Abstract
The paper deals with a two-person zero-sum differential game for a dynamical system described by differential equations with the Caputo fractional derivatives of an order and a Bolza-type cost functional. A relationship between the differential game and the Cauchy problem for the corresponding Hamilton–Jacobi–Bellman–Isaacs equation with fractional coinvariant derivatives of the order and the natural boundary condition is established. An emphasis is given to construction of optimal positional (feedback) strategies of the players. First, a smooth case is studied when the considered Cauchy problem is assumed to have a sufficiently smooth solution. After that, to cope with a general non-smooth case, a generalized minimax solution of this problem is involved.
1. Introduction
The paper follows the positional approach (see, e.g., [1,2,3]) and is concerned with the questions of how to characterize the value functional and construct optimal positional (feedback) strategies of the players in a two-person zero-sum differential game for a dynamical system described by differential equations with the Caputo fractional derivatives of an order and a given Bolza-type cost functional. For the basics of fractional calculus and the theory of fractional differential equations, the reader is referred to, e.g., [4,5,6]. Investigations of some other kinds of differential games for fractional-order systems can be found in, e.g., [7,8,9,10,11,12,13].
The differential game under consideration was previously studied in [14,15]. More precisely, in [14], based on a suitable approximation of the game by a differential game for a (first-order) time-delay system, it was proved that the original game has the value, and, moreover, optimal positional strategies of the players were obtained in the form of control procedures that use the approximating time-delay system as a guide (see, e.g., [1] (Section 8.2)). In [15], the characteristic u- and v-stability properties of the value functional were established, and optimal positional strategies of the players were built by a suitable modification of the method of extremal shift to accompanying points (see, e.g., [2] (Section 8)). It should be noted that the results obtained in [14,15] demonstrate a close relationship between positional differential games for fractional-order systems and that for time-delay systems.
The present paper continues these studies and proposes another way of constructing optimal positional strategies of the players, which is based on a different technique. Motivated by [16], the differential game under consideration is associated to the Cauchy problem for the corresponding Hamilton–Jacobi–Bellman–Isaacs equation with fractional coinvariant (-) derivatives of the order and the natural boundary condition. Then, at a first step, a particular case is studied when it is additionally assumed that this Cauchy problem admits a sufficiently smooth (namely, -smooth of the order ) solution. Using standard arguments (see, e.g., [3] (Section 11.5) and also [17] for time-delay systems), it is proved that this solution coincides with the value functional of the original differential game, and, furthermore, optimal positional strategies of the players can be obtained by applying the extremal aiming in the direction of the -gradient of the order of this solution.
In a general non-smooth case, following, e.g., [3], it is shown that the value functional coincides with a generalized minimax solution of the given Cauchy problem [18,19]. The proof of this fact reduces to construction of optimal positional strategies of the players on the basis of this minimax solution. To this end, by analogy with, e.g., [20] and [3] (Section 12.2) (see also, e.g., [17,21] for time-delay systems), some “smoothing” transformation of the minimax solution is performed, which makes it possible to determine the desired extremal directions that can be used in the extremal aiming procedure instead of the -gradient of the order (since it may fail to exist for the minimax solution). It should be emphasized that peculiarities inherent in fractional-order systems are handled with the help of a suitable choice of a Lyapunov–Krasovskii functional [19], which the transformation relies on.
The rest of paper is organized as follows. In Section 2, basic notation is given. The dynamical system of a fractional order and cost functional are described in Section 3. In Section 4, the value functional of the differential game is defined in terms of non-anticipative strategies of the players. In Section 5, positional strategies of the players are introduced. The Cauchy problem for the Hamilton–Jacobi–Bellman–Isaacs equation is formulated in Section 6. Section 7 deals with the case when the Cauchy problem has a smooth solution. In Section 8, the generalized minimax solution of this problem is considered, and its “smoothing” transformation is performed. Section 9 is devoted to the general non-smooth case. Concluding remarks are presented in Section 10.
2. Notation
Let , , and be fixed throughout the paper. By and , the Euclidean norm and inner product in are denoted. Given , let stand for the closed ball in centered at the origin of radius R.
