly on u\in \mathbb R^+ , g grows q(u) -superlinearly at \infty uniformly on v\in \mathbb R^+ ; condition (H6) implies that f grows \zeta(v) -sublinearly at \infty uniformly on u\in \mathbb R^+ , g grows \eta(u) -sublinearly at \infty uniformly on v\in \mathbb R^+ .

    Theorem 3.1. Suppose that (H1)–(H5) hold. Then (1.1) has at least one positive radial solution.

    Proof. Step 1. When \varphi, \phi\in \partial B_{\mathcal {O}_{M, h}}\cap P , we have

    \begin{equation} (\varphi, \phi)\not = \lambda A(\varphi, \phi), \lambda\in [0, 1]. \end{equation} (3.1)

    Suppose the contrary i.e., if (3.1) is false, then there exist \varphi_0, \phi_0\in \partial B_{\mathcal {O}_{M, h}}\cap P and \lambda_0\in [0, 1] such that

    (\varphi_0, \phi_0) = \lambda_0 A(\varphi_0, \phi_0).

    This implies that

    \begin{equation} \varphi_0, \phi_0 \in P_0 \end{equation} (3.2)

    and

    \begin{equation} \|\varphi_0\|\le \|A_1(\varphi_0, \phi_0)\|, \ \|\phi_0\|\le \|A_2(\varphi_0, \phi_0)\|. \end{equation} (3.3)

    From (H5) we have

    A_i(\varphi_0, \phi_0)(t) = \int_{0}^{1} G(t, s) h(s) \mathcal {F}_i(\varphi_0(s)-w(s), \phi_0(s)-w(s)) \mathrm{d} s\le \int_{0}^{1}\vartheta(s) Q_i \mathrm{d} s < \mathcal {O}_{M, h} , i = 1, 2.

    Thus

    \|A_1(\varphi_0, \phi_0)\|+\|A_2(\varphi_0, \phi_0)\| < 2\mathcal {O}_{M, h} = \|\varphi_0\|+\|\phi_0\|(\varphi_0, \phi_0\in \partial B_{\mathcal {O}_{M, h}}\cap P),

    which contradicts (3.3), and thus (3.1) holds. From Lemma 2.6 we have

    \begin{equation} i(A, B^2_{\mathcal {O}_{M, h}}\cap P^2, P^2) = 1. \end{equation} (3.4)

    Step 2. There exists a sufficiently large R > \mathcal {O}_{M, h} such that

    \begin{equation} (\varphi, \phi)\not = A(\varphi, \phi)+\lambda (\varrho_1, \varrho_1), \varphi, \phi\in \partial B_R \cap P, \lambda\ge 0, \end{equation} (3.5)

    where \varrho_1\in P_0 is a given element. Suppose the contrary. Then there are \varphi_1, \phi_1\in \partial B_R \cap P, \lambda_1\ge 0 such that

    \begin{equation} (\varphi_1, \phi_1) = A(\varphi_1, \phi_1)+\lambda_1 (\varrho_1, \varrho_1). \end{equation} (3.6)

    This implies that

    \varphi_1(t) = A_1(\varphi_1, \phi_1)(t)+\lambda_1 \varrho_1(t), \ \phi_1(t) = A_2(\varphi_1, \phi_1)(t)+\lambda_1 \varrho_1(t), t\in [0, 1].

    From Lemma 2.4 and \varrho_1\in P_0 we have

    \begin{equation} \varphi_1, \phi_1\in P_0. \end{equation} (3.7)

    Note that \|\varphi_1\| = \|\phi_1\| = R > \mathcal {O}_{M, h} , and thus \varphi_1(t)\ge w(t), \phi_1(t)\ge w(t), t\in [0, 1] .

    By (H4)(ii) we obtain

    \liminf\limits_{\phi\to \infty}\frac{\mathcal {F}_1(\varphi, \phi)}{p(\phi)} = \liminf\limits_{\phi\to \infty}\frac{f(\varphi, \phi)+M}{p(\phi)}\ge 1, \ \liminf\limits_{\varphi\to \infty}\frac{\mathcal {F}_2(\varphi, \phi)}{q(\varphi)} = \liminf\limits_{\varphi\to \infty}\frac{g(\varphi, \phi)+M}{q(\varphi)}\ge 1.

    This implies that there exist c_1, c_2 > 0 such that

    \mathcal {F}_1(\varphi, \phi)\ge p(\phi)-c_1, \ \mathcal {F}_2(\varphi, \phi)\ge q(\varphi)-c_2, \ \varphi, \phi\in \mathbb R^+.

