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Research article Special Issues

Sequential adaptive switching time optimization technique for maximum hands-off control problems

  • Received: 11 January 2024 Revised: 01 March 2024 Accepted: 13 March 2024 Published: 19 March 2024
  • In this paper, we consider maximum hands-off control problem governed by a nonlinear dynamical system, where the maximum hands-off control constraint is characterized by an L0 norm. For this problem, we first approximate the L0 norm constraint by a L1 norm constraint. Then, the control parameterization together with sequential adaptive switching time optimization technique is proposed to approximate the optimal control problem by a sequence of finite-dimensional optimization problems. Furthermore, a smoothing technique is exploited to approximate the non-smooth maximum operator and an error analysis is investigated for this approximation. The gradients of the cost functional with respect to the decision variables in the approximate problem are derived. On the basis of these results, we develop a gradient-based optimization algorithm to solve the resulting optimization problem. Finally, an example is solved to demonstrate the effectiveness of the proposed algorithm.

    Citation: Sida Lin, Lixia Meng, Jinlong Yuan, Changzhi Wu, An Li, Chongyang Liu, Jun Xie. Sequential adaptive switching time optimization technique for maximum hands-off control problems[J]. Electronic Research Archive, 2024, 32(4): 2229-2250. doi: 10.3934/era.2024101

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  • In this paper, we consider maximum hands-off control problem governed by a nonlinear dynamical system, where the maximum hands-off control constraint is characterized by an L0 norm. For this problem, we first approximate the L0 norm constraint by a L1 norm constraint. Then, the control parameterization together with sequential adaptive switching time optimization technique is proposed to approximate the optimal control problem by a sequence of finite-dimensional optimization problems. Furthermore, a smoothing technique is exploited to approximate the non-smooth maximum operator and an error analysis is investigated for this approximation. The gradients of the cost functional with respect to the decision variables in the approximate problem are derived. On the basis of these results, we develop a gradient-based optimization algorithm to solve the resulting optimization problem. Finally, an example is solved to demonstrate the effectiveness of the proposed algorithm.



    Calculus is a branch of mathematics which helps us to study the derivatives and integrals. The classical derivative was convoluted with the strength regulation kind kernel and eventually, this gave upward thrust to new calculus referred to as the quantum calculus. Quantum calculus (named q-calculus) is the study of calculus without limits. In recent decades, the quantum calculus has become a powerful tool in numerous branches of mathematics and physics like q-calculus, particularly q-fractional calculus, q-integral calculus, q-transform analysis. Jackson [1] is the first researcher to define the q-analogue of derivative and integral operator as well as provided its applications. It is imperative to mention that quantum integral inequalities are more practical and informative than their classical counterparts. It has been mainly due to the fact that quantum integral inequalities can describe the hereditary properties of the processes and phenomena under investigation. Historically the subject of quantum calculus can be traced back to Euler and Jacobi, but in recent decades it has experienced a rapid development, see [2,3,4,5,6,7]. As a result, new generalizations of the classical concepts of quantum calculus have been initiated and reviewed in many literature. Tariboon and Ntouyas [8,9] proposed the quantum calculus concepts on finite intervals and obtained several q-analogues of classical mathematical objects. This inspired other researchers to establish numerous novel results concerning quantum analogs of classical mathematical results. Noor et al. [10] provided the q-analogues of many known inequalities via the first order q-differentiable convex functions. Humaira et al. [11] obtained a new generalized q1q2-integral identity and established several new q1q2-analogues of first order q1q2-differentiable convex functions over finite rectangles. Wu et al. [12] gave a new corrected q-analogue of the classical Simpson inequality for preinvex function. Deng et al. [13] obtained a new generalized q-integral identity and found several new q-analogues for twice q-differentiable generalized (s,m)-preinvex functions.

    The theory of post quantum calculus denoted by (p,q)-calculus is a natural generalization of the quantum calculus denoted by q-calculus, which has been studied extensively. Recently, Tunç and Göv [14] studied the concept of (p,q)-calculus on the intervals [χ1,χ2]R, defined the (p,q)-derivative and (p,q)-integral and established their basic properties and integral inequalities. Integral inequalities [15,16,17,18,19,20,21,22,23,24,25,26,27] play an important role in understanding the universe, and they can be used to find the uniqueness and existence of the linear and nonlinear differential equations. While convexity is an indispensable tool in the study of inequality theory [28,29,30,31,32,33,34,35,36,37,38].

    It is well-known that the Hermite-Hadamard inequality [39,40,41,42,43] is one of the most important inequalities in the convex functions theory, which can be stated as follows.

    Let K:IRR be a convex function. Then the double inequality

    K(χ1+χ22)1χ2χ1χ2χ1K(t)dtK(χ1)+K(χ2)2 (1.1)

    holds for all χ1,χ2I with χ1χ2.

    As the generalization and refinement of the Hermite-Hadamard inequality (1.1), the Ostrowski inequality [44] can be stated in Theorem 1.1.

    Theorem 1.1. Let K:[χ1,χ2]RR be continuous on [χ1,χ2] and differentiable on (χ1,χ2) such that |K(τ)|M for all τ(χ1,χ2). Then the inequality

    |K(ϱ)1χ2χ1χ2χ1K(τ)dτ|[14+(ϱχ1+χ22)2(χ2χ1)2](χ2χ1)M (1.2)

    holds for all ϱ[χ1,χ2] with the best possible constant 14.

    Inequality (1.2) can be rewritten in its equivalent form

    |K(ϱ)1χ2χ1χ2χ1K(τ)dτ|Mχ2χ1[(ϱχ1)2+(χ2ϱ)22].

    Recently, the generalizations, variants and applications of the Ostrowski inequality have attracted the attention of many researchers.

    Now, we discuss some connections between the class of convex functions and s-type convex functions.

    Definition 1.2. Let s[0,1]. Then the function K:IR is said to be a s-type convex function on I if the inequality

    K(χϱ+(1χ)ρ)[1s(1χ)]K(ϱ)+[1sχ]K(ρ) (1.3)

    holds for all ϱ,ρI and χ[0,1].

    Remark 1. Definition 1.2 leads to the conclusion that

    (1) If we choose s=1, then we get classical convex function.

    (2) If we take s=0, then we have the definition of P-function [45].

    (3) If K is s-type convex function on I, then the range of K is [0,).

    Indeed, let ϱI. Then it follows from the s-type convexity of K that

    K(χη1+(1χ)ϱ)[1s(1χ)]K(η1)+[1sχ]K(ϱ)

    for all η1I and χ[0,1]. If we choose χ=1, then we get

    K(η1)K(η1)+(1s)K(ϱ)
    (1s)K(ρ)0K(ϱ)0

    for all ϱI.

    Proposition 1. Every non-negative convex function is also s-type convex function.

    Proof. The proof is clearly due to

    s(1χ)(1χ),χsχ

    for all χ[0,1] and s[0,1].

    Next, We recall the definition of n-polynomial s-type convex function.

    Definition 1.3. Let s[0,1] and nN. Then the function K:IR is said to be a n-polynomial s-type convex function on I if the inequality

    K(χϱ+(1χ)ρ)1nni=1[1(s(1χ))i]K(ϱ)+1nni=1[1(sχ)i]K(ρ) (1.4)

    holds for ϱ,ρI and χ[0,1].

    Remark 2. From Definition 1.3, one has

    (1) If we choose s=0, then we get the P-function [45].

    (2) If we take s=1, then we obtain the Definition given in [46].

    (3) If we choose n=1, then we obtain Definition 1.2.

    (4) If K is a n-polynomial s-type convex function, then the range of K is [0,).

    Remark 3. Every non-negative n-polynomial convex function is also n-polynomial s-type convex function. Indeed

    1nni=1[1(s(1χ))i]1nni=1[1(1χ)i]

    and

    1nni=1[1χi]1nni=1[1(sχ)i]

    for all χ[0,1],nN and s[0,1].

