Abstract
In this paper, we present a new fractional variational problem where the Lagrangian depends not only on the independent variable, an unknown function and its left- and right-sided Caputo fractional derivatives with respect to another function, but also on the endpoint conditions and a free parameter. The main results of this paper are necessary and sufficient optimality conditions for variational problems with or without isoperimetric and holonomic restrictions. Our results not only provide a generalization to previous results but also give new contributions in fractional variational calculus. Finally, we present some examples to illustrate our results.
    Keywords:
                                                                    fractional calculus;                    Euler–Lagrange equation;                    natural boundary conditions;                    isoperimetric problems;                    holonomic-constrained problems        MSC:
                26A33; 49K05; 34A08
            1. Introduction
Non-integer calculus, known as fractional calculus, deals with integrals and derivatives with arbitrary real or complex orders [,]. It has developed in the past decades, becoming an important tool in applied sciences and engineering. Nowadays, fractional calculus is an important subject, e.g., in physics [,], robot trajectory controllers [], heat diffusion [], signal and image processing [], or biology [,].
A question that arises when dealing with fractional calculus is which fractional integral or derivative should we choose? There are several definitions proposed, such as Riemann–Liouville, Caputo, Hadamard, Erdélyi–Kober, Grünwald–Letnikov, Weyl, or Marchaud fractional operators. However, there are ways to overcome this issue, considering a more general class of operators. In [], we find the concept of fractional derivative with respect to another function. For particular choices of such function, we obtain some of the previous ones. We denote the fractional order by , and let  be a function with , for all . Given an integrable function , the left-sided and the right-sided Riemann–Liouville fractional integrals of x with kernel  are defined as
      
      
        
      
      
      
      
    
      and
      
      
        
      
      
      
      
    
      respectively, where  represents the Gamma function, and  is the order of the fractional integral. Moreover,
      
      
        
      
      
      
      
    
We can recognize that the Riemann–Liouville, the Hadamard and the Erdélyi–Kober fractional integrals are just particular cases of this more general definition. With respect to fractional differentiation, the left- and right-sided Riemann–Liouville fractional derivatives of x, with kernel , are given by the formulas
      
      
        
      
      
      
      
    
      and
      
      
        
      
      
      
      
    
      where . For simplicity, we call the last operators as -Riemann–Liouville fractional derivatives of x of order . It can be easily noticed that for certain choices of function , we recover some important fractional derivatives. We also remark that when , we have
      
      
        
      
      
      
      
    
It is worth mentioning that, opposite to the ordinary derivatives, fractional derivatives are non-local and, in the case of left-sided derivatives, take into account the past. This is particularly useful for problems in different areas, such as economics, epidemiology, and optimal control problems [,,,].
Recently, in [], motivated by the concept of Caputo fractional derivative and by these generalized fractional operators, the following definition was presented. Let  and  be defined by  if , and  if . Given two functions , with , for all , the left- and right-sided Caputo fractional derivatives of x with kernel  (or simply, -Caputo fractional derivatives of x), are defined as
      
      
        
      
      
      
      
    
      and
      
      
        
      
      
      
      
    
      respectively. Thus, if , then
      
      
        
      
      
      
      
    
For , then
      
      
        
      
      
      
      
    
      and
      
      
        
      
      
      
      
    
We now present the following formulas (see Lemma 1 in []) that are useful in Section 3. If , then
      
      
        
      
      
      
      
    
      and
      
      
        
      
      
      
      
    
Next, we present the following fractional integration by parts formulas that are fundamental for the proofs of our results. For a more detailed study of the -Caputo fractional derivatives, we refer to [].
Theorem 1. 
[] Let  and  be two functions. Then,
      
        
      
      
      
      
    and
      
        
      
      
      
      
    
In particular, when , Theorem 1 becomes
      
      
        
      
      
      
      
    
      and
      
      
        
      
      
      
      