    Therefore, we have

    \begin{equation} \begin{aligned} \varphi_1(t)& = A_1(\varphi_1, \phi_1)(t)+\lambda_1 \varrho_1(t)\\ & \ge A_1(\varphi_1, \phi_1)(t)\\ & \ge \int_{0}^{1} G(t, s) h(s) [p( \phi_1(s)-w(s))-c_1] \mathrm{d} s\\ & \ge \int_{0}^{1} G(t, s) h(s) p( \phi_1(s)-w(s)) \mathrm{d} s-c_1 \kappa_2 \end{aligned} \end{equation} (3.8)

    and

    \begin{equation} \begin{aligned} \phi_1(t)& = A_2(\varphi_1, \phi_1)(t)+\lambda_1 \varrho_1(t)\\ & \ge A_2(\varphi_1, \phi_1)(t)\\ & \ge \int_{0}^{1} G(t, s) h(s) [q( \varphi_1(s)-w(s))-c_2] \mathrm{d} s\\ & \ge \int_{0}^{1} G(t, s) h(s) q( \varphi_1(s)-w(s)) \mathrm{d} s-c_2\kappa_2. \end{aligned} \end{equation} (3.9)

    Consequently, we have

    \begin{aligned} \phi_1(t)-w(t)&\ge \int_{0}^{1} G(t, s) h(s) q( \varphi_1(s)-w(s)) \mathrm{d} s-c_2\kappa_2-w(t)\\ & \ge \int_{0}^{1} G(t, s) h(s) q( \varphi_1(s)-w(s)) \mathrm{d} s -(c_2+M)\kappa_2. \end{aligned}

    From (H4)(iii), there is a c_3 > 0 such that

    p(\mathcal {L}_{G, h}q(z))\ge e_1\mathcal {L}_{G, h} z-\mathcal {L}_{G, h}c_3, z\in \mathbb R^+.

    Combining with (H4)(i), we have

    \begin{aligned} p(\phi_1(t)-w(t))&\ge p(\phi_1(t)-w(t)+(c_2+M)\kappa_2)-p((c_2+M)\kappa_2)\\ & \ge p\left(\int_{0}^{1} G(t, s) h(s) q( \varphi_1(s)-w(s)) \mathrm{d} s\right)-p((c_2+M)\kappa_2)\\ & = p\left(\int_{0}^{1} \frac{G(t, s) h(s)}{\mathcal {L}_{G, h}} \mathcal {L}_{G, h} q( \varphi_1(s)-w(s)) \mathrm{d} s\right)-p((c_2+M)\kappa_2)\\ & \ge \int_{0}^{1} p\left(\frac{G(t, s) h(s)}{\mathcal {L}_{G, h}} \mathcal {L}_{G, h} q( \varphi_1(s)-w(s)) \right)\mathrm{d} s-p((c_2+M)\kappa_2)\\ & \ge \int_{0}^{1} \frac{G(t, s) h(s)}{\mathcal {L}_{G, h}} p\left( \mathcal {L}_{G, h} q( \varphi_1(s)-w(s)) \right)\mathrm{d} s-p((c_2+M)\kappa_2)\\ & \ge \int_{0}^{1} \frac{G(t, s) h(s)}{\mathcal {L}_{G, h}} (e_1\mathcal {L}_{G, h} (\varphi_1(s)-w(s))-\mathcal {L}_{G, h}c_3) \mathrm{d} s-p((c_2+M)\kappa_2)\\ & \ge e_1 \int_{0}^{1} G(t, s) h(s) (\varphi_1(s)-w(s)) \mathrm{d} s-p((c_2+M)\kappa_2)-c_3\kappa_2. \end{aligned}

    Substituting this inequality into (3.8) we have

    \begin{aligned} \varphi_1(t)-w(t)& \ge \int_{0}^{1} G(t, s) h(s) \left[e_1 \int_{0}^{1} G(s, \tau) h(\tau) (\varphi_1(\tau)-w(\tau)) \mathrm{d} \tau-p((c_2+M)\kappa_2)-c_3\kappa_2\right] \mathrm{d} s\\ & \ \ \ -(c_1+M) \kappa_2\\ & \ge e_1 \int_{0}^{1} \int_{0}^{1} G(t, s) h(s) G(s, \tau) h(\tau) (\varphi_1(\tau)-w(\tau)) \mathrm{d} \tau \mathrm{d} s\\ & \ \ \ -p((c_2+M)\kappa_2)\kappa_2-c_3\kappa^2_2 -(c_1+M) \kappa_2. \end{aligned}

    Multiply by \vartheta(t) on both sides of the above and integrate over [0, 1] and use Lemma 2.2 to obtain

    \begin{aligned} \int_0^1 (\varphi_1(t)-w(t))\vartheta(t) \mathrm{d} t& \ge e_1\int_0^1 \vartheta(t) \int_{0}^{1} \int_{0}^{1} G(t, s) h(s) G(s, \tau) h(\tau) (\varphi_1(\tau)-w(\tau)) \mathrm{d} \tau \mathrm{d} s \mathrm{d} t\\ & \ \ \ -p((c_2+M)\kappa_2)\kappa^2_2-c_3\kappa^3_2 -(c_1+M) \kappa^2_2\\ & \ge e_1\kappa_1^2 \int_0^1 (\varphi_1(t)-w(t))\vartheta(t) \mathrm{d} t -p((c_2+M)\kappa_2)\kappa^2_2-c_3\kappa^3_2 -(c_1+M) \kappa^2_2. \end{aligned}

    From this inequality we have

    \int_0^1 (\varphi_1(t)-w(t))\vartheta(t) \mathrm{d} t\le \frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{e_1\kappa_1^2-1}

    and thus

    \begin{aligned} \int_0^1 \varphi_1(t)\vartheta(t) \mathrm{d} t& \le \frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{e_1\kappa_1^2-1}+ \int_0^1 w(t)\vartheta(t) \mathrm{d} t\\ & \le \frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{e_1\kappa_1^2-1}+M\kappa_2^2 . \end{aligned}

    Note that (3.7), \varphi_1\in P_0 , and we have

    \|\varphi_1\|\le \frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{\kappa_1(e_1\kappa_1^2-1)}+\frac{M\kappa_2^2}{\kappa_1} .