    In what follows, we suppose that χ1,χ2,χ3,χ4R with χ1<χ2 and χ3<χ4, 0<qk<pk1(k=1,2) are constants, N=[χ1,χ2]×[χ3,χ4]R2 is a rectangle and N=(χ1,χ2)×(χ3,χ4) is the interior of N.

    Definition 1.4. Let K:NR be a continuous function. Then the partial (p1,q1)-, (p2,q2)- and (p1p2,q1q2)-derivatives at (z,w)N are respectively defined by

    χ1p1,q1K(z,w)χ1p1,q1z=K(p1z+(1p1)χ1,w)K(q1z+(1q1)χ1,w)(p1q1)(zχ1)(zχ1),χ3p2,q2K(z,w)χ3p2,q2w=K(z,p2w+(1p2)χ3)K(z,q2w+(1q2)χ3)(p2q2)(wχ3)(wχ3),χ1,χ32p1p2,q1q2K(z,w)χ1p1,q1zχ3p2,q2w=1(p1q1)(p2q2)(zχ1)(wχ3)[K(q1z+(1q1)χ1,q2w+(1q2)χ3)K(q1z+(1q1)χ1,p2w+(1p2)χ3)K(p1z+(1p1)χ1,q2w+(1q2)χ3)+K(p1z+(1p1)χ1,p2w+(1p2)χ3)].

    Definition 1.5. Let K:NR be a continuous function. Then the definite (p1p2,q1q2)-integral on N is defined by

    tχ3sχ1K(z,w)χ1dp1,q1zχ3dp2,q2w=(p1q1)(p2q2)(sχ1)(tχ3)×m=0n=0qn1qm2pn+11pm+12K(qn1pn+11s+(1qn1pn+11)χ1,qm2pm+12t+(1qm2pm+12)χ3) (1.5)

    for (s,t)N.

    Definition 1.6. For any real number n, the (p,q)-analogue is defined by

    [n]p,q=pnqnpq,

    where 0<q<p1 are constants.

    In the present paper, we introduce new Definitions 1.7 and 1.8 for (p1p2,q1q2)-differentiable function, and (p,q)χ4χ1,(p,q)χ2χ3 and (p,q)χ2,χ4 integrals for two variables mappings over finite rectangles by using convex set. These new definitions will open new doors for convexity and (p,q)-calculus for two variables functions over the finite rectangles in the plane R2. We drive a key lemma for (p1p2,q1q2)-integral. By making use of new identity, we will obtain estimates of integral inequality whose twice partial (p1p2,q1q2)-derivatives in absolute value at certain powers are n-polynomial s-type convex function. We also discuss some new special cases of the main results. A briefly conclusion is given at the end.

    Definition 1.7. Let K:NR be a continuous function. Then the partial (p1,q1)-, (p2,q2)- and (p1p2,q1q2)-derivatives at (z,w)N are respectively defined by

    χ2p1,q1K(z,w)χ2p1,q1z=K(p1z+(1p1)χ2,w)K(q1z+(1q1)χ2,w)(p1q1)(χ2z)(χ2z),χ4p2,q2K(z,w)χ4p2,q2w=K(z,p2w+(1p2)χ4)K(z,q2w+(1q2)χ4)(p2q2)(χ4w)(χ4w),χ4χ12p1p2,q1q2K(z,w)χ1p1,q1zχ4p2,q2w=1(p1q1)(p2q2)(zχ1)(χ4w)[K(q1z+(1q1)χ1,q2w+(1q2)χ4)K(q1z+(1q1)χ1,p2w+(1p2)χ4)K(p1z+(1p1)χ1,q2w+(1q2)χ4)+K(p1z+(1p1)χ1,p2w+(1p2)χ4)](zχ1,χ4w),χ2χ32p1p2,q1q2K(z,w)χ2p1,q1zχ3p2,q2w=1(p1q1)(p2q2)(χ2z)(wχ3)[K(q1z+(1q1)χ2,q2w+(1q2)χ3)K(q1z+(1q1)χ2,p2w+(1p2)χ3)K(p1z+(1p1)χ2,q2w+(1q2)χ3)+K(p1z+(1p1)χ2,p2w+(1p2)χ3)](χ2z,wχ3),χ2,χ42p1p2,q1q2K(z,w)χ2p1,q1zχ4p2,q2w=(p1q1)(p2q2)(χ2z)(χ4w)[K(q1z+(1q1)χ2,q2w+(1q2)χ4)K(q1z+(1q1)χ2,p2w+(1p2)χ4)K(p1z+(1p1)χ2,q2w+(1q2)χ4)+K(p1z+(1p1)χ2,p2w+(1p2)χ4)](χ2z,χ4w).

    Definition 1.8. Let K:NR be a continuous function. Then the definite (p,q)χ4χ1,(p,q)χ2χ3 and (p,q)χ2,χ4 integrals on [χ1,χ2]×[χ3,χ4] are respectively defined by

    χ4tsχ1K(z,w)χ1dp1,q1zχ3dp2,q2w=(p1q1)(p2q2)(sχ1)(χ4t)×m=0n=0qn1qm2pn+11pm+12K(qn1pn+11s+(1qn1pn+11)χ1,qm2pm+12t+(1qm2pm+12)χ4),
    tχ3χ2sK(z,w)χ2dp1,q1zχ3dp2,q2w(p1q1)(p2q2)(χ2s)(tχ3)×m=0n=0qn1qm2pn+11pm+12K(qn1pn+11s+(1qn1pn+11)χ2,qm2pm+12t+(1qm2pm+12)χ3)

    and

    χ4tχ2sK(z,w)χ2dp1,q1zχ4dp2,q2w(p1q1)(p2q2)(χ2s)(χ4t)×m=0n=0qn1qm2pn+11pm+12K(qn1pn+11s+(1qn1pn+11)χ2,qm2pm+12t+(1qm2pm+12)χ4)

    for (s,t)[χ1,χ2]×[χ3,χ4].

    Lemma 2.1. Let K:NR be a twice partial (p1p2,q1q2)-differentiable function on No such that the partial (p1p2,q1q2)-derivatives χ1,χ32p1p2,q1q2K(z,w)χ1p1,q1zχ3p2,q2w, χ4χ12p1p2,q1q2K(z,w)χ1p1,q1zχ4p2,q2w, χ2χ32p1p2,q1q2K(z,w)χ2p1,q1zχ3p2,q2w and χ2,χ42p1p2,q1q2K(z,w)χ2p1,q1zχ4p2,q2w are continuous and integrable on N. Then one has the equality

    K(ϱ,ρ)1p1(χ2χ1)[p1ϱ+(1p1)χ1χ1K(u,ρ)χ1dp1,q1u+χ2p1ϱ+(1p1)χ2K(u,ρ)χ2dp1,q1u]1p2(χ4χ3)[p2ρ+(1p2)χ3χ3K(ϱ,v)χ3dp2,q2v+χ4p2ρ+(1p2)χ4K(ϱ,v)χ4dp2,q2v]+A=Δ{(ϱχ1)2(ρχ3)21010zwχ1,χ32p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w0dp1,q1z0dp2,q2w+(ϱχ1)2(χ4ρ)21010zwχ4χ12p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ4)χ1p1,q1zχ4p2,q2w0dp1,q1z0dp2,q2w+(χ2ϱ)2(ρχ3)21010zwχ2χ32p1p2,q1q2K(zϱ+(1z)χ2,wρ+(1w)χ3)χ3p1,q1zχ2p2,q2w0dp1,q1z0dp2,q2w+(χ2ϱ)2(χ4ρ)21010zwχ2,χ42p1p2,q1q2K(zϱ+(1z)χ2,wρ+(1w)χ4)χ2p1,q1zχ4p2,q2w0dp1,q1z0dp2,q2w}, (2.1)

    where

    A=1p1p2(χ2χ1)(χ4χ3)p1ϱ+(1p1)χ1χ1p2ρ+(1p2)χ3χ3K(u,v)χ1dp1,q1uχ3dp2,q2v+1p1p2(χ2χ1)(χ4χ3)p1ϱ+(1p1)χ1χ1χ4p2ρ+(1p2)χ4K(u,v)χ1dp1,q1uχ4dp2,q2v+1p1p2(χ2χ1)(χ4χ3)χ2p1ϱ+(1p1)χ2p2ρ+(1p2)χ3χ3K(u,v)χ2dp1,q1uχ3dp2,q2v+1p1p2(χ2χ1)(χ4χ3)χ2p1ϱ+(1p1)χ2χ4p2ρ+(1p2)χ4K(u,v)χ2dp1,q1uχ4dp2,q2v

    for all ϱ,ρN and Δ=q1q2(χ2χ1)(χ4χ3).

