Optimal control problems for switched systems how best to switch between different subsystems. In this paper, two kinds of linear quadratic optimal control problems for multistage switched systems composing of both randomness and uncertainty are studied. Chance theory brings us a useful tool to deal with this indeterminacy. Based on chance theory and Bellman's principle, the analytical expressions are derived for calculating both the optimal control input and the optimal switching control law. Optimal control is implemented by genetic algorithm instead of enumerating all the elements of a series of sets whose size grows exponentially. Finally, the results of numerical examples are provided to illustrate the effectiveness of the proposed method.
Citation: Guangyang Liu, Yang Chang, Hongyan Yan. Uncertain random problem for multistage switched systems[J]. AIMS Mathematics, 2023, 8(10): 22789-22807. doi: 10.3934/math.20231161
[1] | Khaled M. Saad, Manal Alqhtani . Numerical simulation of the fractal-fractional reaction diffusion equations with general nonlinear. AIMS Mathematics, 2021, 6(4): 3788-3804. doi: 10.3934/math.2021225 |
[2] | Abdon Atangana, Ali Akgül . Analysis of a derivative with two variable orders. AIMS Mathematics, 2022, 7(5): 7274-7293. doi: 10.3934/math.2022406 |
[3] | Abdon Atangana, Seda İğret Araz . Extension of Chaplygin's existence and uniqueness method for fractal-fractional nonlinear differential equations. AIMS Mathematics, 2024, 9(3): 5763-5793. doi: 10.3934/math.2024280 |
[4] | Manal Alqhtani, Khaled M. Saad . Numerical solutions of space-fractional diffusion equations via the exponential decay kernel. AIMS Mathematics, 2022, 7(4): 6535-6549. doi: 10.3934/math.2022364 |
[5] | Amir Ali, Abid Ullah Khan, Obaid Algahtani, Sayed Saifullah . Semi-analytical and numerical computation of fractal-fractional sine-Gordon equation with non-singular kernels. AIMS Mathematics, 2022, 7(8): 14975-14990. doi: 10.3934/math.2022820 |
[6] | Hasib Khan, Jehad Alzabut, Anwar Shah, Sina Etemad, Shahram Rezapour, Choonkil Park . A study on the fractal-fractional tobacco smoking model. AIMS Mathematics, 2022, 7(8): 13887-13909. doi: 10.3934/math.2022767 |
[7] | Rahat Zarin, Amir Khan, Pushpendra Kumar, Usa Wannasingha Humphries . Fractional-order dynamics of Chagas-HIV epidemic model with different fractional operators. AIMS Mathematics, 2022, 7(10): 18897-18924. doi: 10.3934/math.20221041 |
[8] | Muhammad Farman, Ali Akgül, Sameh Askar, Thongchai Botmart, Aqeel Ahmad, Hijaz Ahmad . Modeling and analysis of fractional order Zika model. AIMS Mathematics, 2022, 7(3): 3912-3938. doi: 10.3934/math.2022216 |
[9] | Muhammad Aslam, Muhammad Farman, Hijaz Ahmad, Tuan Nguyen Gia, Aqeel Ahmad, Sameh Askar . Fractal fractional derivative on chemistry kinetics hires problem. AIMS Mathematics, 2022, 7(1): 1155-1184. doi: 10.3934/math.2022068 |
[10] | Asif Khan, Tayyaba Akram, Arshad Khan, Shabir Ahmad, Kamsing Nonlaopon . Investigation of time fractional nonlinear KdV-Burgers equation under fractional operators with nonsingular kernels. AIMS Mathematics, 2023, 8(1): 1251-1268. doi: 10.3934/math.2023063 |
Optimal control problems for switched systems how best to switch between different subsystems. In this paper, two kinds of linear quadratic optimal control problems for multistage switched systems composing of both randomness and uncertainty are studied. Chance theory brings us a useful tool to deal with this indeterminacy. Based on chance theory and Bellman's principle, the analytical expressions are derived for calculating both the optimal control input and the optimal switching control law. Optimal control is implemented by genetic algorithm instead of enumerating all the elements of a series of sets whose size grows exponentially. Finally, the results of numerical examples are provided to illustrate the effectiveness of the proposed method.
Fractional calculus has come out as one of the most applicable subjects of mathematics [1]. Its importance is evident from the fact that many real-world phenomena can be best interpreted and modeled using this theory. It is also a fact that many disciplines of engineering and science have been influenced by the tools and techniques of fractional calculus. Its emergence can easily be traced and linked with the famous correspondence between the two mathematicians, L'Hospital and Leibnitz, which was made on 30th September 1695. After that, many researchers tried to explore the concept of fractional calculus, which is based on the generalization of nth order derivatives or n-fold integration [2,3,4].