    On the other hand, multiply by \vartheta(t) on both sides of (3.8) and integrate over [0, 1] and use Lemma 2.2 to obtain

    \begin{aligned} \kappa_1 \int_{0}^{1} \vartheta(t) p( \phi_1(t)-w(t)) \mathrm{d} t&\le \int_0^1 \varphi_1(t)\vartheta(t)\mathrm{d} t +c_1 \kappa^2_2\\ &\le \frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{e_1\kappa_1^2-1}+M\kappa_2^2+c_1 \kappa^2_2 .\end{aligned}

    From Remark 2.1 we have w\in P_0 , note that \|\phi_1\| = R > \frac{M(\gamma+\delta)(\beta+\alpha)}{\rho}\int_{0}^{1} h(s) \mathrm{d} s\ge \|w\| and \phi_1\in P_0 , then \phi_1-w\in P_0 . By the concavity of p we have

    \begin{aligned} \|\phi_1-w\|&\le \kappa_1^{-1}\int_0^1 (\phi_1(t)-w(t))\vartheta(t)\mathrm{d} t = \frac{\|\phi_1-w\|}{\kappa_1 p(\|\phi_1-w\|)}\int_0^1 \frac{\phi_1(t)-w(t)}{\|\phi_1-w\|}p(\|\phi_1-w\|)\vartheta(t)\mathrm{d} t\\ & \le \frac{\|\phi_1-w\|}{\kappa_1 p(\|\phi_1-w\|)}\int_0^1 p\left(\frac{\phi_1(t)-w(t)}{\|\phi_1-w\|}\|\phi_1-w\|\right)\vartheta(t)\mathrm{d} t\\ & \le \frac{\|\phi_1-w\|}{\kappa^2_1 p(\|\phi_1-w\|)}\left[\frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{e_1\kappa_1^2-1}+M\kappa_2^2+c_1 \kappa^2_2\right]. \end{aligned}

    This implies that

    p(\|\phi_1-w\|)\le \frac{1}{\kappa^2_1 }\left[\frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{e_1\kappa_1^2-1}+M\kappa_2^2+c_1 \kappa^2_2\right].

    From (H4)(i) we have

    \begin{aligned} p(\|\phi_1\|)& = p(\|\phi_1-w+w\|)\le p(\|\phi_1-w\|+\|w\|)\le p(\|\phi_1-w\|)+p(\|w\|)\\ & \le \frac{1}{\kappa^2_1 }\left[\frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{e_1\kappa_1^2-1}+M\kappa_2^2+c_1 \kappa^2_2\right]+p(\|w\|)\\ & \le \frac{1}{\kappa^2_1 }\left[\frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{e_1\kappa_1^2-1}+M\kappa_2^2+c_1 \kappa^2_2\right]+p(M\kappa_2) \\ & < +\infty.\end{aligned}

    Therefore, there exists \mathcal {O}_{\phi_1} > 0 such that \|\phi_1\|\le\mathcal {O}_{\phi_1} .

    We have prove the boundedness of \varphi_1, \phi_1 when (3.6) holds, i.e., when \varphi_1, \phi_1\in \partial B_R\cap P , there exist a positive constant to control the norms of \varphi_1, \phi_1 . Now we choose a sufficiently large

    R_1 > \max\left\{\mathcal {O}_{M, h}, \mathcal {O}_{\phi_1}, \frac{p((c_2+M)\kappa_2)\kappa^2_2+c_3\kappa^3_2 +(c_1+M) \kappa^2_2}{\kappa_1(e_1\kappa_1^2-1)}+\frac{M\kappa_2^2}{\kappa_1}\right\}.

    Then when \varphi_1, \phi_1\in \partial B_{R_1} \cap P , (3.6) is not satisfied, and thus (3.5) holds. From Lemma 2.5 we have

    \begin{equation} i(A, B^2_{R_1}\cap P^2, P^2) = 0. \end{equation} (3.10)

    Combining (3.4) with (3.10) we have

    i(A, (B^2_{R_1}\backslash \overline{B}^2_{\mathcal {O}_{M, h}})\cap P^2, P^2) = i(A, B^2_{R_1}\cap P^2, P^2)- i(A, B^2_{\mathcal {O}_{M, h}}\cap P^2, P^2) = 0-1 = -1.

    Then the operator A has at least one fixed point (denoted by (\varphi^*, \phi^*) ) on (B^2_{R_1}\backslash \overline{B}^2_{\mathcal {O}_{M, h}})\cap P^2 with \varphi^*(t), \phi^*(t)\ge w(t), t\in [0, 1] . Therefore, (\varphi^*-w, \phi^*-w) is a positive solution for (2.2), and (1.1) has at least one positive radial solution.

    Theorem 3.2. Suppose that (H1)–(H3), (H6) and (H7) hold. Then (1.1) has at least one positive radial solution.