    Proof. We consider the integral

    1010zwχ1,χ32p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w0dp1,q1z0dp2,q2w.

    By the definition of partial (p1p2,q1q2)-derivative and definite (p1p2,q1q2)χ1,χ3-integral, we have

    1010zwχ1,χ32p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w0dp1,q1z0dp2,q2w=1(1q1)(1q2)(ϱχ1)(ρχ3)×[1010K(zq1ϱ+(1zq1)χ1,wq2ρ+(1wq2)χ3)0dp1,q1z0dp2,q2w1010K(zq1ϱ+(1zq1)χ1,wp2ρ+(1wp2)χ3)0dp1,q1z0dp2,q2w1010K(zp1ϱ+(1zp1)χ1,wq2ρ+(1wq2)χ3)0dp1,q1z0dp2,q2w+1010K(zp1ϱ+(1zp1)χ1,wp2ρ+(1wp2)χ3)0dp1,q1z0dp2,q2w]=1(ϱχ1)(ρχ3)×[n=0m=0qn1qm2pn+11pm+12K(qn+11pn+11ϱ+(1qn+11pn+11)χ1,qm+12pm+12ρ+(1qm+12pm+12)χ3)n=0m=0qn1qm2pn+11pm+12K(qn+11pn+11ϱ+(1qn+11pn+11)χ1,qm2pm2ρ+(1qm2pm2)χ3)n=0m=0qn1qm2pn+11pm+12K(qn1pn+11ϱ+(1qn1pn+11)χ1,qm+12pm+12ρ+(1qm+12pm+12)χ3)+n=0m=0qn1qm2pn+11pm+12K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3)]=1q1q2(ϱχ1)(ρχ3)n=1m=1qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3)1p2q1(ϱχ1)(ρχ3)n=1m=0qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3)1p1q2(ϱχ1)(ρχ3)n=0m=1qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3)+1p1p2(ϱχ1)(ρχ3)n=0m=0qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3). (2.2)

    Note that

    1q1q2(ϱχ1)(ρχ3)n=1m=1qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3)=K(ϱ,ρ)q1q2(ϱχ1)(ρχ3)1q1q2(ϱχ1)(ρχ3)n=0qn1pn1K(qn1pn1ϱ+(1qn1pn1)χ1,ρ)1q1q2(ϱχ1)(ρχ3)m=0qm2pm2K(ϱ,qm2pm2ρ+(1qm2pm2)χ3)+1q1q2(ϱχ1)(ρχ3)×n=0m=0qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3), (2.3)
    1p2q1(ϱχ1)(ρχ3)n=1m=0qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3)=1p2q1(ϱχ1)(ρχ3)m=0qm2pm2K(ϱ,qm2pm2ρ+(1qm2pm2)χ3)1p2q1(ϱχ1)(ρχ3)×n=0m=0qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3) (2.4)

    and

    1p1q2(ϱχ1)(ρχ3)n=0m=1qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3)=1p1q2(ϱχ1)(ρχ3)n=0qn1pn1K(qn1pn1ϱ+(1qn1pn1)χ1,ρ)1p1q2(ϱχ1)(ρχ3)×n=0m=0qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3). (2.5)

    Utilizing (2.3)–(2.5) in (2.2), we get

    1010zwχ1,χ32p1p2,q1q2χ1p1,q1zχ3p2,q2wK(zϱ+(1z)χ1,wρ+(1w)χ3)0dp1,q1z0dp2,q2w=K(ϱ,ρ)q1q2(ϱχ1)(ρχ3)(p2q2)(ρχ3)p2q1q2(ϱχ1)(ρχ3)2m=0qm2pm2K(ϱ,qm2pm2ρ+(1qm2pm2)χ3)(p1q1)(ϱχ1)p1q1q2(ϱχ1)2(ρχ3)n=0qn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,ρ)+(p1q1)(p2q2)(ϱχ1)(ρχ3)p1p2q1q2(ϱχ1)2(ρχ3)2n=0m=0qn1qm2pn1pm2K(qn1pn1ϱ+(1qn1pn1)χ1,qm2pm2ρ+(1qm2pm2)χ3)

    and

    1010zwχ1,χ32p1p2,q1q2χ1p1,q1zχ3p2,q2wK(zϱ+(1z)χ1,wρ+(1w)χ3)0dp1,q1z0dp2,q2w=K(ϱ,ρ)q1q2(ϱχ1)(ρχ3)1p2q1q2(ϱχ1)(ρχ3)2p2ρ+(1p2)χ3χ3K(ϱ,v)0dp2,q2v1p1q1q2(ϱχ1)2(ρχ3)p1ϱ+(1p1)χ1χ1K(u,ρ)0dp1,q1u+1p1p2q1q2(ϱχ1)2(ρχ3)2p1ϱ+(1p1)χ1χ1p2ρ+(1p2)χ3χ3K(u,v)0dp1,q1u0dp2,q2v. (2.6)

    Multiplying both sides of equality (2.6) by Δ(ϱχ1)2(ρχ3)2 leads to

    Δ(ϱχ1)2(ρχ3)21010zwχ1,χ32p1p2,q1q2χ1p1,q1zχ3p2,q2wK(zϱ+(1z)χ1,wρ+(1w)χ3)0dp1,q1z0dp2,q2w=(ϱχ1)(ρχ3)(χ2χ1)(χ4χ3)K(ϱ,ρ)ϱχ1p2(χ2χ1)(χ4χ3)p2ρ+(1p2)χ3χ3K(ϱ,v)0dp2,q2vρχ3p1(χ2χ1)(χ4χ3))p1ϱ+(1p1)χ1χ1K(u,ρ)0dp1,q1u+1p1p2(χ2χ1)(χ4χ3)p1ϱ+(1p1)χ1χ1p2ρ+(1p2)χ3χ3K(u,v)0dp1,q1u0dp2,q2v. (2.7)

    Similarly, calculating the remaining integrals and by using definition 1.8 we get