Recently, Khan and Khan [5] have discovered novel definitions of fractional integral and derivative operators. These operators enjoy interesting properties such as continuity, boundedeness, linearity etc. The integral operators, they presented, are stated as under:
Definition 1 ([5]). Let h∈Lθ[s,t](conformable integrable on [s,t]⊆[0,∞)). The left-sided and right-sided generalized conformable fractional integrals τθKνs+ and τθKνt− of order ν>0 with θ∈(0,1], τ∈R, θ+τ≠0 are defined by:
τθKνs+h(r)=1Γ(ν)r∫s(rτ+θ−wτ+θτ+θ)ν−1h(w)wτdθw,r>s, | (1.1) |
and
τθKνt−h(r)=1Γ(ν)t∫r(wτ+θ−rτ+θτ+θ)ν−1h(w)wτdθw,t>r, | (1.2) |
respectively, and τθK0s+h(r)=τθK0t−h(r)=h(r). Here Γ denotes the well-known Gamma function.
Here the integral t∫sdθw represents the conformable integration, defined as:
t∫sh(w)dθw=t∫sh(w)wθ−1dw. | (1.3) |
The operators defined in Definition 1 are in generalized form and contain few important operators in themselves. Here, only the left-sided operators are presented, the corresponding right-sided operators may be deduced in the similar way. Moreover, to understand the theory of conformable fractional calculus, one can see [5,6,7]. Also, the basic theory of fractional calculus can be found in the books [1,8,9] and for the latest research in this field one can see [3,4,10,11,12] and the references there in.
Remark 1. 1) For θ=1 in the Definition 1, the following Katugampula fractional integral operator is obtained [13]:
τ1Kνs+h(r)=1Γ(ν)r∫s(rτ+1−wτ+1τ+1)ν−1h(w)dw,r>s. | (1.4) |
2) For τ=0 in the Definition 1, the New Riemann Liouville type conformable fractional integral operator is obtained as given below:
0θKνs+h(r)=1Γ(ν)r∫s(rθ−wθθ)ν−1h(w)dθw,r>s. | (1.5) |
3) Using the definition of conformable integral given in (1.3) and L'Hospital rule, it is straightforward that when θ→0 in (1.5), we get the Hadamard fractional integral operator as follows:
00+Kνs+h(r)=1Γ(ν)r∫s(logrw)ν−1h(w)dww,r>s. | (1.6) |
4) For θ=1 in (1.5), the well-known Riemann-Liouville fractional integral operator is obtained as follows:
01Kνs+h(r)=1Γ(ν)r∫s(r−w)ν−1h(w)dw,r>s. | (1.7) |
5) For the case ν=1,τ=0 in Definition 1, we get the conformable fractional integrals. And when θ=ν=1, τ=0, we get the classical Riemann integrals.
This subsection is devoted to start with the definition of convex function, which plays a very important role in establishment of various kinds of inequalities [14]. This definition is given as follows [15]:
Definition 2. A function h:I⊆R→R is said to be convex on I if the inequality
h(ηs+(1−η)t)≤ηh(s)+(1−η)h(t) | (1.8) |
holds for all s,t∈I and 0≤η≤1. The function h is said to be concave on I if the inequality given in (1.8) holds in the reverse direction.
Associated with the Definition 2 of convex functions the following double inequality is well-known and it has been playing a key role in various fields of science and engineering [15].
Theorem 1. Let h:I⊆R→R be a convex function and s,t∈I with s<t. Then we have the following Hermite-Hadamard inequality:
h(s+t2)≤1t−st∫sh(τ)dτ≤h(s)+h(t)2. | (1.9) |
This inequality (1.9) appears in a reversed order if the function h is supposed to be concave. Also, the relation (1.9) provides upper and lower estimates for the integral mean of the convex function h. The inequality (1.9) has various versions (extensions or generalizations) corresponding to different integral operators [16,17,18,19,20,21,22,23,24,25] each version has further forms with respect to various kinds of convexities [26,27,28,29,30,31,32] or with respect to different bounds obtained for the absolute difference of the two leftmost or rightmost terms in the Hermite-Hadamard inequality.
By using the Riemann-Liouville fractional integral operators, Sirikaye et al. have proved the following Hermite-Hadamard inequality [33].
Theorem 2. ([33]). Let h:[s,t]→R be a function such that 0≤s<t and h∈L[s,t]. If h is convex on [s,t], then the following double inequality holds:
h(s+t2)≤Γ(ν+1)2(t−s)ν[01Kνs+h(t)+01Kνt−h(s)]≤h(s)+h(t)2. | (1.10) |
For more recent research related to generalized Hermite-Hadamard inequality one can see [34,35,36,37,38,39,40,41,42] and the references therein.