For every , following, e.g., [4] (Definition 2.3), let us consider the set of all functions that can be represented in the form
for some (Lebesgue) measurable and essentially bounded function . Here, the second term is the (left-sided) Riemann–Liouville fractional integral of the order of the function (see, e.g., [4] (Definition 2.1)), and is the gamma function. The set is a linear space, and every function is continuous (see, e.g., [4] (Remark 3.3)). Let be endowed with the norm
According to, e.g., [4] (Theorem 2.4), the (left-sided) Caputo fractional derivative of the order of a function , which is defined by (see, e.g., [5] (Section 2.4) and [6] (Chapter 3))
exists for almost every (a.e.) .
Finally, let us introduce the set G of all pairs such that and . This set is endowed with the metric (see, e.g., [17] and also [16])
where , and
Note that, by [16] (Proposition 8.2), the mappings for a fixed and are continuous, as well as, in view of the Arzelà–Ascoli theorem, the mapping . Here, the symbol means the restriction of the function to the interval , i.e.,
3. Dynamical System of Fractional Order and Cost Functional
The paper deals with a two-person zero-sum differential game in which the dynamical system is described by the fractional differential equation
where is time, is the current state of the system, is the Caputo derivative of the order , and are the current controls of the first and second players, respectively, and are compact sets, , .
Assumption 1.
The function is continuous and possesses the following two properties: for every , one can choose a number such that
and there exists a constant such that
As an initial data for system (2), we consider a pair , which is called an initial position of the system (see, e.g., [14,15,16]). Here, t is an initial time, and the function is treated as an initial history of a system’s motion. Thus, in view of notation (1), the initial condition takes the form . By admissible (open-loop) controls of the first and second players on the time interval , we mean any measurable functions and , respectively. Let and be the corresponding sets of all such controls. Denote
According to, e.g., [14] (Proposition 2), from the initial position , every pair of controls and generate a unique motion of system (2), which is defined as a function that, together with and , satisfies the fractional differential equation in (2) for a.e. .
For system (2), a differential game is studied in which the first player wants to minimize, and the second player wants to maximize the cost functional
where is the motion of system (2) generated from the initial position by the players’ controls and .
Assumption 2.
The mappings and are continuous, and, for every , one can find a number such that
4. Value Functional
The value functional of the differential game (2) and (5) is defined with the help of non-anticipative strategies of the players.
Let an initial position be fixed. By a non-anticipative strategy of the first player, we mean a mapping possessing the following property: for any and any second player’s controls , , if the equality holds for a.e. , then the corresponding first player’s controls and satisfy the equality for a.e. . Then, the lower value of the differential game is given by
where the infimum is calculated over all first player’s non-anticipative strategies .
Similarly, a second player’s non-anticipative strategy is a mapping such that, for every and every , , if for a.e. , then for a.e. , where and . Respectively, the upper value of the differential game is given by
where the supremum is calculated over all second player’s non-anticipative strategies .
Let us suppose that, in addition to Assumptions 1 and 2, the following Isaacs’ condition, also known as the saddle point condition in a small game, is fulfilled.
Assumption 3.
The equality below is valid:
Then, according to, e.g., [15] (Section 9), for every initial position , the lower and upper game values coincide, which means that the differential game (2) and (5) has the value
Thus, relation (8) defines the game value functional .
It should be noted that non-anticipative strategies, being a convenient tool in theoretical considerations, are rather difficult to implement. In this regard, the paper focuses on construction of optimal positional (feedback) strategies of the players, which are more acceptable from a practical point of view.
5. Positional Strategies
In accordance with [14,15], as a first player’s positional strategy in the differential game (2) and (5), we consider an arbitrary mapping . Let be an initial position, and let be a partition of the time interval , i.e.,
where . Here, and below, we use the notation . The pair is called a control law of the first player. From the initial position , this law together with a second player’s control uniquely generate the first player’s control (and, respectively, the corresponding motion of system (2)) by the following step-by-step rule:
and, formally, . In other words, at every time , , the first player measures the history of the motion on (see (1)), computes the value , and then applies the constant control until , when a new measurement of the history is taken. Let us denote the corresponding value of cost functional (5) by .
Observe that, by construction, the mapping that assigns to each second player’s control the first player’s control formed by is a non-anticipative strategy of the first player. Hence, in view of (6) and (8), we have
In this connection, given a set and a number , a positional strategy of the first player U is called -optimal uniformly on K if the following property holds: there exists such that, for any initial position and any partition of with the diameter , the inequality
takes place. Respectively, we say that the strategy U is optimal uniformly on the set K if it is -optimal uniformly on this set for every .