    Δ(ϱχ1)2(χ4ρ)21010zwχ4χ12p1p2,q1q2χ1p1,q1zχ4p2,q2wK(zϱ+(1z)χ1,wρ+(1w)χ4)0dp1,q1z0dp2,q2w=(ϱχ1)(χ4ρ)(χ2χ1)(χ4χ3)K(ϱ,ρ)ϱχ1p2(χ2χ1)(χ4χ3)χ4p2ρ+(1p2)χ4K(ϱ,v)χ4dp2,q2vχ4ρp1(χ2χ1)(χ4χ3))p1ϱ+(1p1)χ1χ1K(u,ρ)χ1dp1,q1u+1p1p2(χ2χ1)(χ4χ3)p1ϱ+(1p1)χ1χ1χ4p2ρ+(1p2)χ4K(u,v)χ1dp1,q1uχ4dp2,q2v, (2.8)
    Δ(χ2ϱ)2(ρχ3)21010zwχ2χ32p1p2,q1q2χ2p1,q1zχ3p2,q2wK(zϱ+(1z)χ1,wρ+(1w)χ3)0dp1,q1z0dp2,q2w=(χ2ϱ)(ρχ3)(χ2χ1)(χ4χ3)K(ϱ,ρ)χ2ϱp2(χ2χ1)(χ4χ3)p2ρ+(1p2)χ3χ3K(ϱ,v)χ3dp2,q2vρχ3p1(χ2χ1)(χ4χ3))χ2p1ϱ+(1p1)χ2K(u,ρ)χ2dp1,q1u+1p1p2(χ2χ1)(χ4χ3)p1ϱ+(1p1)χ1χ2χ2p2ρ+(1p2)χ2K(u,v)χ2dp1,q1uχ3dp2,q2v, (2.9)
    Δ(χ2ϱ)2(χ4ρ)21010zwχ2,χ42p1p2,q1q2χ2p1,q1zχ4p2,q2wK(zϱ+(1z)χ2,wρ+(1w)χ4)0dp1,q1z0dp2,q2w=(χ2ϱ)(χ4ρ)(χ2χ1)(χ4χ3)K(ϱ,ρ)χ2ϱp2(χ2χ1)(χ4χ3)χ4p2ρ+(1p2)χ4K(ϱ,v)χ4dp2,q2vχ4ρp1(χ2χ1)(χ4χ3))χ2p1ϱ+(1p1)χ2K(u,ρ)χ2dp1,q1u+1p1p2(χ2χ1)(χ4χ3)χ4p1ϱ+(1p1)χ2χ4p2ρ+(1p2)χ4K(u,v)χ2dp1,q1uχ4dp2,q2v. (2.10)

    From (2.7)–(2.10) and (2.1), we derive the desired result of Lemma 2.1.

    Remark 4. Taking pk=1 for k=1,2 we get

    K(ϱ,ρ)1(χ2χ1)[ϱχ1K(u,ρ) χ1dq1u+χ2ϱK(u,ρ) χ2dq1u]1(χ4χ3)[ρχ3K(ϱ,v) χ3dq2v+χ4ρK(ϱ,v) χ4dq2v]+W=Δ{(ϱχ1)2(ρχ3)21010zw χ1,χ32q1,q2K(zϱ+(1z)χ1,wρ+(1w)χ3) χ1q1z χ3q2w 0dq1z 0dq2w+(ϱχ1)2(χ4ρ)21010zw χ4χ12q1,q2K(zϱ+(1z)χ1,wρ+(1w)χ4) χ1q1z χ4q2w 0dq1z 0dq2w+(χ2ϱ)2(ρχ3)21010zw χ2χ32q1,q2K(zϱ+(1z)χ2,wρ+(1w)χ3) χ3q1z χ2q2w 0dq1z 0dq2w+(χ2ϱ)2(χ4ρ)21010zw χ2,χ42q1,q2K(zϱ+(1z)χ2,wρ+(1w)χ4) χ2q1z χ4q2w 0dq1z 0dq2w}, (2.11)

    where

    W=1(χ2χ1)(χ4χ3)ϱχ1ρχ3K(u,v)χ1dq1uχ3dq2v+1(χ2χ1)(χ4χ3)ϱχ1χ4ρK(u,v)χ1dq1uχ4dq2v+1(χ2χ1)(χ4χ3)χ2ϱρχ3K(u,v)χ2dq1uχ3dq2v+1(χ2χ1)(χ4χ3)χ2ϱχ4ρK(u,v)χ2dq1uχ4dq2v.

    In this section, we introduce (p1p2,q1q2)-Ostrowski inequalities by using n-polynomial s-type convex function on the co-ordinates.

    Theorem 3.1. Suppose that nN, s[0,1] and all the assumptions of Lemma 2.1 are true. If |χ1,χ32p1p2,q1q2K(z,w)χ1p1,q1zχ3p2,q2w|τ2, |χ4χ12p1p2,q1q2K(z,w)χ1p1,q1zχ4p2,q2w|τ2, |χ2χ32p1p2,q1q2K(z,w)χ2p1,q1zχ3p2,q2w|τ2 and |χ2,χ42p1p2,q1q2K(z,w)χ2p1,q1zχ4p2,q2w|τ2 are n-polynomial s-type convex functions on the co-ordinates on N for τ1,τ2>1 with 1τ1+1τ2=1 and |χ1,χ32p1p2,q1q2K(ϱ,ρ)χ1p1,q1zχ3p2,q2w|M, |χ4χ12p1p2,q1q2K(z,w)χ1p1,q1zχ4p2,q2w|M, |χ2χ32p1p2,q1q2K(z,w)χ2p1,q1zχ3p2,q2w|M, |χ2,χ42p1p2,q1q2K(z,w)χ2p1,q1zχ4p2,q2w|M, ϱ,ρN, then the following inequality holds

    |K(ϱ,ρ)1p1(χ2χ1)[p1ϱ+(1p1)χ1χ1K(u,ρ)χ1dp1,q1u+χ2p1ϱ+(1p1)χ2K(u,ρ)χ2dp1,q1u]1p2(χ4χ3)[p2ρ+(1p2)χ3χ3K(ϱ,v)χ3dp2,q2v+χ4p2ρ+(1p2)χ4K(ϱ,v)χ4dp2,q2v]+A|ΔMτ2(Cp1,q1+Dp1,q1)(Cp2,q2+Dp2,q2)[(ϱχ1)2+(χ2ϱ)2][(ρχ3)2+(χ4ρ)2]τ1[1+τ1]p1,q1[1+τ1]p2,q2, (3.1)

    where

    Cpk,qk=1(pkqk)nni=1e=0siqekpe+1k(1qekpe+1k)i,Dpk,qk=11nni=1si(pkqkpi+1kqi+1k)

    for k=1,2 and Δ,A are defined in Lemma 2.1.

    Proof. Taking absolute value on both sides of (2.1), by applying Hölder inequality for double integrals and utilizing the fact that |2p1p2,q1q2Kp1,q1zp2,q2w|τ2 is n-polynomial s-type convex on co-ordinates, we get the following inequality

    |K(ϱ,ρ)1p1(χ2χ1)[p1ϱ+(1p1)χ1χ1K(u,ρ)χ1dp1,q1u+χ2p1ϱ+(1p1)χ2K(u,ρ)χ2dp1,q1u]1p2(χ4χ3)[p2ρ+(1p2)χ3χ3K(ϱ,v)χ3dp2,q2v+χ4p2ρ+(1p2)χ4K(ϱ,v)χ4dp2,q2v]+A|Δ(1010zτ1wτ10dp1,q1z0dp2,q2w)1τ1×{(ϱχ1)2(ρχ3)2(1010|χ1,χ32p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ20dp1,q1z0dp2,q2w)1τ2
    +(ϱχ1)2(χ4ρ)2(1010|χ4χ12p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ4)χ1p1,q1zχ4p2,q2w|τ20dp1,q1z0dp2,q2w)1τ2+(χ2ϱ)2(ρχ3)2(1010|χ2χ32p1p2,q1q2K(zϱ+(1z)χ2,wρ+(1w)χ3)χ2p1,q1zχ3p2,q2w|τ20dp1,q1z0dp2,q2w)1τ2+(χ2ϱ)2(χ4ρ)2(1010|χ2,χ42p1p2,q1q2K(zϱ+(1z)χ2,wρ+(1w)χ4)χ2p1,q1zχ4p2,q2w|τ20dp1,q1z0dp2,q2w)1τ2}.

    Considering first integral

    1010|χ1,χ32p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ20dp1,q1z0dp2,q2w10{10[1nni=1[1(s(1z))i]|χ1,χ32p1p2,q1q2K(ϱ,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ2+1nni=1[1(sz)i]|χ1,χ32p1p2,q1q2K(χ1,wρ+(1w)χ3)χ1p1,q1zχ1p2,q2w|τ2]0dp1,q1z}0dp2,q2w. (3.2)

    Computing the (p1,q1)-integral on the right-hand side of (3.2), we have

    10[1nni=1[1(s(1z))i]|χ1,χ32p1p2,q1q2K(ϱ,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ2+1nni=1[1(sz)i]|χ1,χ32p1p2,q1q2K(χ1,wρ+(1w)χ3)χ1p1,q1zχ1p2,q2w|τ2]0dp1,q1z.