    Proof. Step 1. When \varphi, \phi\in \partial B_{\mathcal {O}_{M, h}}\cap P , we have

    \begin{equation} (\varphi, \phi)\not = A(\varphi, \phi)+\lambda (\varrho_2, \varrho_2), \lambda\ge 0, \end{equation} (3.11)

    where \varrho_2\in P is a given element. Suppose the contrary. Then there exist \varphi_2, \phi_2\in \partial B_{\mathcal {O}_{M, h}}\cap P, \lambda_2\ge 0 such that

    (\varphi_2, \phi_2) = A(\varphi_2, \phi_2)+\lambda_2 (\varrho_2, \varrho_2).

    This implies that

    \|\varphi_2\|\ge \varphi_2(t)\ge A_1(\varphi_2, \phi_2)(t)+\lambda_2 \varrho_2(t)\ge A_1(\varphi_2, \phi_2)(t), t\in [0, 1],
    \|\phi_2\|\ge \phi_2(t)\ge A_2(\varphi_2, \phi_2)(t)+\lambda_2 \varrho_2(t)\ge A_2(\varphi_2, \phi_2)(t), t\in [0, 1].

    Then we have

    \begin{equation} \|\varphi_2\|+\|\phi_2\|\ge \|A_1(\varphi_2, \phi_2)\|+\|A_2(\varphi_2, \phi_2)\|. \end{equation} (3.12)

    From (H7) we have

    \begin{aligned} \|A_i(\varphi_2, \phi_2)\|& = \max\limits_{t\in [0, 1]}A_i(\varphi_2, \phi_2)(t)\\ & \ge \max\limits_{t\in [0, 1]} \frac{\rho}{(\gamma+\delta)(\beta+\alpha)}G(t, t) \int_{0}^{1} G(s, s) h(s) \mathcal {F}_i(\varphi_2(s)-w(s), \phi_2(s)-w(s)) \mathrm{d} s\\ & \ge \mathcal L_G \int_{0}^{1} G(s, s) h(s) \widetilde{Q}_i \mathrm{d} s = \widetilde{Q}_i\kappa_2\mathcal L_G, i = 1, 2. \end{aligned}

    By the condition on \widetilde{Q}_i we have

    \|A_1(\varphi_2, \phi_2)\|+\|A_2(\varphi_2, \phi_2)\| > 2 \mathcal {O}_{M, h} = \|\varphi_2\|+\|\phi_2\|,

    and this contradicts (3.12), so (3.11) holds. By Lemma 2.5 we have

    \begin{equation} i(A, B^2_{\mathcal {O}_{M, h}}\cap P^2, P^2) = 0. \end{equation} (3.13)

    Step 2. There exists a sufficiently large R > \mathcal {O}_{M, h} such that

    \begin{equation} (\varphi, \phi)\not = \lambda A(\varphi, \phi), \varphi, \phi\in \partial B_R \cap P, \lambda\in [0, 1]. \end{equation} (3.14)

    Suppose the contrary. Then there exist \varphi_3, \phi_3\in \partial B_R \cap P, \lambda_3\in [0, 1] such that

    \begin{equation} (\varphi_3, \phi_3) = \lambda_3 A(\varphi_3, \phi_3). \end{equation} (3.15)

    Combining with Lemma 2.4 we have

    \begin{equation} \varphi_3, \phi_3\in P_0. \end{equation} (3.16)

    Note that \varphi_3, \phi_3\in \partial B_R\cap P, and then \varphi_3(t)-w(t), \phi_3(t)-w(t)\ge 0, t\in [0, 1] . Hence, from (H6) we have

    \limsup\limits_{\phi\to \infty} \frac{\mathcal {F}_1(\varphi, \phi)}{\zeta(\phi)} = \limsup\limits_{\phi\to \infty} \frac{f(\varphi, \phi)+M}{\zeta(\phi)}\le 1, \ \limsup\limits_{\varphi\to \infty} \frac{\mathcal {F}_2(\varphi, \phi)}{\eta(\varphi)} = \limsup\limits_{\varphi\to \infty} \frac{g(\varphi, \phi)+M}{\eta(\varphi)}\le 1.

    This implies that there exists \widetilde{M} > 0 such that

    \begin{equation} \mathcal {F}_1(\varphi, \phi)\le \zeta(\phi), \ \mathcal {F}_2(\varphi, \phi)\le \eta(\varphi), \varphi, \phi\ge \widetilde{M}. \end{equation} (3.17)

    By similar methods as in Theorem 3.1, choosing R > \widetilde{M} , and from (3.15) we obtain

    \begin{equation} \begin{aligned} \varphi_3(t)& = \lambda_3 A_1(\varphi_3, \phi_3)(t)\le \int_{0}^{1} G(t, s) h(s) \zeta(\phi_3(s)-w(s)) \mathrm{d} s \end{aligned} \end{equation} (3.18)

    and

    \begin{equation} \begin{aligned} \phi_3(t)& = \lambda_3 A_2(\varphi_3, \phi_3)(t)\le \int_{0}^{1} G(t, s) h(s) \eta(\varphi_3(s)-w(s)) \mathrm{d} s. \end{aligned} \end{equation} (3.19)

    From (H6)(iii), there exists c_4 > 0 such that

    \zeta(\mathcal {L}_{G, h}\eta(z))\le e_2\mathcal {L}_{G, h} z+c_4\mathcal {L}_{G, h}, z\in \mathbb R^+.