    
Fractional calculus of variations started with the pioneering works of Riewe [,]. Since then, numerous works have appeared for different types of fractional derivatives and integrals. To mention a few in such vast literature, we can refer the reader to the books [,,]. The goal is to extremize (minimize or maximize) a given functional, depending on some fractional operator. Due to the large number of fractional operators to choose from, we found several works dealing with similar subjects (e.g., [,,,,,,]). By considering a more general form of fractional derivative, such as the one given in [], we can study different problems in a general form. In [], some calculus of variation problems were addressed, with dependence on this fractional derivative. Necessary and sufficient conditions of optimality were proven, such as the Euler–Lagrange equation, and the isoperimetric problem was studied, among others.
The main goal of this paper is to generalize the fractional variational problem studied in [], considering the case where the Lagrangian depends not only on the independent variable, an unknown function and its left- and right-sided Caputo fractional derivatives with respect to another function, but also on the endpoints conditions and a free parameter. This type of generalized fractional variational problems cannot be solved using the classical theory. Our motivation for studying generalized variational problems where the Lagrangian explicitly depends on state values and a free parameter comes from interesting applications in economics [] and in physics [], respectively. It is worth mentioning that, since these types of fractional derivatives are generalizations of several fractional derivatives and our variational problem is a generalization of different types of fractional variational problems, many results available in the literature are corollaries of the results proven in this paper.
The organization of the paper is as follows. We start Section 2.1 considering the generalized fractional variational problem with fixed boundary conditions and proving a necessary optimality condition of Euler–Lagrange type and also a necessary condition which arises as a consequence of the Lagrangian dependence of the parameter. Then, we prove the natural boundary conditions for variational problems with free boundary conditions. In Section 2.2, we prove necessary optimality conditions for variational problems with integral constraints, with and without fixed boundary conditions. The variational problem with an holonomic constraint is studied in Section 2.3. In Section 2.4, we prove sufficient optimality conditions for the variational problems considered in the previous subsections. We conclude the paper with some illustrative examples and concluding remarks.
2. Main Results
In this work, we consider a functional depending on time, on the state function x, its fractional derivatives  and  of orders , the values  and , and a free parameter . More specifically, we will study the following generalized fractional variational problem.
Problem: Determine  and  such that
      
      
        
      
      
      
      
    
      where  and
      
      
        
      
      
      
      
    
We will consider problem  with fixed boundary conditions
      
      
        
      
      
      
      
    
      for some , and when  and  are free. We will also consider problem  subject to an isoperimetric constraint
      
      
        
      
      
      
      
    
      for some  and to an holonomic constraint
      
      
        
      
      
      
      
    
      for a given function g.
Remark 1. 
We remark that:
- If the function , and the Lagrange function does not depend on a free parameter ζ, then we get the fractional variational problem studied in [];
 - Taking , and if ψ is the identity, the operators and can be replaced by and , respectively (see []). Hence, if α and β goes to 1, our functional tends to the generalized variational functional of the classical calculus of variations studied in [];
 - If , α and β goes to 1, and the Lagrange function does not depend on the state values and on a free parameter, functional reduces to the functional from Lemma 2.2.2 in [].
 
Next, we proceed with some basic definitions that are useful in what follows.
Definition 1. 
Definition 2. 
We say that  is a local minimizer (resp. local maximizer) for the functional  if there exists some , such that, for all  with , we have  (resp. ), where . The pair  is called a local extremizer of .
If  (resp. ) holds for all , then we say that  is a global minimizer (resp. global maximizer). In these cases, we say that  is a global extremizer of .
2.1. Generalized Fractional Variational Principle
The following result provides necessary conditions for an admissible pair  to be a local extremizer of functional , where x satisfies the boundary conditions (2). The equation
        
      
        
      
      
      
      
    
        is called the Euler–Lagrange equation. We will represent it by . To simplify, consider the two following conditions:
      
        
      
      
      
      
    
        and
        
      
        
      
      
      
      
    
        where H is a function and i a positive integer.
Theorem 2 
Proof.  
Let  be a local extremizer for functional  subject to (2),  an admissible variation and  an arbitrary real number. Define the new function  by . Since  is a local extremizer of , then . Therefore, the following condition holds
          
      
        
      
      
      
      
    
Using the fractional integration by parts formulas stated in Theorem 1, we get
          
      
        
      
      
      
      
    
Since , then
          
      
        
      
      
      
      
    
Taking  and using the arbitrariness of , by Lemma 2.2.2 in [], we obtain (4).
Taking the admissible variation  to be null, we deduce from (6) that
          
      
        
      
      
      
      
    
By the arbitrariness of , we conclude that
          
      
        
      
      
      
      
    
          proving (5).    □
Remark 2. 
In Theorem 2, since the state values  and  are fixed, the Lagrangian’s explicit dependence on  and  is irrelevant. However, in Theorem 3, since the state values can be free, this dependency is effective.
We remark that, although the functional  depends only on -Caputo fractional derivatives, the Euler–Lagrange equation involves -Riemann–Liouville fractional derivatives. Using the relations (see Theorem 3 in [])
        