    In view of the Definitions 1.4 for k=1,2, we get

    Cpk,qk=1nni=110[1(s(1z))i]0dpk,qkz=1(pkqk)nni=1e=0siqekpe+1k(1qekpe+1k)i,Dpk,qk=1nni=110[1(sz)i]0dpk,qkz=11nni=1si(pkqkpi+1kqi+1k).

    Putting the above calculations into (3.2), we obtain

    10[Cp1,q1|χ1,χ32p1p2,q1q2K(ϱ,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ2+Dp1,q1|χ1,χ32p1p2,q1q2K(χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ2]0dp2,q2w. (3.3)

    Similarly, by computing the (p2,q2)-integral, utilizing the fact |χ1,χ32p1p2,q1q2K(ϱ,ρ)χ1p1,q1zχ3p2,q2w|M,ϱ,ρN on the right-hand side of (3.3), we have

    1010|χ1,χ32p1p2,q1q2K(zϱ+(1w)χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ20dp1,q1z0dp2,q2wMτ2(Cp1,q1+Dp1,q1)(Cp2,q2+Dp2,q2). (3.4)

    Analogously, we get

    1010|χ4χ12p1p2,q1q2K(zϱ+(1w)χ1,χ4+wρ+(1w)χ4)χ1p1,q1zχ4p2,q2w|τ20dp1,q1z0dp2,q2wMτ2(Cp1,q1+Dp1,q1)(Cp2,q2+Dp2,q2) (3.5)
    1010|χ2χ32p1p2,q1q2K(zϱ+(1z)χ2,wρ+(1w)χ3)χ2p1,q1zχ3p2,q2w|τ20dp1,q1z0dp2,q2wMτ2(Cp1,q1+Dp1,q1)(Cp2,q2+Dp2,q2) (3.6)

    and

    1010|χ2,χ42p1p2,q1q2K(zϱ+(1z)χ2,χ4+wρ+(1w)χ4)χ2p1,q1zχ4p2,q2w|τ20dp1,q1z0dp2,q2wMτ2(Cp1,q1+Dp1,q1)(Cp2,q2+Dp2,q2). (3.7)

    Now by making use of the inequalities (3.4)(3.7) and using the fact that

    1010zτ1wτ10dp1,q1z0dp2,q2w=1[1+τ1]p1,q1[1+τ1]p2,q2,

    we get the desired inequality (3.1). This completes the proof.

    Corollary 1. I. Taking pk=1 for k=1,2 in Theorem 3.1, we get

    |K(ϱ,ρ)1(χ2χ1)[ϱχ1K(u,ρ)χ1dq1u+χ2ϱK(u,ρ)χ2dq1u]1(χ4χ3)[ρχ3K(ϱ,v)χ3dq2v+χ4ρK(ϱ,v)χ4dq2v]+W|ΔMτ2(Cq1+Dq1)(Cq2+Dq2)[(ϱχ1)2+(χ2ϱ)2][(ρχ3)2+(χ4ρ)2]τ1[1+τ1]q1[1+τ1]q2,

    where

    Cqk=1(1qk)nni=1e=0siqek(1qek)i,Dqk=11nni=1si(1qk1qi+1k)

    and Δ,W are defined in Remark 4.

    II. Taking qk1 for k=1,2 in part I, we get

    |K(ϱ,ρ)+1(χ2χ1)(χ4χ3)χ2χ1χ4χ3K(u,v)dvduQ|Mτ2(2nni=1(i+1sii+1))2τ1(1+τ1)2[(ϱχ1)2+(χ2ϱ)2χ2χ1][(ρχ3)2+(χ4ρ)2χ4χ3],

    where

    Q=1χ2χ1χ2χ1K(u,ρ)du+1χ4χ3χ4χ3K(ϱ,v)dv.

    Remark 5. Taking n=s=1 in part II of Corollary 1, we obtain Theorem 4 of [47].

    Theorem 3.2. Suppose that nN, s[0,1] and all the assumptions of Lemma 2.1 holds. If |χ1,χ32p1p2,q1q2K(z,w)χ1p1,q1zχ3p2,q2w|τ, |χ4χ12p1p2,q1q2K(z,w)χ1p1,q1zχ4p2,q2w|τ, |χ2χ32p1p2,q1q2K(z,w)χ2p1,q1zχ3p2,q2w|τ and |χ2,χ42p1p2,q1q2K(z,w)χ2p1,q1zχ4p2,q2w|τ are n-polynomial s-type convex functions on the co-ordinates on N for τ1, and |χ1,χ32p1p2,q1q2K(ϱ,ρ)χ1p1,q1zχ3p2,q2w|M, |χ4χ12p1p2,q1q2K(z,w)χ1p1,q1zχ4p2,q2w|M, |χ2χ32p1p2,q1q2K(z,w)χ2p1,q1zχ3p2,q2w|M, |χ2,χ42p1p2,q1q2K(z,w)χ2p1,q1zχ4p2,q2w|M, ϱ,ρN, then the following inequality holds

    |K(ϱ,ρ)1p1(χ2χ1)[p1ϱ+(1p1)χ1χ1K(u,ρ)χ1dp1,q1u+χ2p1ϱ+(1p1)χ2K(u,ρ)χ2dp1,q1u]1p2(χ4χ3)[p2ρ+(1p2)χ3χ3K(ϱ,v)χ3dp2,q2v+χ4p2ρ+(1p2)χ4K(ϱ,v)χ4dp2,q2v]+A|ΔMτ(Ap1,q1+Bp1,q1)(Ap2,q2+Bp2,q2)[(ϱχ1)2+(χ2ϱ)2][(ρχ3)2+(χ4ρ)2][(p1+q1)(p2+q2)]11τ, (3.8)

    where

    Apk,qk=1pk+qk(pkqk)nni=1e=0siq2ekp2e+2k(1qekpe+1k)i,Bpk,qk=1pk+qk1nni=1si(pkqkpi+2kqi+2k)

    for k=1,2 and Δ,A are defined in Lemma 2.1.

    Proof. Taking absolute value on both sides of (2.1), by applying power mean inequality for double integrals, we get the following inequality

    |K(ϱ,ρ)1p1(χ2χ1)[p1ϱ+(1p1)χ1χ1K(u,ρ)0dp1,q1u+p1ϱ+(1p1)χ2χ2K(u,ρ)0dp1,q1u]1p2(χ4χ3)[p2ρ+(1p2)χ3χ3K(ϱ,v)0dp2,q2v+p2ρ+(1p2)χ4χ4K(ϱ,v)0dp2,q2v]+A|Δ(1010zw0dp1,q1z0dp2,q2w)11τ×{(ϱχ1)2(ρχ3)2(1010zw|χ1,χ32p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ0dp1,q1z0dp2,q2w)1τ
    +(ϱχ1)2(χ4ρ)2(1010zw|χ4χ12p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ4)χ1p1,q1zχ4p2,q2w|τ0dp1,q1z0dp2,q2w)1τ+(χ2ϱ)2(ρχ3)2(1010zw|χ2χ32p1p2,q1q2K(zϱ+(1z)χ2,wρ+(1w)χ3)χ2p1,q1zχ3p2,q2w|τ0dp1,q1z0dp2,q2w)1τ+(χ2ϱ)2(χ4ρ)2(1010zw|χ2,χ42p1p2,q1q2K(zϱ+(1z)χ2,wρ+(1w)χ4)χ2p1,q1zχ4p2,q2w|τ0dp1,q1z0dp2,q2w)1τ}.