Similarly, any mapping is considered as a positional strategy of the second player. Given an initial position , a partition of the time interval , and a first player’s control , let be the value of cost functional (5) that corresponds to the second player’s control formed by the law as follows:
and, formally, . Due to (7) and (8), the estimate below is valid:
Then, for a set and a number , a positional strategy of the second player V is called -optimal uniformly on K if there exists such that the inequality
is fulfilled for any and any partition of with . We say that V is optimal uniformly on K if it is -optimal uniformly on K for every .
6. Hamilton–Jacobi–Bellman–Isaacs Equation
Denote . According to [16], a functional is called coinvariantly (-) differentiable of the order at a point if there exist and such that, for every function (see (4)), the following relation holds:
where is determined by (1), the function may depend on t and , and when . The values and are called, respectively, the -derivative in t and -gradient of the order of at .
To the differential game (2) and (5), we associate the Hamiltonian (see Assumption 3)
and the Cauchy problem for the Hamilton–Jacobi–Bellman–Isaacs equation
under the right-end boundary condition
The unknown in problem (13) and (14) is a functional .
The goal of the paper is to establish a relationship between the differential game (2) and (5) and the Cauchy problem (13) and (14) with a particular emphasis on construction of optimal and -optimal positional control strategies of the players. Let us first study this question under an additional supposition that the Cauchy problem (13) and (14) admits a sufficiently smooth solution.
7. Optimal Positional Strategies in the Smooth Case
Following [16], we say that a functional is -smooth of the order if it is continuous, -differentiable of the order at every point , and the mappings and are continuous. If such a functional satisfies the Hamilton–Jacobi–Bellman–Isaacs equation (13) and boundary condition (14), then it is called a classical solution of the Cauchy problem (13) and (14).
Let us suppose that a classical solution of the Cauchy problem (13) and (14) exists. In this case, let us define players’ positional strategies and by applying the extremal aiming in the direction of the -gradient of the order of this solution:
and, formally, let and be chosen arbitrarily for any .
Theorem 1.
Let Assumptions 1, 2, and 3 hold. In addition, suppose that the Cauchy problem (13) and (14) admits a classical solution . Then, this solution φ coincides with the value functional of the differential game (2) and (5), i.e.,
and the players’ positional strategies and defined by this solution φ according to (15) are optimal uniformly on each compact set .
The proof of the theorem follows the scheme from, e.g., [3] (Section 11.5) (see also [17] (Theorem 3.1) for time-delay systems), and, for convenience, it is divided into the two lemmas below, which are valid under the assumptions of the theorem.
Lemma 1.
For every compact set and every , there exists such that, for any initial position , any partition Δ of with , and any second player’s control , the inequality below holds:
Before proceeding to the proof of the lemma, let us carry out some auxiliary constructions, which are also needed in the subsequent sections. Denote
where c is the constant from (3) and is the set from (4). Let a compact set be given. Consider the set
According to [22] (Theorem 2), compactness of the set K implies compactness of the set in . In particular, by the Arzelà–Ascoli theorem, all functions are uniformly bounded and equicontinuous. Let a number be such that
Then, in view of (3), the following estimate is valid:
Furthermore, due to continuity of the functions f and , let us take a number and a modulus of continuity such that
Proof of Lemma 1.
Let a compact set and be fixed. Define the compact set , number , and modulus of continuity as above. Since the functional is continuous, one can choose from the condition
Then, owing to continuity of the mappings and , there are a number and a modulus of continuity such that
Let us show that the conclusion of the lemma holds for satisfying the inequality
Take an initial position and a partition of with . Consider a motion of system (2) generated by the first player’s control law and a second player’s control . Let be the corresponding first player’s control. Observe that the inclusion is fulfilled by (3), (18), and (19).