      
        
      
      
      
      
    
        and
        
      
        
      
      
      
      
    
        it is possible to write Equation (4) using only -Caputo fractional derivatives.
Definition 3. 
We say that a pair  is an extremal of functional  if  satisfies the Euler-Lagrange Equation (4).
We now consider the case when the values  and  are not necessarily specified. For each boundary condition missing, there is a corresponding natural boundary condition, as given by Theorem 3.
Theorem 3(Generalized fractional natural boundary conditions). 
Suppose that L satisfies  and . If  is a local extremizer of functional , then (4) and (5) hold. Moreover,
- If is free, then
 - If is free, then
 
Proof.  
Suppose that  is a local extremizer of functional . Let  and  be an arbitrary real number. Let . Since no boundary conditions are imposed,  do not need to be null at the endpoints. However, since Equation (6) must be satisfied for all , it is also satisfied for those functions that vanish at the endpoints. Using the same arguments used in the proof of Theorem 2, one can conclude that  satisfies the necessary conditions (4) and (5).
          
□
From Theorem 3, we can obtain the following corollaries. Note that if L does not depend on the parameter , then condition (5) is trivially satisfied and we get the following results.
Corollary 1. 
If x is a local extremizer of
      
        
      
      
      
      
    then x satisfies the generalized fractional equation , where
      
        
      
      
      
      
    Moreover,
- If is free, then x satisfies the following condition
 - If is free, then x satisfies
 
If the Lagrangian function does not depend on the state values  and , and on a real parameter , then we get the following result.
Corollary 2. 
If x is a local extremizer of functional
      
        
      
      
      
      
    then x satisfies  where  Moreover,
- If is free, then x satisfies the following condition
 - If is free, then x satisfies
 
Remark 3. 
Note that
- If we consider , for all , in Corollary 1 and Corollary 2, we obtain Theorem 3.1 from [] and Theorem 1 from [], respectively;
 - The comparision of the natural boundary conditions (9) and (10) with (11) and (12) shows that the fractional problems of the calculus of variations, where the functional to extremize explicitly depends on and/or , are of a different nature when compared with the case where the Lagrangian does not depend on the endpoint conditions.
 
2.2. Generalized Fractional Isoperimetric Problems
In this section, we deal with variational problems with integral constraints. Besides some possible boundary conditions, we impose on the set of admissible functions an integral restriction of type (3) (see, e.g., []). Such kinds of problems are known in the literature as isoperimetric problems. An example of this type of problem is Queen Dido’s problem, probably the oldest problem in the calculus of variations, which consists of finding, among all the closed curves of the plane of a given perimeter, the curve that encloses the maximum area (see, e.g., []).
Before presenting necessary optimality conditions for such kind of variational problems, we first present the following definition.
Definition 4. 
In the next two results, we prove necessary optimality conditions for generalized fractional isoperimetric problems, with and without fixed boundary conditions, respectively, for the particular case of normal extremizers.
Theorem 4 (Necessary optimality conditions for normal extremizers to fractional isoperimetric problems I). 
Proof.  
Consider variations , where  are admissible variations, with , and  are arbitrary real numbers, for . Let  be the functions defined by
          
      
        
      
      
      
      
    
          and
          
      
        
      
      
      
      
    
Note that
          
      
        
      
      
      
      
    
Since , we conclude that
          
      
        
      
      
      
      
    
      
        
      
      
      
      
    
Observing that  is not an extremal of functional , one concludes that
          
      
        
      
      
      
      
    
          for some . Then we can choose , such that . Since , there exists an open set , such that  and there exists  such that  and , for all . This means that there exists an infinite family of pairs  where  and , which satisfies the isoperimetric constraint (3). Now, we proceed proving the necessary conditions. Observe that  is a local extremizer of function , subject to the constraint , and we just proved that . Then, by the Lagrange Multiplier Rule, there exists a real number  such that . Observe that
          
      
        
      
      
      
      
    
          and
          
      
        
      
      
      
      
    
Denoting , we get
          
      
        
      
      
      
      
    
Since the last equation must hold for any , then, in particular, we can conclude that
          
      
        
      
      
      
      
    
From Lemma 2.2.2 in [], we obtain
          
      
        