    Considering first integral

    1010zw|χ1,χ32p1p2,q1q2K(zϱ+(1z)χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ0dp1,q1z0dp2,q2w10w{10z[1nni=1[1(s(1z))i]|χ1,χ32p1p2,q1q2K(ϱ,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ+1nni=1[1(sz)i]|χ1,χ32p1p2,q1q2K(χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ]0dp1,q1z}0dp2,q2w. (3.9)

    Computing the (p1,q1)-integral on the right-hand side of (3.9), we have

    10z[1nni=1[1(s(1z))i]|χ1,χ32p1p2,q1q2K(ϱ,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ+1nni=1[1(sz)i]|χ1,χ32p1p2,q1q2K(χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ]0dp1,q1z.

    In view of the Definitions 1.5 fpr k=1,2, we get

    Apk,qk=1nni=110z[1(s(1z))i]0dpk,qkz=1pk+qk(pkqk)nni=1e=0siq2ekp2e+2k(1qekpe+1k)i,Bpk,qk=1nni=110z[1(sz)i]0dpk,qkz=1pk+qk1nni=1si(pkqkpi+2kqi+2k).

    Putting the above calculations into (3.9), we obtain

    10w[Ap1,q1|χ1,χ32p1p2,q1q2K(ϱ,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ+Bp1,q1|χ1,χ32p1p2,q1q2K(χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ]0dp2,q2w. (3.10)

    Similarly, by computing the (p2,q2)-integral, utilizing the fact |χ1,χ32p1p2,q1q2K(ϱ,ρ)χ1p1,q1zχ3p2,q2w|M,ϱ,ρN on the right-hand side of (3.10), we have

    1010zw|χ1,χ32p1p2,q1q2K(zϱ+(1w)χ1,wρ+(1w)χ3)χ1p1,q1zχ3p2,q2w|τ0dp1,q1z0dp2,q2wMτ(Ap1,q1+Bp1,q1)(Ap2,q2+Bp2,q2). (3.11)

    Analogously, we get

    1010zw|χ4χ12p1p2,q1q2K(zϱ+(1w)χ1,χ4+wρ+(1w)χ4)χ1p1,q1zχ4p2,q2w|τ0dp1,q1z0dp2,q2wMτ(Ap1,q1+Bp1,q1)(Ap2,q2+Bp2,q2), (3.12)
    1010zw|χ2χ32p1p2,q1q2K(zϱ+(1z)χ2,wρ+(1w)χ3)χ2p1,q1zχ3p2,q2w|τ0dp1,q1z0dp2,q2wMτ(Ap1,q1+Bp1,q1)(Ap2,q2+Bp2,q2) (3.13)

    and

    1010zw|χ2,χ42p1p2,q1q2K(zϱ+(1z)χ2,χ4+wρ+(1w)χ4)χ2p1,q1zχ4p2,q2w|τ0dp1,q1z0dp2,q2wMτ(Ap1,q1+Bp1,q1)(Ap2,q2+Bp2,q2). (3.14)

    Now by making use of the inequalities (3.11)(3.14) and the fact that

    1010zw0dp1,q1z0dp2,q2w=1(p1+q1)(p2+q2),

    we get the desired inequality (3.8). This completes the proof.

    Corollary 2. I. Taking τ=1 in Theorem 3.2, we get

    |K(ϱ,ρ)1p1(χ2χ1)[p1ϱ+(1p1)χ1χ1K(u,ρ)χ1dp1,q1u+χ2p1ϱ+(1p1)χ2K(u,ρ)χ2dp1,q1u]1p2(χ4χ3)[p2ρ+(1p2)χ3χ3K(ϱ,v)χ3dp2,q2v+χ4p2ρ+(1p2)χ4K(ϱ,v)χ4dp2,q2v]+A|ΔM(Ap1,q1+Bp1,q1)(Ap2,q2+Bp2,q2)[(ϱχ1)2+(χ2ϱ)2][(ρχ3)2+(χ4ρ)2].

    II. Taking pk=1 for k=1,2 in Theorem 3.2, we obtain

    |K(ϱ,ρ)1(χ2χ1)[ϱχ1K(u,ρ)χ1dq1u+χ2ϱK(u,ρ)χ2dq1u]1(χ4χ3)[ρχ3K(ϱ,v)χ3dq2v+χ4ρK(ϱ,v)χ4dq2v]+W|ΔMτ(Aq1+Bq1)(Aq2+Bq2)[(1+q1)(1+q2)]11τ[(ϱχ1)2+(χ2ϱ)2][(ρχ3)2+(χ4ρ)2],

    where

    Aqk=11+qk1qknni=1e=0siq2ek(1qek)i,Bqk=11+qk1nni=1si(1qk1qi+2k),

    and Δ,W are defined in Remark 4.

    III. Taking pk=1 for k=1,2, and qk1 in part II, we get

    |K(ϱ,ρ)+1(χ2χ1)(χ4χ3)χ2χ1χ4χ3K(u,v)dvduQ|M41τ1(1nni=1i2+5i+66si2(i+1)(i+2))2τ[(ϱχ1)2+(χ2ϱ)2χ2χ1][(ρχ3)2+(χ4ρ)2χ4χ3],

    where Q is defined in part II of Corollary 1.

    IV. Taking n=1=s in part III, we have the following inequality

    |K(ϱ,ρ)+1(χ2χ1)(χ4χ3)χ2χ1χ4χ3K(u,v)dvduQ|M4[(ϱχ1)2+(χ2ϱ)2χ2χ1][(ρχ3)2+(χ4ρ)2χ4χ3],

    where Q is defined in part II of Corollary 1.

    Let kR{1,0}, and φ1 and φ2 be two distinct positive real numbers. Then the generalized logarithmic mean Lk(φ1,φ2) is defined by

    Lk(φ1,φ2)=(φk+12φk+11(k+1)(φ2φ1))1k.

    Proposition 2. If m,k>1 and χ1,χ2,χ3,χ4 are positive real numbers such that χ1<χ2 and χ3<χ4, then one has

    |ϱm×ρkρk(χ2χ1)[Lmm(ϱ,χ1)+Lmm(χ2,ϱ)]ϱk(χ4χ3)[Lkk(ρ,χ3)+Lkk(χ4,ρ)]+1(χ2χ1)(χ4χ3)(Lmm(ϱ,χ1)+Lmm(χ2,ϱ))(Lkk( ρ,χ3)+Lkk(χ4,ρ))|M (1+τ1)2τ1[(ϱχ1)2+(χ2ϱ)2χ2χ1][(ρχ3)2+(χ4ρ)2χ4χ3].

    Proof. Let K(ϱ,ρ)=ϱm×ρk for m,k>1. Then, we have

    ϱχ1um×ρkχ1dq1u=ρk[1q11qm+11](ϱm+1χm+11ϱχ1),
    χ2ϱum×ρkχ2dq1u=ρk[1q11qm+11](χm+12ϱm+1χ2ϱ),
    ρχ3ϱm×vkχ3dq2v=ϱm[1q21qk+12](ρk+1χk+13 ρχ3),
    χ4ρϱm×vkχ4dq2v=ϱm[1q21qk+12](χk+14ρk+1χ4ρ),
    ϱχ1ρχ3um×vkχ1dq1uχ3dq2v=[1q11qm+11][1q21qk+12](ϱm+1χm+11ϱχ1)(ρk+1χk+13ρχ3),
    ϱχ1χ4ρum×vkχ1dq1uχ4dq2v=[1q11qm+11][1q21qk+12](ϱm+1χm+11ϱχ1)(χk+14ρk+1χ4ρ),
    χ2ϱρχ3um×vkχ2dq1uχ3dq2v=[1q11qm+11][1q21qk+12](χm+12ϱm+1χ2ϱ)(ρk+1χk+13ρχ3)

    and

    χ2ϱχ4ρum×vkχ2dq1uχ4dq2v=[1q11qm+11][1q21qk+12](χm+12ϱm+1χ2ϱ)(χk+14ρk+1χ4ρ).