Motivated from the Riemann-Liouville version of Hermite-Hadamard inequality (given above in (1.10)), we prove the same inequality for newly introduced generalized conformable fractional operators. As a result we get a more generalized inequality, containing different versions of Hermite-Hadamard inequality in single form. We also prove an identity for generalized conformable fractional operators and establish a bound for the absolute difference of two rightmost terms in the newly obtained Hermite-Hadamard inequality. We point out some relations of our results with those of other results from the past. At the end we present conclusion, where directions for future research are also mentioned.
In the following theorem the well-known Hermite-Hadamard inequality for the newly defined integral operators is proved.
Theorem 3. Let ν>0 and τ∈R,θ∈(0,1] such that τ+θ>0. Let h:[s,t]⊆[0,∞)→R be a function such that h∈Lθ[s,t](conformal integrable on [s, t]). If h is also a convex function on [s,t], then the following Hermite-Hadamard inequality for generalized conformable fractional Integrals τθKνs+ and τθKνt− holds:
h(s+t2)≤(τ+θ)νΓ(ν+1)4(tτ+θ−sτ+θ)ν[τθKνs+H(t)+τθKνt−H(s)]≤h(s)+h(t)2, | (2.1) |
where H(x)=h(x)+˜h(x), ˜h(x)=h(s+t−x).
Proof. Let η∈[0,1]. Consider x,y∈[s,t], defined by x=ηs+(1−η)t,y=(1−η)s+ηt. Since h is a convex function on [s,t], we have
h(s+t2)=h(x+y2)≤h(x)+h(y)2=h(ηs+(1−η)t)+h((1−η)s+ηt)2. | (2.2) |
Multiplying both sides of (2.2) by
(t−s)(τ+θ)1−ν((1−η)s+ηt)τ+θ−1Γ(ν)[tτ+θ−((1−η)s+ηt)τ+θ]1−ν, |
and integrating with respect to η, we get
(t−s)(τ+θ)1−νΓ(ν)h(s+t2)1∫0((1−η)s+ηt)τ+θ−1[tτ+θ−((1−η)s+ηt)τ+θ]1−νdη≤(t−s)(τ+θ)1−νΓ(ν)12{1∫0((1−η)s+ηt)τ+θ−1[tτ+θ−((1−η)s+ηt)τ+θ]1−νh(ηs+(1−η)t)dη+1∫0(1−η)s+ηt)τ+θ−1[tτ+θ−((1−η)s+ηt)τ+θ]1−νh((1−η)s+ηt)dη}. | (2.3) |
Note that we have
1∫0((1−η)s+ηt)τ+θ−1[tτ+θ−((1−η)s+ηt)τ+θ]1−νdη=1ν(τ+θ)(t−s)(tτ+θ−sτ+θ)ν. |
Also, by using the identity ˜h((1−η)s+ηt)=h(ηs+(1−η)t), and making substitution (1−η)s+ηt=w, we get
(t−s)(τ+θ)1−νΓ(ν)1∫0((1−η)s+ηt)τ+θ−1[tτ+θ−((1−η)s+ηt)τ+θ]1−νh(ηs+(1−η)t)dη=(τ+θ)1−νΓ(ν)t∫swτ+θ−1[tτ+θ−wτ+θ]1−ν˜h(w)dw=(τ+θ)1−νΓ(ν)t∫swτ[tτ+θ−wτ+θ]1−ν˜h(w)dθw=τθKνs+˜h(t). | (2.4) |
Similarly
(t−s)(τ+θ)1−νΓ(ν)1∫0((1−η)s+ηt)τ+θ−1[tτ+θ−((1−η)s+ηt)τ+θ]1−νh(ηt+(1−η)s)dη=τθKνs+h(t). | (2.5) |
By substituting these values in (2.3), we get
(tτ+θ−sτ+θ)νΓ(ν+1)(τ+θ)νh(s+t2)≤τθKνs+H(t)2. | (2.6) |
Again, by multiplying both sides of (2.2) by
(t−s)(τ+θ)1−ν((1−η)s+ηt)τ+θ−1Γ(ν)[((1−η)s+ηt)τ+θ−sτ+θ]1−ν, |
and then integrating with respect to η and by using the same techniques used above, we can obtain:
(tτ+θ−sτ+θ)νΓ(ν+1)(τ+θ)νh(s+t2)≤τθKνt−H(s)2. | (2.7) |
Adding (2.7) and (2.6), we get:
h(s+t2)≤Γ(ν+1)(τ+θ)ν4(tτ+θ−sτ+θ)ν[τθKνs+H(t)+τθKνt−H(s)]. | (2.8) |
Hence the left-hand side of the inequality (2.1) is established.