Let us introduce the function
Then, we have and, in accordance with (5) and (14), we obtain . Thus, the desired inequality (17) can be rewritten as follows:
Now, let us suppose that . Similarly to (27), we get , and, therefore, in order to prove (26), it suffices to verify that
Since the functional is -smooth of the order , based on [16] (Lemma 9.2), we conclude that the function is Lipschitz continuous on and
Here, and below, we use the notation . Consider for which equality (29) is valid. Let be such that . Then, estimates (21), (22), and (24) and the choice (25) of imply that
According to (9), we have . Hence, it follows from the definition (15) of the strategy and the definition (12) of the Hamiltonian H that
Putting together relations (30) and (31) and taking into account that the functional satisfies Equation (13), we arrive at the inequality for a.e. , which in turn yields (28). The lemma is proved. □
Lemma 2.
For every compact set and every , there exists such that, for any initial position , any partition Δ of with , and any first player’s control , the inequality below holds:
In view of relation (12), the proof of Lemma 2 repeats that of Lemma 1 with clear changes and, therefore, is omitted.
Proof of Theorem 1.
Given an initial position , it follows from Lemma 1 and inequality (10) that . Similarly, due to Lemma 2 and inequality (11), we derive . Hence, we obtain the desired equality (16). Taking this equality into account, we conclude that Lemmas 1 and 2 imply that the players’ positional strategies and are optimal uniformly on each compact set . □
8. Minimax Solution
Under Assumptions 1 and 2, the Hamiltonian H and the boundary functional in the Cauchy problem (13) and (14) satisfy requirements – and from [19]. Hence, by [19] (Theorem 6.1), the problem (13) and (14) has a unique minimax solution, which is defined as a continuous functional that meets boundary condition (14) and possesses the following two properties:
- (i)
- For any , any , any , and any , there exists a function such that
- (ii)
- For any , any , any , and any , there exists a function such that
Let us note that, in view of [19] (Section 4), if the Cauchy problem (13) and (14) admits a classical solution, then it coincides with the minimax solution of this problem. On the other hand, if the minimax solution is -differentiable of the order at some point , then it satisfies equation (13) at this point, and, consequently, if the minimax solution turns out to be -smooth of the order , then it is a classical solution.
In a general case, the minimax solution of the Cauchy problem (13) and (14) is not -differentiable of the order at some points . Therefore, the extremal aiming procedure (15) can not be directly applied in this case. In order to overcome this difficulty and obtain the desired positional strategies of the players, we follow, e.g., [20] and [3] (Section 12.2) (see also, e.g., [17,21] for time-delay systems) and perform some “smoothing” transformation of the minimax solution .
This transformation relies on the Lyapunov–Krasovskii functional proposed in [19]. Namely, let a compact set be given, and let the corresponding compact set be defined by (19). Then, according to [19] (Section 5.1.4), one can choose and construct continuous mappings
such that the following properties are fulfilled:
- (a)
- For any , the functional is nonnegative, and the estimate holds for every when , ;
- (b)
- For any and any , , the function , , is Lipschitz continuous, and, for a.e. ,
- (c)
- If and , satisfy the equality , then
- (d)
- For any and any , there is such that, given and , meeting the conditions and , the inequality is valid.
Furthermore, consider the set
where is the set from (18), and denote
Observe that , and, for any , any , and any , the inclusion is fulfilled. Moreover, since the set K is compact, it follows from [22] (Theorem 2) that the set is compact in G, which in turn implies compactness of the set in for every .
Now, given a number , by the minimax solution of the Cauchy problem (13) and (14), let us define the functional according to the equality
where the minimum is attained due to continuity of the functionals and . After that, let us choose
and, taking the functional from (32), put
The vector serves as the desired extremal direction that is used in the next section instead of when constructing a positional strategy of the first player by applying the extremal aiming (15).
Similarly, from the point of view of the second player, let us define
where
9. Optimal Positional Strategies in a General Case
Let be the minimax solution of the Cauchy problem (13) and (14), and let be a compact set. In accordance with the previous section, let us take the corresponding number and set , and, for every and every , determine the extremal directions and . Then, for any , taking (15) into account, let us define players’ positional strategies and as follows:
and, formally, let us choose and for arbitrarily.
Theorem 2.
Let Assumptions 1, 2, and 3 be fulfilled. Then, the minimax solution of the Cauchy problem (13) and (14) coincides with the value functional of the differential game (2) and (5), and, given a compact set and a number , one can find such that, for any , the players’ positional strategies and defined by the minimax solution φ and the set K according to (38) are ζ-optimal uniformly on this set K.