    It follows from part I of Corollary 1 that

    |K(ϱ,ρ)ρk(χ2χ1)[1q11qm+11][(ϱm+1χm+11ϱχ1)+(χm+12ϱm+1χ2ϱ)]ϱk(χ4χ3)[1q21qk+12][(ρk+1χk+13 ρχ3)+(χk+14ρk+1χ4ρ)]+Z|ΔMτ2(Cq1+Dq1)(Cq2+Dq2)[(ϱχ1)2+(χ2ϱ)2][(ρχ3)2+(χ4ρ)2]τ1[1+τ1]q1[1+τ1]q2,

    where

    Z=1(χ2χ1)(χ4χ3)[1q11qm+11][1q21qk+12][(ϱm+1χm+11ϱχ1)(ρk+1χk+13ρχ3)+(ϱm+1χm+11ϱχ1)(χk+14ρk+1χ4ρ)+(χm+12ϱm+1χ2ϱ)(ρk+1χk+13ρχ3)+(χm+12ϱm+1χ2ϱ)(χk+14ρk+1χ4ρ)],
    Cqk=1(1qk)nni=1e=0siqek(1qek)i,Dqk=11nni=1si(1qk1qi+1k).

    Remark 6. Applying the same idea as in Proposition 2 and using Theorems 3.1, 3.2 and their corresponding corollaries, and choosing suitable functions, for example K(ϱ,ρ)=ϱm×ρk,m,k>1 and ϱ,ρ>0;K(ϱ,ρ)=1ϱρ,ϱ,ρ>0;K(ϱ,ρ)=eϱ+ρ,ϱ,ρR, and so on, we can obtain other new interesting inequalities for special means. We omit their proofs and the details are left to the interested readers.

    In this paper, we have defined several new partial post quantum derivatives and integrals for the functions with two variables, provided some new generalizations in the frame of a new class of convex functions named n-polynomial s-type convex functions, found a new version (p1p2,q1q2)-Ostrowski type inequality via the class of n-polynomial s-type convex functions on co-ordinates, established a twice partial integral identitity involving (p1p2,q1q2)-differentiable functions, and generalized the Ostrowski type inequality. Our results are the generalizations of many previous known results, and our ideas and approach may lead to a lot of follow-up research.

    The authors would like to thank the anonymous referees for their valuable comments and suggestions, which led to considerable improvement of the article.

    This work was supported by the National Natural Science Foundation of China (Grant Nos. 11971142, 61673169, 11701176, 11871202).

    The authors declare that they have no competing interests.