      
      
      
      
    
          proving Equation (13). Introducing the Euler–Lagrange Equation (13) into (16), one gets
          
      
        
      
      
      
      
    
From the arbitrariness of , we get
          
      
        
      
      
      
      
    
          proving (14).    □
Theorem 5 
(Necessary optimality conditions for normal extremizers to fractional isoperimetric problems II). Suppose that , , , and  hold. Let  be a normal extremizer of functional , subject to (3). Then, there exists , such that defining ,  satisfies Equations (13) and (14). Moreover,
- 1.
 - If is not fixed then
 - 2.
 - If is not fixed then
 
Proof.  
The idea of the proof is to combine the methods presented in the proofs of Theorem 3 and Theorem 4.    □
Theorem 6 
(Necessary optimality conditions for normal and abnormal extremizers to fractional isoperimetric problems). Suppose that , , , and  hold. Let  be a local extremizer of functional , subject to the integral constraint (3). Then, there exists a vector , such that, defining the Lagrangian function , then Equations (13) and (14) hold, as well the natural boundary conditions (17) and (18).
Proof.  
First, suppose that  is a normal extremizer. Then, the results follow from Theorem 5 fixing . Otherwise, we consider .    □
2.3. Generalized Fractional Holonomic Constrained Problems
We now turn our attention to what is called in the literature as holonomic constrained problems. Suppose that the state variable x is a two-dimensional vector . Thus, functional  is defined as
        
      
        
      
      
      
      
    
        where
        
- , , and ;
 - and ;
 - .
 
Boundary conditions are
        
      
        
      
      
      
      
    
        for some  and the holonomic constraint is
        
      
        
      
      
      
      
    
        where g is a given  function.
Theorem 7 
Proof.  
Consider variations of  of type , where  is a differentiable function with . Since variations must fulfill the holonomic constraint, we have that
          
      
        
      
      
      
      
    
          for all . Differentiating Equation (25) with respect to  and taking , we get that
          
      
        
      
      
      
      
    
Using the boundary conditions of , Equation (26) becomes
          
      
        
      
      
      
      
    
Define function  as
          
      
        
      
      
      
      
    
Hence, Equation (23) is proven for the case . Now, we prove the remaining conditions. Since  is an extremizer of functional , its first variation must vanish when evaluated at , that is,
          
      
        
      
      
      
      
    
By Theorem 1, we obtain
          
      
        
      
      
      
      
    
Therefore,
          
      
        
      
      
      
      
    
Now, we deduce the natural boundary conditions, for the case where  and  are free.
Theorem 8 
(Natural boundary conditions with an holonomic constraint). Let  be an extremizer of functional , as in (19), subject to the holonomic constraint (21) such that Equation (22) holds, and to the remaining assumptions of Theorem 7. Then, there exists  satisfying (23) and (24). Moreover,
- If is not fixed, then, for ,
 - If is not fixed, then, for ,
 
2.4. Sufficient Optimality Conditions
Now, we focus on sufficient conditions that guarantee the existence of extremizers of functional . We consider fractional variational problems with or without an isoperimetric and holonomic restrictions. Our results are presented in the general case where the state values are not fixed.
Definition 5. 
We say that  is jointly convex (resp. jointly concave) in  if, for all ,  exist and are continuous and verify
      
        
      
      
      
      
    for all  and where 
Theorem 9. 
Proof.  
We shall give the proof only for the case where L is jointly convex; the other case is similar. Let  and  be arbitrary. Since L is jointly convex in , we get
          
      
        
      
      
      
      
    
A similar result can be proved for isoperimetric problems.
Theorem 10. 
Suppose L is jointly convex (resp. jointly concave) in , and also that there exists a real number λ such that  is jointly convex (resp. jointly concave) in . Let . If  satisfies the necessary conditions (13) and (14) and (17) and (18), then  is a global minimizer (resp. global maximizer) of functional  subject to the isoperimetric constraint (3).
Proof.  
We shall give the proof only for the case where L and  are jointly convex; the proof of the other case is analogous. Since M is jointly convex then, by Theorem 9,  is a global minimizer of functional  defined by
          
      
        
      
      
      
      
    
Hence, for any  and , one has
          
      
        
      
      
      
      
    
          and, therefore,
          
      
        
      
      
      
      
    
If we restrict to the integral constraint (3), we can conclude that
          
      
        
      
      
      
      
    
          proving the desired result.    □
Finally, a sufficient condition of optimality is proven when in the presence of an holonomic constraint.
Theorem 11. 
Suppose L is jointly convex (resp. jointly concave) in . Let function λ be defined by (28), where g is a  function, such that , for all . If  satisfies the necessary conditions (23) and (24) and the natural boundary conditions (31) and (32), then  is a global minimizer (resp. global maximizer) of functional  as in (19), subject to the holonomic constraint (21).
3. Examples
In this section we present three examples in order to illustrate some results developed in the previous section. In all the examples, we suppose that functions L and  satisfy the needed assumptions.
Example 1. 
  