Also since h is convex, we have:
h(ηs+(1−η)t)+h((1−η)s+ηt)≤h(s)+h(t). | (2.9) |
Multiplying both sides
(t−s)(τ+θ)1−ν((1−η)s+ηt)τ+θ−1Γ(ν)[tτ+θ−((1−η)s+ηt)τ+θ]1−ν, |
and integrating with respect to η we get
(t−s)(τ+θ)1−νΓ(ν)1∫0((1−η)s+ηt)τ+θ−1[tτ+θ−((1−η)s+ηt)τ+θ]1−νh(ηs+(1−η)t)dη+(t−s)(τ+θ)1−νΓ(ν)1∫0((1−η)s+ηt)τ+θ−1[tτ+θ−((1−η)s+ηt)τ+θ]1−νh(ηt+(1−η)s)dη≤(t−s)(τ+θ)1−νΓ(ν)[h(s)+h(t)]1∫0(1−η)s+ηt)τ+θ−1[tτ+θ−((1−η)s+ηt)τ+θ]1−νdη, | (2.10) |
that is,
τθKνs+H(t)≤(tτ+θ−sτ+θ)νΓ(ν+1)(τ+θ)ν[h(s)+h(t)]. | (2.11) |
Similarly multiplying both sides of (2.9) by
(t−s)(τ+θ)1−ν((1−η)s+ηt)τ+θ−1Γ(ν)[((1−η)s+ηt)τ+θ−sτ+θ]1−ν, |
and integrating with respect to η, we can obtain
τθKνt−H(s)≤(tτ+θ−sτ+θ)νΓ(ν+1)(τ+θ)ν[h(s)+h(t)]. | (2.12) |
Adding the inequalities (2.11) and (2.12), we get:
Γ(ν+1)(τ+θ)ν4(tτ+θ−sτ+θ)ν[τθKνt−H(s)+τθKνs+H(t)]≤h(s)+h(t)2. | (2.13) |
Combining (2.8) and (2.13), we get the required result.
The inequality in (2.1) is in compact form containing few inequalities for different integrals in it. The following remark tells us about that fact.
Remark 2. 1) For θ=1 in (2.1), we get Hermite-Hadamard inequality for Katugampola fractional integral operators, as follows [38]:
h(s+t2)≤(τ+1)νΓ(ν+1)4(tτ+1−sτ+1)ν[τ1Kνs+H(t)+τ1Kνt−H(s)]≤h(s)+h(t)2, | (2.14) |
where H(x)=h(x)+˜h(x), ˜h(x)=h(s+t−x).
2) For τ=0 in (2.1), we get Hermite-Hadamard inequality for newly obtained Riemann Liouville type conformable fractional integral operators, as follows:
h(s+t2)≤θνΓ(ν+1)4(tθ−sθ)ν[0θKνs+H(t)+0θKνt−H(s)]≤h(s)+h(t)2, | (2.15) |
where H(x)=h(x)+˜h(x), ˜h(x)=h(s+t−x).
3) For τ+θ→0, in (2.1), applying L'Hospital rule and the relation (1.3), we get Hermite-Hadamard inequality for Hadamard fractional integral operators, as follows:
h(s+t2)≤Γ(ν+1)2(lnts)ν[00+Kνs+h(t)+00+Kνt−h(s)]≤h(s)+h(t)2. | (2.16) |
4) For τ+θ=1 in (2.1), the Hermite-Hadamard inequality is obtained for Riemann-Liouville fractional integrals [33]:
h(s+t2)≤Γ(ν+1)2(t−s)ν[01Kνs+h(t)+01Kνt−h(s)]≤h(s)+h(t)2. | (2.17) |
5) For the case ν=1,τ=0 in (2.1), the Hermite-Hadamard inequality is obtained for the conformable fractional integrals as follows:
h(s+t2)≤θ2(tθ−sθ)t∫sH(w)dθw≤h(s)+h(t)2. | (2.18) |
6) When θ=ν=1, τ=0 the Hermite-Hadamard inequality is obtained for classical Riemann integrals [15]:
h(s+t2)≤1t−st∫sh(w)dw≤h(s)+h(t)2. | (2.19) |
To bound the difference of two rightmost terms in the main inequality (2.1), we need to establish the following Lemma.