    [1] M. Nagahara, D. E. Quevedo, D. Nesic, Maximum hands-off control: a paradigm of control effort minimization, IEEE Trans. Autom. Control, 61 (2016), 735–747. https://doi.org/10.1109/TAC.2015.2452831 doi: 10.1109/TAC.2015.2452831
    [2] J. Huang, Y. Shi, Guaranteed cost control for multi-sensor networkedcontrol systems using historical data, in 2012 American Control Conference (ACC), (2012), 4927–4932. https://doi.org/10.1109/ACC.2012.6315279
    [3] D. L. Donoho, Compressed sensing, IEEE Trans. Inf. Theory, 52 (2006), 1289–1306. https://doi.org/10.1109/TIT.2006.871582 doi: 10.1109/TIT.2006.871582
    [4] J. Wu, F. Liu, L. C. Jiao, X. Wang, Compressive sensing SAR image reconstruction based on Bayesian framework and evolutionary computation, IEEE Trans. Image Process., 20 (2011), 1904–1911. https://doi.org/10.1109/TIP.2010.2104159 doi: 10.1109/TIP.2010.2104159
    [5] L. Wang, Q. Wang, J. Wang, X. Zhang, Fast band-limited sparse signal reconstruction algorithms for big data processing, IEEE Sens. J., 23 (2023), 13084–13099. https://doi.org/10.1109/JSEN.2023.3268295 doi: 10.1109/JSEN.2023.3268295
    [6] Y. Shi, Y. Gao, S. Liao, D. Zhang, Y. Gao, D. Shen, A learning based CT prostate segmentation method via joint transductive feature selection and regression, Neurocomputing, 173 (2016), 317–331. https://doi.org/10.1016/j.neucom.2014.11.098 doi: 10.1016/j.neucom.2014.11.098
    [7] S. Weng, Editorial: spectroscopy, imaging and machine learning for crop stress, Front. Plant Sci., 14 (2023). https://doi.org/10.3389/fpls.2023.1240738 doi: 10.3389/fpls.2023.1240738
    [8] S. Wang, H. Chen, W. Kong, X. Wu, Y. Qian, K. Wei, A modified FGL sparse canonical correlation analysis for the identification of Alzheimer's disease biomarkers, Electron. Res. Arch., 31 (2023), 882–903. https://doi.org/10.3934/era.2023044 doi: 10.3934/era.2023044
    [9] F. Xu, Z. Lu, Z. Xu, An efficient optimization approach for a cardinality-constrained index tracking problem, Optim. Methods Software, 31 (2016), 258–271. https://doi.org/10.1080/10556788.2015.1062891 doi: 10.1080/10556788.2015.1062891
    [10] S. Bahmani, P. T. Boufounos, B. Raj, Learning model-based sparsity via projected gradient descent, IEEE Trans. Inf. Theory, 62 (2016), 2092–2099. https://doi.org/10.1109/TIT.2016.2515078 doi: 10.1109/TIT.2016.2515078
    [11] S. N. Negahban, P. Ravikumar, M. J. Wainwright, B. Yu, A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers, Stat. Sci., 27 (2012), 538–557. https://doi.org/10.1214/12-STS400 doi: 10.1214/12-STS400
    [12] E. J. Candes, T. Tao, Decoding by linear programming, IEEE Trans. Inf. Theory, 51 (2005), 4203-4215. https://doi.org/10.1109/TIT.2005.858979 doi: 10.1109/TIT.2005.858979
    [13] S. Foucart, M. J. Lai, Sparsest solutions of underdetermined linear systems via lq minimization for 0q1, Appl. Comput. Harmon. Anal., 26 (2009), 395–407. https://doi.org/10.1016/j.acha.2008.09.001 doi: 10.1016/j.acha.2008.09.001
    [14] R. Chartrand, V. Staneva, Restricted isometry properties and nonconvex compressive sensing, Inverse Probl., 24 (2008), 035020. https://doi.org/10.1088/0266-5611/24/3/035020 doi: 10.1088/0266-5611/24/3/035020
    [15] G. Gasso, A. Rakotomamonjy, S. Canu, Recovering sparse signals with a certain family of nonconvex penalties and DC programming, IEEE Trans. Signal Process., 57 (2009), 4686–4698. https://doi.org/10.1109/TSP.2009.2026004 doi: 10.1109/TSP.2009.2026004
    [16] H. A. L. Thi, H. M. Le, P. D. Tao, Feature selection in machine learning: an exact penalty approach using a difference of convex function algorithm, Mach. Learn., 101 (2015), 163–186. https://doi.org/10.1007/s10994-014-5455-y doi: 10.1007/s10994-014-5455-y
    [17] W. Peng, T. Gu, Y. Zhuang, Z. He, C. Han, Pattern synthesis with minimum mainlobe width via sparse optimization, Digital Signal Process., 128 (2022), 103632. https://doi.org/10.1016/j.dsp.2022.103632 doi: 10.1016/j.dsp.2022.103632
    [18] J. Liang, X. Zhu, C. Yue, Z. Li, B. Qu, Performance analysis on knee point selection methods for multi-objective sparse optimization problems, in 2018 IEEE Congress on Evolutionary Computation (CEC), (2018), 1–8. https://doi.org/10.1109/CEC.2018.8477915
    [19] X. Xiu, Z. Miao, W. Liu, A sparsity-aware fault diagnosis framework focusing on accurate isolation, IEEE Trans. Ind. Inf., 19 (2022), 1356–1365. https://doi.org/10.1109/TII.2022.3180070 doi: 10.1109/TII.2022.3180070
    [20] C. V. Rao, Sparsity of linear discrete-Time optimal control problems with L1 objectives, IEEE Trans. Autom. Control, 63 (2017), 513–517. https://doi.org/10.1109/TAC.2017.2732286 doi: 10.1109/TAC.2017.2732286
    [21] M. Babazadeh, Regularization for optimal sparse control structures: a primal-dual framework, in 2021 American Control Conference (ACC), (2021), 3850–3855. https://doi.org/10.23919/ACC50511.2021.9482729
    [22] P. Benner, H. Faßbender, On the numerical solution of large-scale sparse discrete-time Riccati equations, Adv. Comput. Math., 35 (2011), 119–147. https://doi.org/10.1007/s10444-011-9174-7 doi: 10.1007/s10444-011-9174-7
    [23] F. S. Aktacs, O. Ekmekcioglu, M. C. Pinar, Provably optimal sparse solutions to overdetermined linear systems with non-negativity constraints in a least-squares sense by implicit enumeration, Optim. Eng., 22 (2021), 2505–2535. https://doi.org/10.1007/s11081-021-09676-2 doi: 10.1007/s11081-021-09676-2
    [24] B. Polyak, A. Tremba, Sparse solutions of optimal control via Newton method for under-determined systems, J. Global Optim., 76 (2020), 613–623. https://doi.org/10.1007/s10898-019-00784-z doi: 10.1007/s10898-019-00784-z
    [25] D. Kalise, K. Kunisch, Z. Rao, Infinite horizon sparse optimal control, J. Optim. Theory Appl., 172 (2017), 481–517. https://doi.org/10.1007/s10957-016-1016-9 doi: 10.1007/s10957-016-1016-9
    [26] P. Budhraja, A. S. A. Dilip, Maximum hands-off control for a class of nonlinear systems, in 2021 29th Mediterranean Conference on Control and Automation (MED), (2021), 1003–1006. https://doi.org/10.1109/MED51440.2021.9480171
    [27] W. Ji, Optimal control problems with time inconsistency, Electron. Res. Arch., 31 (2023), 492–508. https://doi.org/10.3934/era.2023024 doi: 10.3934/era.2023024
    [28] P. Yu, S. Tan, J. Guo, Y. Song, Data-driven optimal controller design for sub-satellite deployment of tethered satellite system, Electron. Res. Arch., 32 (2024), 505–522. https://doi.org/10.3934/era.2024025 doi: 10.3934/era.2024025
    [29] K. L. Teo, B. Li, C. Yu, V. Rehbock, Applied and Computational Optimal Control: A Control Parametrization Approach, Springer: Optimization and Its Applications, 2021. https://doi.org/10.1007/978-3-030-69913-0
    [30] S. Su, M. Shao, C. Yu, K. L. Teo, On the correlation of local collocation and control parameterization methods, J. Ind. Manage. Optim., 2024. https://doi.org/10.3934/jimo.2024004 doi: 10.3934/jimo.2024004
    [31] Q. Lin, R. Loxton, K. L. Teo, The control parameterization method for nonlinear optimal control: a survey, J. Ind. Manage. Optim., 10 (2014), 275–309. https://doi.org/10.3934/jimo.2014.10.275 doi: 10.3934/jimo.2014.10.275
    [32] C. Xu, H. Li, Two-grid methods of finite element approximation for parabolic integro-differential optimal control problems, Electron. Res. Arch., 31 (2023), 4818–4842. https://doi.org/10.3934/era.2023247 doi: 10.3934/era.2023247
    [33] Y. Yuan, C. Liu, Optimal control for the coupled chemotaxis-fluid models in two space dimensions, Electron. Res. Arch., 29 (2021), 4269–4296. https://doi.org/10.3934/era.2021085 doi: 10.3934/era.2021085
    [34] Z. Z. Tao, B. Sun, A feedback design for numerical solution to optimal control problems based on Hamilton-Jacobi-Bellman equation, Electron. Res. Arch., 29 (2021), 3429–3447. https://doi.org/10.3934/era.2021046 doi: 10.3934/era.2021046
    [35] X. Pang, H. Song, X. Wang, J. Zhang, Efficient numerical methods for elliptic optimal control problems with random coefficient, Electron. Res. Arch., 28 (2020), 1001–1022. https://doi.org/10.3934/era.2020053 doi: 10.3934/era.2020053
    [36] H. W. J. Lee, K. L. Teo, X. Q. Cai, An optimal control approach to nonlinear mixed integer programming problems, Comput. Math. Appl., 36 (1998), 87–105. https://doi.org/10.1016/S0898-1221(98)00131-X doi: 10.1016/S0898-1221(98)00131-X
    [37] A. Siburian, V. Rehbock, Numerical procedure for solving a class of singular optimal control problems, Optim. Methods Software, 19 (2004), 413–426. https://doi.org/10.1080/10556780310001656637 doi: 10.1080/10556780310001656637
    [38] G. Vossen, Switching time optimization for bang-bang and singular controls, J. Optim. Theory Appl., 144 (2010), 409–429. https://doi.org/10.1007/s10957-009-9594-4 doi: 10.1007/s10957-009-9594-4
    [39] X. Zhu, C. Yu, K. L. Teo, Sequential adaptive switching time optimization technique for optimal control problems, Automatica, 146 (2022), 110565. https://doi.org/10.1016/j.automatica.2022.110565 doi: 10.1016/j.automatica.2022.110565
    [40] C. Liu, R. Loxton, K. L. Teo, S. Wang, Optimal state-delay control in nonlinear dynamic systems, Automatica, 135 (2022), 109981. https://doi.org/10.1016/j.automatica.2021.109981 doi: 10.1016/j.automatica.2021.109981
    [41] C. Liu, Z. Gong, C. Yu, S. Wang, K. L. Teo, Optimal control computation for nonlinear fractional time-delay systems with state inequality constraints, J. Optim. Theory Appl., 191 (2021), 83–117. https://doi.org/10.1007/s10957-021-01926-8 doi: 10.1007/s10957-021-01926-8
    [42] C. Liu, C. Yu, Z. Gong, H. T. Cheong, K. L. Teo, Numerical computation of optimal control problems with Atangana CBaleanu fractional derivatives, J. Optim. Theory Appl., 197 (2023), 798–816. https://doi.org/10.1007/s10957-023-02212-5 doi: 10.1007/s10957-023-02212-5
    [43] C. Yu, K. H. Wong, An enhanced control parameterization technique with variable switching times for constrained optimal control problems with control-dependent time-delayed arguments and discrete time-delayed arguments, J. Comput. Appl. Math., 427 (2023), 115106. https://doi.org/10.1016/j.cam.2023.115106 doi: 10.1016/j.cam.2023.115106
    [44] D. Wu, Y. Chen, C. Yu, Y. Bai, K. L. Teo, Control parameterization approach to time-delay optimal control problems: a survey, J. Ind. Manage. Optim., 19 (2023), 3750–3783. https://doi.org/10.3934/jimo.2022108 doi: 10.3934/jimo.2022108
    [45] D. Wu, Y. Bai, F. Xie, Time-scaling transformation for optimal control problem with time-varying delay, Discrete Contin. Dyn. Syst. - Ser. S, 13 (2020), 1683–1695. https://doi.org/10.3934/dcdss.2020098 doi: 10.3934/dcdss.2020098
    [46] P. Liu, X. Li, X. Liu, Y. Hu, An improved smoothing technique-based control vector parameterization method for optimal control problems with inequality path constraints, Optim. Control. Appl. Methods, 38 (2017), 586–600. https://doi.org/10.1002/oca.2273 doi: 10.1002/oca.2273
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