    By the convexity of \zeta we have

    \begin{equation} \begin{aligned} \zeta(\phi_3(t)-w(t))& \le \zeta\left(\int_{0}^{1} G(t, s) h(s) \eta(\varphi_3(s)-w(s)) \mathrm{d} s\right)\\ & \le \int_{0}^{1} \zeta\left[ G(t, s) h(s) \eta(\varphi_3(s)-w(s))\right] \mathrm{d} s \\ & = \int_{0}^{1} \zeta\left[ \frac{G(t, s) h(s)}{\mathcal {L}_{G, h}} \mathcal {L}_{G, h}\eta(\varphi_3(s)-w(s))\right] \mathrm{d} s\\ & \le \int_{0}^{1} \frac{G(t, s) h(s)}{\mathcal {L}_{G, h}} \zeta\left[ \mathcal {L}_{G, h}\eta(\varphi_3(s)-w(s))\right] \mathrm{d} s\\ & \le \int_{0}^{1} \frac{G(t, s) h(s)}{\mathcal {L}_{G, h}} [e_2\mathcal {L}_{G, h} (\varphi_3(s)-w(s))+c_4\mathcal {L}_{G, h}] \mathrm{d} s\\ & \le \int_{0}^{1} G(t, s) h(s) [e_2 (\varphi_3(s)-w(s))+c_4] \mathrm{d} s . \end{aligned} \end{equation} (3.20)

    Substituting this inequality into (3.18) we have

    \begin{equation} \begin{aligned} \varphi_3(t)&\le \int_{0}^{1} G(t, s) h(s) \int_{0}^{1} G(s, \tau) h(\tau) [e_2 (\varphi_3(\tau)-w(\tau))+c_4] \mathrm{d} \tau \mathrm{d} s\\ & \le e_2 \int_{0}^{1} \int_{0}^{1} G(t, s) h(s) G(s, \tau) h(\tau) (\varphi_3(\tau)-w(\tau)) \mathrm{d} \tau \mathrm{d} s +c_4 \kappa_2^2 . \end{aligned} \end{equation} (3.21)

    Consequently, we have

    \begin{equation} \begin{aligned} \varphi_3(t)-w(t)&\le \int_{0}^{1} G(t, s) h(s) \int_{0}^{1} G(s, \tau) h(\tau) [e_2 (\varphi_3(\tau)-w(\tau))+c_4] \mathrm{d} \tau \mathrm{d} s\\ & \le e_2 \int_{0}^{1} \int_{0}^{1} G(t, s) h(s) G(s, \tau) h(\tau) (\varphi_3(\tau)-w(\tau)) \mathrm{d} \tau \mathrm{d} s +c_4 \kappa_2^2. \end{aligned} \end{equation} (3.22)

    Multiply by \vartheta(t) on both sides of (3.22) and integrate over [0, 1] and use Lemma 2.2 to obtain

    \int_0^1 (\varphi_3(t)-w(t))\vartheta(t)\mathrm{d} t\le e_2 \kappa_2^2 \int_0^1 (\varphi_3(t)-w(t))\vartheta(t)\mathrm{d} t+ c_4 \kappa_2^3,

    and we have

    \int_0^1 (\varphi_3(t)-w(t))\vartheta(t)\mathrm{d} t\le \frac{c_4 \kappa_2^3}{1-e_2 \kappa_2^2}.

    Note that (3.16), w\in P_0 , and

    \|\varphi_3-w\|\le \frac{c_4 \kappa_2^3}{\kappa_1(1-e_2 \kappa_2^2)}.

    By the triangle inequality we have

    \|\varphi_3\| = \|\varphi_3-w+w\|\le \|\varphi_3-w\|+\|w\|\le \frac{c_4 \kappa_2^3}{\kappa_1(1-e_2 \kappa_2^2)}+M\kappa_2.

    On the other hand, from (3.20) we have

    \begin{aligned} \zeta(\phi_3(t)-w(t))& \le \int_{0}^{1} G(t, s) h(s) [e_2 (\varphi_3(s)-w(s))+c_4] \mathrm{d} s \\ & \le \int_{0}^{1} \vartheta(s) [e_2 (\varphi_3(s)-w(s))+c_4] \mathrm{d} s \\ & \le \frac{c_4e_2 \kappa_2^3}{1-e_2 \kappa_2^2}+c_4\kappa_2 . \end{aligned}

    Note that \frac{c_4e_2 \kappa_2^3}{1-e_2 \kappa_2^2}+c_4\kappa_2 is independent to R , and using (H6)(i) there exists \mathcal {O}_{\phi_3} > 0 such that

    \|\phi_3-w\|\le \mathcal {O}_{\phi_3},

    and then

    \|\phi_3\| = \|\phi_3-w+w\|\le \|\phi_3-w\|+\|w\|\le \mathcal {O}_{\phi_3}+M\kappa_2.