Lemma 1. Let τ+θ>0 and ν>0. If h∈Lθ[s,t], then
h(s)+h(t)2−(τ+θ)νΓ(ν+1)4(tτ+θ−sτ+θ)ν[τθKνs+H(t)+τθKνt−H(s)]=t−s4(tτ+θ−sτ+θ)ν1∫0Δντ+θ(η)h′(ηs+(1−η)t)dη, | (2.20) |
where
Δντ+θ(η)=[(ηs+(1−η)t)τ+θ−sτ+θ]ν−[(ηt+(1−η)s)τ+θ−sτ+θ]ν+[tτ+θ−((1−η)s+ηt)τ+θ]ν−[tτ+θ−((1−η)t+ηs)τ+θ]ν. |
Proof. With the help of integration by parts, we have
τθKνs+H(t)=(tτ+θ−sτ+θ)ν(τ+θ)νΓ(ν+1)H(s)+(t−s)ν(τ+θ)νΓ(ν+1)1∫0[tτ+θ−((1−η)s+ηt)τ+θ]νH′(ηt+(1−η)s)dη. | (2.21) |
Similarly, we have
τθKνt−H(s)=(tτ+θ−sτ+θ)ν(τ+θ)νΓ(ν+1)H(t)−(t−s)ν(τ+θ)νΓ(ν+1)1∫0[((1−η)s+ηt)τ+θ−sτ+θ]νH′(ηt+(1−η)s)dη. | (2.22) |
Using (2.21) and (2.22) we have
4(tτ+θ−sτ+θ)νt−s(h(s)+h(t)2−(τ+θ)νΓ(ν+1)4(tτ+θ−sτ+θ)ν[τθKνt−H(s)+τθKνs+H(t)])=1∫0([((1−η)s+ηt)τ+θ−sτ+θ]ν−[(tτ+θ−((1−η)s+ηt)τ+θ]ν)H′(ηt+(1−η)s)dη. | (2.23) |
Also, we have
H′(ηt+(1−η)s)=h′(ηt+(1−η)s)−h′(ηs+(1−η)t),η∈[0,1]. | (2.24) |
And
1∫0[((1−η)s+ηt)τ+θ−sτ+θ]νH′(ηt+(1−η)s)dη=1∫0[((1−η)t+ηs)τ+θ−sτ+θ]νh′(ηs+(1−η)t)dη−1∫0[((1−η)s+ηt)τ+θ−sτ+θ]νh′(ηs+(1−η)t)dη. | (2.25) |
Also, we have
1∫0[tτ+θ−((1−η)s+ηt)τ+θ]νH′(ηt+(1−η)s)dη=1∫0[tτ+θ−((1−η)t+ηs)τ+θ]νh′(ηs+(1−η)t)dη−1∫0[tτ+θ−((1−η)s+ηt)τ+θ]νh′(ηs+(1−η)t)dη. | (2.26) |
Using (2.23), (2.25) and (2.26) we get the required result.
Remark 3. When τ+θ=1 in Lemma 1, we get the Lemma 2 in [33].
Definition 3. For ν>0, we define the operators
Ων1(x,y,τ+θ)=s+t2∫s|x−w||yτ+θ−wτ+θ|νdw−t∫s+t2|x−w||yτ+θ−wτ+θ|νdw, | (2.27) |
and
Ων2(x,y,τ+θ)=s+t2∫s|x−w||wτ+θ−yτ+θ|νdw−t∫s+t2|x−w||wτ+θ−yτ+θ|νdw, | (2.28) |
where x,y∈[s,t]⊆[0,∞) and τ+θ>0.
Theorem 4. Let h be a conformable integrable function over [s,t] such that |h′| is convex function. Then for ν>0 and τ+θ>0 we have:
|h(s)+h(t)2−(τ+θ)νΓ(ν+1)4(tτ+θ−sτ+θ)ν[τθKνs+H(t)+τθKνt−H(s)]|≤Kντ+θ(s,t)4(t−s)(tτ+θ−sτ+θ)ν(|h′(s)|+|h′(t)|), | (2.29) |
where Kντ+θ(s,t)=Ων1(t,t,τ+θ)+Ων2(s,s,τ+θ)−Ων2(t,s,τ+θ)−Ων1(s,t,τ+θ).
Proof. Using Lemma 1 and convexity of |h′|, we have:
|h(s)+h(t)2−(τ+θ)νΓ(ν+1)4(tτ+θ−sτ+θ)ν[τθKνs+H(t)+τθKνt−H(s)]|≤t−s4(tτ+θ−sτ+θ)ν1∫0|Δντ+θ(η)||h′(ηs+(1−η)t)|dη≤t−s4(tτ+θ−sτ+θ)ν(|h′(s)|1∫0η|Δντ+θ(η)|dη+|h′(t)|1∫0(1−η)|Δντ+θ(η)|dη). | (2.30) |
Here 1∫0η|Δντ+θ(η)|dη=1(t−s)2t∫s|ψ(u)|(t−u)du,
and ψ(u)=(uτ+θ−sτ+θ)ν−((t+s−u)τ+θ−sτ+θ)ν+(tτ+θ−(s+t−u)τ+θ)ν−(tτ+θ−uτ+θ)ν.