The proof follows the scheme from, e.g., [20] and [3] (Theorem 12.3) (see also, e.g., [21] (Theorem 1) for time-delay systems). Let us establish two lemmas below, which are valid under the assumptions of the theorem.
Lemma 3.
For every compact set and every , there exist a number and a function such that, for any , any initial position , any partition Δ of with , and any second player’s control , the inequality below holds:
Proof.
By a fixed compact set , define the compact set , numbers and , and modulus of continuity by (19), (20), and (22). Since the functional is continuous, one can find such that
Let be fixed. By the numbers and , let us choose the number according to property (see Section 8) and then put . Now, let be given. Due to continuity of the mappings and from (32), there exist a number and a modulus of continuity such that
Finally, let us choose a number satisfying the inequality
Let us show that the conclusion of the lemma holds for the specified number and function .
Take arbitrarily , an initial position , and a partition of with . Consider a motion of system (2) generated by the first player’s control law and a second player’s control . Let be the corresponding first player’s control. Observe that, due to (3), (18), (19), and (33), the inclusions and , , are fulfilled.
Following the lines of the proof of Lemma 1, let us introduce the function
where is the functional from (35). Let us first estimate the value from above. Since according to (34) and in view of property and the definition of , we have
Now, let us estimate the value from below. Note that . Hence, arguing by analogy with (44) and after that applying (14) and (40), we derive
On the other hand, taking into account the choice (36) of the function and the inclusion , we obtain
It follows from (45) and (46) that
Therefore, in accordance with the equality , which is valid by the definition (34) of the set , the choice of yields
Thus, based on (46), since the functional is nonnegative due to property , we conclude that
Consequently, in view of (5), we get
Relations (44) and (47) imply that, in order to obtain the desired inequality (39), it suffices to verify that . If , this estimate obviously holds, so let us prove it in the case when . To this end, let us show that, for every , the inequality below is valid:
For brevity, let us denote (see (36) and (37))
By the definition (43) of the function , we have
Furthermore, due to the definition (35) of the functional , we get
Taking into account that the minimax solution possesses property , let us choose a function from the condition
Since and , we obtain that , , and . In particular, we derive , and, therefore,
Thus, relations (49)–(52) imply that
Let us estimate the values from the right-hand side of (53) from above. In view of the definition (12) of the Hamiltonian H and inequalities (22) and (41), we have
Now, let us consider the auxiliary function
Observe that
Moreover, property yields that the function is Lipschitz continuous, and
Then, applying (18), (20)–(22), and (41), for a.e. , we get (see also (30))
According to (9), we have , . Hence, if follows from the definition (38) of the strategy and the definition (12) of the Hamiltonian H that
Finally, owing to property , we obtain
Lemma 4.
For every compact set and every , there exist a number and a function such that, for any , any initial position , any partition Δ of with , and any first player’s control , the inequality below holds:
The proof of Lemma 4 repeats that of Lemma 3 with clear changes in view of relation (12) and property of the minimax solution .
Thus, it remains to observe that Lemmas 3 and 4 imply Theorem 2 by essentially the same arguments as in the proof of Theorem 1.
Remark 1.
One can show that Theorems 1 and 2 are valid if, instead of Assumption 3, we assume only that relation (12) holds. In this case, the existence of the value of the differential game (2) and (5) does not follow from [15] but can be proved based on Lemmas 3 and 4 by the scheme from, e.g., [14] (Theorem 1).
10. Conclusions
In the paper, a two-person zero-sum differential game for a dynamical system described by differential equations with the Caputo fractional derivatives of an order and a Bolza-type cost functional has been studied. The Cauchy problem for the associated Hamilton–Jacobi–Bellman–Isaacs equation with fractional coinvariant derivatives of the order and the natural boundary condition has been considered. It has been proved that the value functional of the differential game coincides with the unique generalized minimax solution of the given Cauchy problem, and a new way of constructing optimal positional strategies of the players has been proposed. Moreover, a particular case has been investigated in detail when it is additionally assumed that the Cauchy problem admits a classical solution.
Despite the fact that the results obtained in the paper are of a theoretical nature, they may serve in the future as a necessary basis for constructing solutions of specific differential games for fractional-order systems.
Funding
This research was funded by the Russian Science Foundation Grant No. 19-71-00073.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The author declares no conflict of interest.
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