    Therefore, when \varphi_3, \phi_3\in \partial B_R \cap P , we obtain there is a positive constant to control the norms of \varphi_3, \phi_3 . Then if we choose

    R_2 > \left\{\mathcal {O}_{M, h}, \mathcal {O}_{\phi_3}+M\kappa_2, \widetilde{M}, \frac{c_4 \kappa_2^3}{\kappa_1(1-e_2 \kappa_2^2)}+M\kappa_2 \right\},

    then (3.14) holds, and from Lemma 2.6 we have

    \begin{equation} i(A, B^2_{R_2}\cap P^2, P^2) = 1. \end{equation} (3.23)

    From (3.13) and (3.23) we have

    i(A, (B^2_{R_2}\backslash \overline{B}^2_{\mathcal {O}_{M, h}})\cap P^2, P^2) = i(A, B^2_{R_2}\cap P^2, P^2)- i(A, B^2_{\mathcal {O}_{M, h}}\cap P^2, P^2) = 1-0 = 1.

    Then the operator A has at least one fixed point (denoted by (u^{**}, v^{**}) ) on (B^2_{R_2}\backslash \overline{B}^2_{\mathcal {O}_{M, h}})\cap P^2 with u^{**}(t), v^{**}(t)\ge w(t), t\in [0, 1] . Therefore, (u^{**}-w, v^{**}-w) is a positive solution for (2.2), and (1.1) has at least one positive radial solution.

    We now provide some examples to illustrate our main results. Let \alpha = \beta = \gamma = \delta = 1, and k(|z|) = e^{|z|}, z\in \mathbb R^n . Then (H1) and (H2) hold.

    Example 3.1. Let p(\phi) = \phi^{\frac{4}{5}}, q(\varphi) = \varphi^2, \varphi, \phi\in \mathbb R^+ . Then \liminf_{z\to\infty}\frac{p(\mathcal {L}_{G, h}q(z))}{z} = \liminf_{z\to\infty}\frac{\mathcal {L}^{\frac{4}{5}}_{G, h}z^\frac{8}{5}}{z}\ge \infty , and (H4)(i), (iii) hold. If we choose

    f(\varphi, \phi) = \frac{1}{\beta_1\kappa_2(|\sin \varphi|+1)}\phi-M, \ g(\varphi, \phi) = \frac{\mathcal {O}^{1-\beta_3}_{M, h}}{\beta_2\kappa_2(|\cos \phi|+1)}\varphi^{\beta_3}-M, \beta_1, \beta_2 > 1, \beta_3 > 2,

    then (H3) holds, and when \varphi, \phi\in [0, \mathcal {O}_{M, h}] , we have

    \mathcal {F}_1(\varphi, \phi) = f(\varphi, \phi)+M\le \frac{\mathcal {O}_{M, h}}{\beta_1\kappa_2}: = Q_1, \ \mathcal {F}_2(\varphi, \phi) = g(\varphi, \phi)+M\le \frac{\mathcal {O}^{1-\beta_3}_{M, h}}{\beta_2\kappa_2}\mathcal {O}^{\beta_3}_{M, h} = \frac{\mathcal {O}_{M, h}}{\beta_2\kappa_2}: = Q_2.

    Hence, (H5) holds. Also we have

    \liminf\limits_{\phi\to \infty}\frac{f(\varphi, \phi)}{p(\phi)} = \liminf\limits_{\phi\to \infty}\frac{\frac{1}{\beta_1\kappa_2(|\sin \varphi|+1)}\phi-M}{\phi^{\frac{4}{5}}} = \infty, \ \liminf\limits_{\varphi\to \infty}\frac{g(\varphi, \phi)}{q(\varphi)} = \liminf\limits_{\varphi\to \infty}\frac{\frac{\mathcal {O}^{1-\beta_3}_{M, h}}{\beta_2\kappa_2(|\cos \phi|+1)}\varphi^{\beta_3}-M}{\varphi^2} = \infty.

    Then (H4)(ii) holds. As a result, all the conditions in Theorem 3.1 hold, and (1.1) has at least one positive radial solution.

    Example 3.2. Let \zeta(\phi) = \phi^2, \eta(\varphi) = \varphi^{\frac{2}{5}} , \varphi, \phi\in \mathbb R^+ . Then \limsup_{z\to\infty}\frac{\zeta(\mathcal {L}_{G, h}\eta(z))}{z} = \limsup_{z\to\infty}\frac{\mathcal {L}^2_{G, h}z^{\frac{4}{5}}}{z} = 0\le e_2\mathcal {L}_{G, h} , and (H7)(i), (iii) hold. If we choose

    f(\varphi, \phi) = \widetilde{Q}_{1}+\left(\phi+|\cos \varphi |\right)^{\alpha_{1}}-M, \ g(\varphi, \phi) = \widetilde{Q}_{2}+\left(|\sin \phi|+\varphi\right)^{\alpha_{2}}-M, \varphi, \phi \in \mathbb{R}^{+},

    where \alpha_{1} \in(0, 2), \alpha_{2} \in\left(0, \frac{2}{5}\right) . Then (H3) holds. Moreover, we have

    \mathcal{F}_{1}(\varphi, \phi) = f(\varphi, \phi)+M \geq \widetilde{Q}_{1}, \ \mathcal{F}_{2}(\varphi, \phi) = g(\varphi, \phi)+M \geq \widetilde{Q}_{2},

    and

    \limsup\limits _{\phi \rightarrow \infty} \frac{\widetilde{Q}_{1}-M+\left(\phi+|\cos \varphi |\right)^{\alpha_{1}}}{\phi^2} = 0, \limsup \limits_{\varphi \rightarrow \infty} \frac{\widetilde{Q}_{2}-M+\left(|\sin \phi|+\varphi\right)^{\alpha_{2}}}{\varphi^{\frac{2}{5}}} = 0.