We observe that ψ is a nondecreasing function on [s,t]. Moreover, we have:
ψ(s)=−2(tτ+θ−sτ+θ)ν<0, |
and also ψ(s+t2)=0. As a consequence, we have
{ψ(u)≤0,if s≤u≤s+t2,ψ(u)>0,if s+t2<u≤t. |
Thus we get
1∫0η|Δντ+θ(η)|dη=1(t−s)2t∫s|ψ(u)|(t−u)du=1(t−s)2[−s+t2∫sψ(u)(t−u)du+t∫s+t2ψ(u)(t−u)du]=1(t−s)2[K1+K2+K3+K4], | (2.31) |
where
K1=−s+t2∫s(t−u)(uτ+θ−sτ+θ)νdu+t∫s+t2(t−u)(uτ+θ−sτ+θ)νdu, | (2.32) |
K2=s+t2∫s(t−u)((t+s−u)τ+θ−sτ+θ)νdu−t∫s+t2(t−u)((t+s−u)τ+θ−sτ+θ)νdu, | (2.33) |
K3=−s+t2∫s(t−u)(tτ+θ−(s+t−u)τ+θ)νdu+t∫s+t2(t−u)(tτ+θ−(s+t−u)τ+θ)νdu, | (2.34) |
and
K4=s+t2∫s(t−u)(tτ+θ−uτ+θ)νdu−t∫s+t2(t−u)(tτ+θ−uτ+θ)νdu. | (2.35) |
We can see here that K1=−Ων2(t,s,τ+θ), K4=Ων1(t,t,τ+θ).
Also, by using of change of the variables v=s+t−u, we get
K2=Ων2(s,s,τ+θ),K3=−Ων1(s,t,τ+θ). | (2.36) |
By substituting these values in (2.31), we get
1∫0ηΔντ+θ(η)dη=−Ων2(t,s,τ+θ)+Ων1(t,t,τ+θ)+Ων2(s,s,τ+θ)−Ων1(s,t,τ+θ)(t−s)2. | (2.37) |
Similarly, we can find
1∫0(1−η)Δντ+θ(η)dη=Ων2(s,s,τ+θ)−Ων2(t,s,τ+θ)+Ων1(t,t,τ+θ)−Ων1(s,t,τ+θ)(t−s)2. | (2.38) |
Finally, by using (2.30), (2.37) and (2.38) we get the required result.
Remark 4. when τ+θ=1 in (2.29), we obtain
|h(s)+h(t)2−Γ(ν+1)2(t−s)ν[01Kνt−h(s)+01Kνs+h(t)]|≤(t−s)2(ν+1)(1−12ν)[h′(s)+h′(t)], |
which is Theorem 3 in [33].
A generalized version of Hermite-Hadamard inequality via newly introduced GC fractional operators has been acquired successfully. This result combines several versions (new and old) of the Hermite-Hadamard inequality into a single form, each one has been discussed by fixing parameters in the newly established version of the Hermite-Hadamard inequality. Moreover, an identity containing the GC fractional integral operators has been proved. By using this identity, a bound for the absolute of the difference between the two rightmost terms in the newly established Hermite-Hadamard inequality has been presented. Also, some relations of our results with those of already existing results have been pointed out. Since this is a fact that there exist more than one definitions for fractional derivatives [2] which makes it difficult to choose a convenient operator for solving a given problem. Thus, in the present paper, the GC fractional operators (containing various previously defined fractional operators into a single form) have been used in order to overcome the problem of choosing a suitable fractional operator and to provide a unique platform for researchers working with different operators in this field. Also, by making use of GC fractional operators one can follow the research work which has been performed for the two versions (1.9) and (1.10) of Hermite-Hadamard inequality.
This work was supported by the Natural Science Foundation of China (Grant Nos. 61673169, 11301127, 11701176, 11626101, 11601485).
The authors declare that there are no conflicts of interest regarding the publication of this paper.
[1] |
X. Xu, P. J. Antsaklis, Optimal control of switched systems based on parameterization of the switching instants, IEEE Trans. Automat. Control, 49 (2004), 2–16. https://doi.org/10.1109/TAC.2003.821417 doi: 10.1109/TAC.2003.821417
![]() |
[2] |
F. Zhu, P. J. Antsaklis, Optimal control of hybrid switched systems: a brief survey, Discrete Event Dyn. Syst., 25 (2015), 345–364. https://doi.org/10.1007/s10626-014-0187-5 doi: 10.1007/s10626-014-0187-5
![]() |
[3] |
S. C. Bengea, R. A. Decarlo, Optimal control of switching systems, Automatica, 41 (2005), 11–27. https://doi.org/10.1016/j.automatica.2004.08.003 doi: 10.1016/j.automatica.2004.08.003
![]() |
[4] |
M. Kamgarpour, C. Tomlin, On optimal control of non-autonomous switched systems with a fixed mode sequence, Automatica, 48 (2012), 1177–1181. https://doi.org/10.1016/j.automatica.2012.03.019 doi: 10.1016/j.automatica.2012.03.019
![]() |
[5] |
R. Li, K. L. Teo, K. H. Wong, G. R. Duan, Control parameterization enhancing transform for optimal control of switched systems, Math. Comput. Model., 43 (2006), 1393–1403. https://doi.org/10.1016/j.mcm.2005.08.012 doi: 10.1016/j.mcm.2005.08.012
![]() |
[6] |
X. Wu, K. Zhang, M. Cheng, Computational method for optimal control of switched systems with input and state constraints, Nonlinear Anal.: Hybrid Syst., 26 (2017), 1–18. https://doi.org/10.1016/j.nahs.2017.04.001 doi: 10.1016/j.nahs.2017.04.001
![]() |
[7] |
Y. Yang, F. Chen, J. Lang, X. Chen, J. Wang, Sliding mode control of persistent dwell-time switched systems with random data dropouts, Appl. Math. Comput., 400 (2021), 126087. https://doi.org/10.1016/j.amc.2021.126087 doi: 10.1016/j.amc.2021.126087
![]() |
[8] |
Q. Abushov, C. Aghayeva, Stochastic maximum principle for nonlinear optimal control problem of switching systems, J. Comput. Appl. Math., 259 (2014), 371–376. https://doi.org/10.1016/j.cam.2013.06.010 doi: 10.1016/j.cam.2013.06.010
![]() |
[9] | X. D. Koutsoukos, Optimal control of stochastic hybrid systems based on locally consistent markov decision processes, Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation Intelligent Control, 2005,435–440. https://doi.org/10.1109/.2005.1467054 |
[10] |
W. Zhang, J. Hu, J. Lian, Quadratic optimal control of switched linear stochastic systems, Syst. Control Lett., 59 (2010), 736–744. https://doi.org/10.1016/j.sysconle.2010.08.010 doi: 10.1016/j.sysconle.2010.08.010
![]() |
[11] |
X. Liu, K. Zhang, S. Li, S. Fei, H. Wei, Optimal control of switching times in switched stochastic systems, Asian J. Control, 17 (2015), 1580–1589. https://doi.org/10.1002/asjc.961 doi: 10.1002/asjc.961
![]() |
[12] |
X. Liu, S. Li, K. Zhang, Optimal control of switching time in switched stochastic systems with multi-switching times and different costs, Int. J. Control, 90 (2017), 1604–1611. https://doi.org/10.1080/00207179.2016.1214879 doi: 10.1080/00207179.2016.1214879
![]() |
[13] |
Y. Zhu, Uncertain optimal control with application to a portfolio selection model, Cybern. Syst.: Int. J., 41 (2010), 535–547. https://doi.org/10.1080/01969722.2010.511552 doi: 10.1080/01969722.2010.511552
![]() |
[14] |
H. Yan, Y. Zhu, Bang-bang control model for uncertain switched systems, Appl. Math. Model., 39 (2015), 2994–3002. https://doi.org/10.1016/j.apm.2014.10.042 doi: 10.1016/j.apm.2014.10.042
![]() |
[15] |
T. Jia, X. Chen, L. He, F. Zhao, J. Qiu, Finite-time synchronization of uncertain fractional-order delayed memristive neural networks via adaptive sliding mode control and its application, Fractal Fract., 6 (2022), 502. https://doi.org/10.3390/fractalfract6090502 doi: 10.3390/fractalfract6090502
![]() |
[16] |
Suriguga, Y. Kao, C. Shao, X. Chen, Stability of high-order delayed Markovian jumping reaction-diffusion HNNs with uncertain transition rates, Appl. Math. Comput., 389 (2021), 125559. https://doi.org/10.1016/j.amc.2020.125559 doi: 10.1016/j.amc.2020.125559
![]() |
[17] |
Y. Liu, Uncertain random variables: a mixture of uncertainty and randomness, Soft Comput., 17 (2013), 625–634. https://doi.org/10.1007/s00500-012-0935-0 doi: 10.1007/s00500-012-0935-0
![]() |
[18] |
Y. Liu, Uncertain random programming with applications, Fuzzy Optim. Decis. Making, 12 (2013), 153–169. https://doi.org/10.1007/s10700-012-9149-2 doi: 10.1007/s10700-012-9149-2
![]() |
[19] |
Y. Yu, X. Liu, Y. Zhang, Z. Jia, On the complete convergence for uncertain random variables, Soft Comput., 26 (2022), 1025–1031. https://doi.org/10.1007/s00500-021-06504-8 doi: 10.1007/s00500-021-06504-8
![]() |
[20] |
B. Li, X. Li, K. L. Teo, P. Zheng, A new uncertain random portfolio optimization model for complex systems with downside risks and diversification, Chaos, Solitons Fract., 160 (2022), 112213. https://doi.org/10.1016/j.chaos.2022.112213 doi: 10.1016/j.chaos.2022.112213
![]() |
[21] |
R. Gao, K. Yao, Importance index of components in uncertain random systems, Knowl.-Based Syst., 109 (2016), 208–217. https://doi.org/10.1016/j.knosys.2016.07.006 doi: 10.1016/j.knosys.2016.07.006
![]() |
[22] |
X. Chen, Y. Zhu, B. Li, Optimal control for uncertain random continuous-time systems, Optimization, 72 (2023), 1385–1428. https://doi.org/10.1080/02331934.2021.2017429 doi: 10.1080/02331934.2021.2017429
![]() |
[23] |
H. Ke, T. Su, Y. Ni, Uncertain random multilevel programming with application to production control problem, Soft Comput., 19 (2015), 1739–1746. https://doi.org/10.1007/s00500-014-1361-2 doi: 10.1007/s00500-014-1361-2
![]() |
[24] |
H. Dalman, Uncertain random programming models for fixed charge multi-item solid transportation problem, New Trends Math. Sci., 6 (2018), 37–51. https://doi.org/10.20852/ntmsci.2018.244 doi: 10.20852/ntmsci.2018.244
![]() |
[25] |
M. K. Mehlawat, P. Gupta, A. Z. Khan, Portfolio optimization using higher moments in an uncertain random environment, Inf. Sci., 567 (2021), 348–374. https://doi.org/10.1016/j.ins.2021.03.019 doi: 10.1016/j.ins.2021.03.019
![]() |
[26] |
J. Zhai, M. Bai, J. Hao, Uncertain random mean-variance-skewness models for the portfolio optimization problem, Optimization, 71 (2022), 3941–3964. https://doi.org/10.1080/02331934.2021.1928122 doi: 10.1080/02331934.2021.1928122
![]() |
[27] |
X. Chen, Y. Zhu, Optimal control for multistage uncertain random dynamic systems with multiple time delays, ISA Trans., 129 (2022), 171–191. https://doi.org/10.1016/j.isatra.2022.02.016 doi: 10.1016/j.isatra.2022.02.016
![]() |
[28] |
H. Yan, Y. Sun, L. Lin, Y. Zhu, A linear control problem of uncertain discrete-time switched systems, J. Ind. Manag. Optim., 13 (2017), 267–282. https://doi.org/10.3934/jimo.2016016 doi: 10.3934/jimo.2016016
![]() |
[29] |
W. Zhang, J. Hu, A. Abatet, On the value functions of the discrete-time switched LQR problem, IEEE Trans. Automat. Control, 54 (2009), 2669–2674. https://doi.org/10.1109/TAC.2009.2031574 doi: 10.1109/TAC.2009.2031574
![]() |
[30] |
X. Chen, Y. Zhu, B. Li, H. Yan, A linear quadratic model based on multistage uncertain random systems, Eur. J. Control, 47 (2019), 37–43. https://doi.org/10.1016/j.ejcon.2018.09.009 doi: 10.1016/j.ejcon.2018.09.009
![]() |
[31] | Y. Zhu, Functions of uncertain variables and uncertain programming, J. Uncertain Syst., 6 (2012), 278–288. |
[32] | S. Mirjalili, Genetic algorithm, In: Evolutionary algorithms and neural networks: theory and applications, 780 (2019), 43–55. https://doi.org/10.1007/978-3-319-93025-1 |
1. | Rania Saadeh, Laith Hamdi, Ahmad Qazza, 2024, Chapter 18, 978-981-97-4875-4, 259, 10.1007/978-981-97-4876-1_18 | |
2. | Saad Ihsan Butt, Ahmad Khan, Sanja Tipurić-Spužević, New fractal–fractional Simpson estimates for twice differentiable functions with applications, 2024, 51, 23074108, 100205, 10.1016/j.kjs.2024.100205 | |
3. | Rania Saadeh, Motasem Mustafa, Aliaa Burqan, 2024, Chapter 17, 978-981-97-4875-4, 239, 10.1007/978-981-97-4876-1_17 |