    
      
      
    
  
  
Suppose we intend to minimize
      
        
      
      
      
      
    in the class of functions , subject to the restriction  ( is free). From Theorem 3, every local extremizer of functional  satisfies the following necessary conditions:
- ;
 - ;
 
Since the Lagrangian function is jointly convex, by Theorem 9, the solution of this system is actually a minimizer of . Observe that, when  and , our problem tends to
      
        
      
      
      
      
    with , and the necessary conditions are
- ;
 - ;
 - .
 
From , we get , for some . Since , then . Since
      
        
      
      
      
      
    we can conclude that  Hence,
      
        
      
      
      
      
    is the only candidate to be a local extremizer of functional , and, since  is jointly convex,  is the global minimizer. Solving the fractional problem analytically is very difficult, and thus a numerical technique is applied. In Figure 1, we show the results. Four different fractional orders are considered, and, as can be observed, the solution converges to  as α goes to one.
      
    
    Figure 1.
      Numerical solutions for Example 1.
  
Example 2. 
Suppose we intend to minimize
      
        
      
      
      
      
    
      
        
      
      
      
      
    in the class of functions , subject to the restriction  ( is free). From Theorem 3 every local extremizer of functional  satisfies the following necessary conditions:
- ;
 - ;
 
Observe that the function  defined by
      
        
      
      
      
      
    is such that
      
        
      
      
      
      
    hence, x satisfies the Euler–Lagrange equation given in 1. Moreover, x satisfies the natural boundary condition given by 3 if , that is,
      
        
      
      
      
      
    
We remark that if , then we are dealing with the Caputo derivative and the identity (35) holds. Hence,
      
        
      
      
      
      
    is a possible local minimizer of functional . Observing that, for every function , we have
      
        
      
      
      
      
    and since , then  is indeed a global minimizer of .
Example 3. 
The goal is to minimize
      
        
      
      
      
      
    in the class of functions , subject to the restriction  ( is free) and to the integral constraint
      
        
      
      
      
      
    
We assume that the kernel fulfills the condition . Fix  and define
      
        
      
      
      
      
    
From Theorem 6, every local extremizer of functional  subject to the integral constraint (36) satisfies the following conditions:
- ;
 - ;
 
Define  and  by . In this case,
      
        
      
      
      
      
    and, therefore,
      
        
      
      
      
      
    
Hence,  satisfies the integral constraint (36) and the necessary conditions 1–3.
4. Conclusions and Future Work
In this work, we proved necessary and sufficient conditions of optimality, where the Lagrangian function depends on a general form of fractional derivative, a free parameter, and the state values. The Euler–Lagrange equation was deduced, for the fundamental problem, as well when in presence of constraints. With some examples, we show the applicability of the procedure.
For future, direct methods can be studied to deal with such generalized fractional variational problems. One possible direction is to study discretizations of the fractional derivative and then convert the problem as a finite dimensional case. In addition, other optimization conditions could be obtained, e.g., with arbitrary fractional orders , or optimal control problems where the state equation involves the -Caputo fractional derivative.  
Author Contributions
Conceptualization, R.A. and N.M.; methodology, R.A. and N.M..; formal analysis, R.A. and N.M.; investigation, R.A. and N.M.; writing—original draft preparation, R.A. and N.M..; writing—review and editing, R.A. and N.M.. All authors have read and agreed to the published version of the manuscript.
Funding
This work is supported by Portuguese funds through the CIDMA (Center for Research and Development in Mathematics and Applications), and the Portuguese Foundation for Science and Technology (FCT—Fundação para a Ciência e a Tecnologia), within project UIDB/04106/2020.
Data Availability Statement
The study did not report any data.
Conflicts of Interest
The authors declare no conflict of interest.
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