    Therefore, (\mathrm{H} 6) and (\mathrm{H} 7) (ii) hold. As a result, all the conditions in Theorem 3.2 hold, and (1.1) has at least one positive radial solution.

    Remark 3.2. Note that condition (HZ)_2 is often used to study various kinds of semipositone boundary value problems (for example, see [19,22,23,26,28,29,30]). However, in Example 3.1 we have

    \liminf\limits _{\phi \to +\infty } \frac{f(\varphi, \phi)}{\varphi} = \liminf\limits _{\phi \to +\infty } \frac{\frac{1}{\beta_1\kappa_2(|\sin \varphi|+1)}\phi-M}{\phi} = \frac{1}{2\beta_1\kappa_2}, \forall \varphi\in \mathbb R^+.

    Comparing with (HZ)_2 we see that our theory gives new results for boundary value problem with semipositone nonlinearities.

    This research was supported by the National Natural Science Foundation of China (12101086), Changzhou Science and Technology Planning Project (CJ20210133), Natural Science Foundation of Chongqing (cstc2020jcyj-msxmX0123), and Technology Research Foundation of Chongqing Educational Committee (KJQN202000528).

    The authors declare no conflict of interest.



    [1] H. Modares, F. L. Lewis, Optimal tracking control of nonlinear partially-unknown constrained-input systems using integral reinforcement learning, Automatica, 50 (2014), 1780–1792. https://doi.org/10.1016/j.automatica.2014.05.011 doi: 10.1016/j.automatica.2014.05.011
    [2] B. Zhao, Y. Li, Model-free adaptive dynamic programming based near-optimal decentralized tracking control of reconfigurable manipulators, Int. J. Control, Autom. Syst., 16 (2018), 478–490. https://doi.org/10.1007/s12555-016-0711-5 doi: 10.1007/s12555-016-0711-5
    [3] T. Huang, D. Liu, A self-learning scheme for residential energy system control and management, Neural Comput. Appl., 22 (2013), 259–269. https://doi.org/10.1007/s00521-011-0711-6 doi: 10.1007/s00521-011-0711-6
    [4] M. Gluzman, J. G. Scott, A. Vladimirsky, Optimizing adaptive cancer therapy: dynamic programming and evolutionary game theory, Proc. Royal Soc. B: Biol. Sci., 287 (2020), 20192454. https://doi.org/10.1098/rspb.2019.2454 doi: 10.1098/rspb.2019.2454
    [5] I. Ha, E. Gilbert, Robust tracking in nonlinear systems, IEEE Trans. Automat. Control, 32 (1987), 763–771. https://doi.org/10.1109/TAC.1987.1104710 doi: 10.1109/TAC.1987.1104710
    [6] M. A. Rami, X. Y. Zhou, Linear matrix inequalities, Riccati equations and indefinite stochastic linear quadratic controls, IEEE Trans. Automat. Control, 45 (2000), 1131–1143. https://doi.org/10.1109/9.863597 doi: 10.1109/9.863597
    [7] R. Byers, Solving the algebraic Riccati equation with the matrix sign function, Linear Algebra Appl., 89 (1987), 267–279. https://doi.org/10.1016/0024-3795(87)90222-9 doi: 10.1016/0024-3795(87)90222-9
    [8] D. Vrabie, O. Pastravanu, M. Abu-Khalaf, F. L. Lewis, Adaptive optimal control for continuous-time linear systems based on policy iteration, Automatica, 45 (2009), 477–484. https://doi.org/10.1016/j.automatica.2008.08.017 doi: 10.1016/j.automatica.2008.08.017
    [9] B. Kiumarsi, F. L. Lewis, M. B. Naghibi-Sistani, A. Karimpour, Optimal tracking control of unknown discrete-time linear systems using input-output measured data, IEEE Trans. Cybern., 45 (2015), 2770–2779. https://doi.org/10.1109/TCYB.2014.2384016 doi: 10.1109/TCYB.2014.2384016
    [10] B. Kiumarsi, F. L. Lewis, H. Modares, A. Karimpour, M. B. Naghibi-Sistani, Reinforcement Q-learning for optimal tracking control of linear discrete-time systems with unknown dynamics, Automatica, 50 (2014), 1167–1175. https://doi.org/10.1016/j.automatica.2014.02.015 doi: 10.1016/j.automatica.2014.02.015
    [11] G. Wang, H. Zhang, Model-free value iteration algorithm for continuous-time stochastic linear quadratic optimal control problems, arXiv, 2022. https://doi.org/10.48550/arXiv.2203.06547
    [12] H. Zhang, Adaptive dynamic programming-based algorithm for infinite-horizon linear quadratic stochastic optimal control problems, arXiv, 2022. https://doi.org/10.48550/arXiv.2210.04486
    [13] R. Liu, Y. Li, X. Liu, Linear-quadratic optimal control for unknown mean-field stochastic discrete-time system via adaptive dynamic programming approach, Neurocomputing, 282 (2018), 16–24. https://doi.org/10.1016/j.neucom.2017.12.007 doi: 10.1016/j.neucom.2017.12.007
    [14] X. Chen, F. Wang, Neural-network-based stochastic linear quadratic optimal tracking control scheme for unknown discrete-time systems using adaptive dynamic programming, Control Theory Technol., 19 (2021), 315–327. https://doi.org/10.1007/s11768-021-00046-y doi: 10.1007/s11768-021-00046-y
    [15] Z. Zhang, X. Zhao, Stochastic linear quadratic optimal tracking control for stochastic discrete time systems based on Q-learning, J. Nanjing Univ. Inf. Sci. Technol. (Nat. Sci.), 13 (2021), 548–555.
    [16] Y. Liu, H. Zhang, Y. Luo, J. Han, ADP based optimal tracking control for a class of linear discrete-time system with multiple delays, J. Franklin Inst., 353 (2016), 2117–2136. https://doi.org/10.1016/j.jfranklin.2016.03.012 doi: 10.1016/j.jfranklin.2016.03.012
    [17] B. L. Zhang, Q. L. Han, X. M. Zhang, X. Yu, Sliding mode control with mixed current and delayed states for offshore steel jacket platforms, IEEE Trans. Control Syst. Technol., 22 (2014), 1769–1783. https://doi.org/10.1109/TCST.2013.2293401 doi: 10.1109/TCST.2013.2293401
    [18] M. J. Park, O. M. Kwon, J. H. Ryu, Advanced stability criteria for linear systems with time-varying delays, J. Franklin Inst., 355 (2018), 520–5433. https://doi.org/10.1016/j.jfranklin.2017.11.029 doi: 10.1016/j.jfranklin.2017.11.029
    [19] H. Zhang, Y. Luo, D. Liu, Neural-network-based near-optimal control for a class of discrete-time affine nonlinear systems with control constraints, IEEE Trans. Neural Networks, 20 (2009), 1490–1503. https://doi.org/10.1109/TNN.2009.2027233 doi: 10.1109/TNN.2009.2027233
    [20] H. Zhang, Z. Wang, D. Liu, Global asymptotic stability of recurrent neural networks with multiple time-varying delays, IEEE Trans. Neural Networks, 19 (2008), 855–873. https://doi.org/10.1109/TNN.2007.912319 doi: 10.1109/TNN.2007.912319
    [21] T. Wang, H. Zhang, Y. Luo, Infinite-time stochastic linear quadratic optimal control for unknown discrete-time systems using adaptive dynamic programming approach, Neurocomputing, 171 (2016), 379–386. https://doi.org/10.1016/j.neucom.2015.06.053 doi: 10.1016/j.neucom.2015.06.053
    [22] A. Garate-Garcia, L. A. Marquez-Martinez, C. H. Moog, Equivalence of linear time-delay systems, IEEE Trans. Automat. Control, 56 (2011), 666–670. https://doi.org/10.1109/TAC.2010.2095550 doi: 10.1109/TAC.2010.2095550
    [23] Y. Liu, R. Yu, Model-free optimal tracking control for discrete-time system with delays using reinforcement Q-learning, Electron. Lett., 54 (2018), 750–752. https://doi.org/10.1049/el.2017.3238 doi: 10.1049/el.2017.3238
    [24] H. Zhang, Q. Wei, Y. Luo, A novel infinite-time optimal tracking control scheme for a class of discrete-time nonlinear systems via the greedy HDP iteration algorithm, IEEE Trans. Syst., Man, Cybern. B, 38 (2008), 937–942. https://doi.org/10.1109/TSMCB.2008.920269 doi: 10.1109/TSMCB.2008.920269
    [25] J. Shi, D. Yue, X. Xie, Adaptive optimal tracking control for nonlinear continuous-time systems with time delay using value iteration algorithm, Neurocomputing, 396 (2020), 172–178. https://doi.org/10.1016/j.neucom.2018.07.098 doi: 10.1016/j.neucom.2018.07.098
    [26] Q. Wei, D. Liu, Adaptive dynamic programming for optimal tracking control of unknown nonlinear systems with application to coal gasification, IEEE Trans. Automat. Sci. Eng., 11 (2014), 1020–1036. https://doi.org/10.1109/TASE.2013.2284545 doi: 10.1109/TASE.2013.2284545
    [27] T. Wang, H. Zhang, Y. Luo, Stochastic linear quadratic optimal control for model-free discrete-time systems based on Q-learning algorithm, Neurocomputing, 312 (2018), 1–8. https://doi.org/10.1016/j.neucom.2018.04.018 doi: 10.1016/j.neucom.2018.04.018
    [28] F. L. Lewis, D. Vrabie, Reinforcement learning and adaptive dynamic programming for feedback control, IEEE Circuits Syst. Mag., 9 (2009), 32–50. https://doi.org/10.1109/MCAS.2009.933854 doi: 10.1109/MCAS.2009.933854
  • This article has been cited by:

    1. Ala Amourah, Abdullah Alsoboh, Daniel Breaz, Sheza M. El-Deeb, A Bi-Starlike Class in a Leaf-like Domain Defined through Subordination via q̧-Calculus, 2024, 12, 2227-7390, 1735, 10.3390/math12111735
  • Reader Comments
  • © 2023 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(1994) PDF downloads(149) Cited by(1)

Figures and Tables

Figures(4)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog