CN116039957B - Spacecraft online game planning method, device and medium considering barrier constraint - Google Patents
Spacecraft online game planning method, device and medium considering barrier constraint Download PDFInfo
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Abstract
The embodiment of the invention discloses a spacecraft online game planning method considering barrier constraint, belonging to the technical field of spacecraft orbit control; the method comprises the following steps: constructing a nonlinear dynamics model of a participating game spacecraft; in the current round, initial state vectors of the spacecraft, the opponent spacecraft and the obstacle spacecraft are obtained through measurement, and a decision spacecraft state information sequence with the window length set in an uncontrolled state is obtained through a dynamics model; predicting opponent spacecraft state information sequence estimation by an opponent spacecraft objective function based on relative distance and angle according to the decision spacecraft state information sequence in the current iteration; according to the estimation of the state information sequence of the opponent spacecraft, solving a control sequence of the decision spacecraft through an objective function of the decision spacecraft and updating the state information sequence of the decision spacecraft; if the set iteration ending condition is not met, entering the next iteration; otherwise, ending the iteration, and outputting the optimal control quantity according to the control sequence of the decision-making spacecraft.
Description
Technical Field
The embodiment of the invention relates to the technical field of spacecraft orbit control, in particular to a spacecraft online game planning method, device and medium considering barrier constraint.
Background
Continuous forms of differential gaming give a conservative, secure strategy under complete information, but this is an open-loop strategy, which has to be recalculated as the opponent changes, and is difficult to apply in practice. The spacecraft sequence game under the pulse maneuver is difficult to apply on-orbit due to the calculation time problem, is relatively suitable for the game problem analysis under the offline scene, and is difficult to meet the requirement of the on-orbit game planning of the spacecraft.
The general orbital gaming problem requires consideration of more factors such as avoiding collisions with other spacecraft, and potentially interactions with other third party aerospace, and the like, and lacks an efficient way to deal with such problems.
Disclosure of Invention
In view of this, the embodiment of the invention is expected to provide a spacecraft online game planning method, device and medium considering barrier constraint; the online game planning of third-party spacecraft avoidance can be realized by considering the existence of obstacle spacecraft scenes and designing a safe and effective game strategy, a nonlinear model predictive control method is adopted, the game problem in a certain range is only calculated by utilizing the idea of local approximation and rolling optimization, and the calculation pressure is reduced.
The technical scheme of the embodiment of the invention is realized as follows:
in a first aspect, an embodiment of the present invention provides a spacecraft online game planning method considering barrier constraints, including:
constructing a nonlinear dynamics model of a participating game spacecraft;
in the current round, the decision spacecraft obtains initial state vectors of the decision spacecraft, the opponent spacecraft and the obstacle spacecraft through measurement, and obtains a state information sequence of the decision spacecraft with a set window length in a non-control state through the dynamics model based on the initial state vectors;
predicting state information sequence estimation of the set window length of the opponent spacecraft by an opponent spacecraft objective function based on relative angles and distances according to the state information sequence of the decision spacecraft and the dynamics model in the current iteration;
according to the estimation of the state information sequence of the opponent spacecraft, solving a decision spacecraft control sequence through the game objective function of the decision spacecraft and updating the state information sequence of the decision spacecraft;
if the set iteration ending condition is not met, entering the next iteration; otherwise, ending iteration, and outputting the optimal control quantity of the decision spacecraft according to the control sequence of the decision spacecraft, so that the decision spacecraft enters a next round game after controlling the operation of the decision spacecraft according to the optimal control quantity.
In a second aspect, an embodiment of the present invention provides a spacecraft online game planning device considering barrier constraint, including a modeling portion, a measuring portion, a predicting portion, a solving portion and a decision portion; wherein,
the modeling part is configured to construct a nonlinear dynamics model of the participating game spacecraft;
the measurement part is configured to obtain initial state vectors of the decision spacecraft, the opponent spacecraft and the obstacle spacecraft by measurement in the current round, and obtain a state information sequence of the decision spacecraft with a set window length in a non-control state by the dynamics model based on the initial state vectors;
the prediction part is configured to predict state information sequence estimation of the set window length of the opponent spacecraft according to the state information sequence of the decision spacecraft and the dynamics model through an opponent spacecraft objective function based on relative angles and distances in the current iteration;
the solving part is configured to solve a decision spacecraft control sequence through the decision spacecraft game objective function according to the opponent spacecraft state information sequence estimation and update the decision spacecraft state information sequence;
The decision part is configured to enter the next iteration if the set iteration ending condition is not met; otherwise, ending iteration, and outputting the optimal control quantity of the decision spacecraft according to the control sequence of the decision spacecraft, so that the decision spacecraft enters a next round game after controlling the operation of the decision spacecraft according to the optimal control quantity.
In a third aspect, embodiments of the present invention provide a computing device, the computing device comprising: a communication interface, a memory and a processor; the components are coupled together by a bus system; wherein,
the communication interface is used for receiving and transmitting signals in the process of receiving and transmitting information with other external network elements;
the memory is used for storing a computer program capable of running on the processor;
the processor is configured to execute the steps of the method for planning online game of a spacecraft in consideration of barrier constraints in the first aspect when the computer program is run, which is not described herein.
In a fourth aspect, an embodiment of the present invention provides a computer storage medium, where a spacecraft online game planning program considering barrier constraints is stored, where the steps of the spacecraft online game planning method considering barrier constraints in the first aspect are implemented when the spacecraft online game planning program considering barrier constraints is executed by at least one processor.
The embodiment of the invention provides a spacecraft online game planning method, device and medium considering barrier constraint; the decision spacecraft obtains initial state vectors of the decision spacecraft, the opponent spacecraft and the obstacle spacecraft through measurement, obtains a decision spacecraft state information sequence with a set window length in a non-control state through a dynamics model based on the initial state vectors, adopts a nonlinear model prediction control method, only needs to solve the same minimization or maximization problem for the two game sides of the current state information of the opponent spacecraft, and can better consider the constraint of an executing mechanism; the method comprises the steps of circularly and iteratively predicting the state information sequence of the opponent spacecraft, then solving and updating the control sequence of the opponent spacecraft, and only calculating the game problem in a certain range by utilizing the thought of local approximation and rolling optimization, wherein the game problem is different from the survival type differential game problem by taking the game time as a target, and the game optimization target of the on-orbit real-time game is a local target function in a prediction window because of knowing when future games are finished, so that the calculation pressure is reduced.
Drawings
Fig. 1 is a schematic view of a solar light interference constrained spacecraft escape scene provided by an embodiment of the invention;
Fig. 2 is a schematic flow chart of a spacecraft online game planning method considering barrier constraint provided by the embodiment of the invention;
FIG. 3 is a schematic diagram of an iterative best response algorithm provided by an embodiment of the present invention;
FIG. 4 is a simulation diagram of a game planning track of an unobstructed scene provided by an embodiment of the invention;
FIG. 5 is a simulation diagram of the relative position and relative angle change in the process of the barrier-free scene game provided by the embodiment of the invention;
FIG. 6 is a simulation diagram of relative position components of a barrier-free scene game process provided by an embodiment of the invention;
FIG. 7 is a simulation diagram of speed components of a barrier-free scene game process provided by an embodiment of the invention;
FIG. 8 is a simulation diagram of control input components of a barrier-free scene game process provided by an embodiment of the invention;
FIG. 9 is a simulation diagram of control inputs of a barrier-free scene game process provided by an embodiment of the invention;
FIG. 10 is a simulation diagram of a change in value function of a game process of a barrier-free scene according to an embodiment of the present invention;
FIG. 11 is a simulation diagram of a game planning track of the obstacle constraint scene 1 provided by the embodiment of the invention;
FIG. 12 is a simulation diagram of the relative position and relative angle changes in the process of the game in the obstacle constraint scene 1 according to the embodiment of the present invention;
FIG. 13 is a simulation diagram of a game planning trajectory for the obstacle constraint scenario 2 provided by an embodiment of the present invention;
FIG. 14 is a simulation diagram of the relative position and relative angle change in the process of the obstacle constraint scene 2 game provided by the embodiment of the invention;
FIG. 15 is a schematic diagram of a spacecraft online game planning device taking into account barrier constraints according to an embodiment of the invention;
fig. 16 is a schematic hardware structure of a computing device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
Two homogeneous spacecraft game scenes under the constraint of sunlight interference exist, and tracking spacecraft and escape spacecraft participating in game attempt to maximize own interests or minimize own interests under the scene that other obstacles or third-party spacecraft may exist. The visibility under specific sunlight interference is shown in fig. 1, the targets in the game of the two parties of the spacecraft participating in the game are the best approach observation for tracking the spacecraft, and the best observation is destroyed for escaping the spacecraft. The main objective of tracking the spacecraft is to achieve optimal observation angles and relative distances in the near observation. The main objective of the escape spacecraft is to achieve a tamper observation condition. Because the relative included angles are relative, the observation included angles of the opponent spacecraft are naturally positioned at the forward light observation position when destroyed.
Referring to fig. 2, the method for planning an online game of a spacecraft considering barrier constraint provided by the embodiment of the invention can be applied to a decision spacecraft, and it can be understood that the decision spacecraft can be a tracking spacecraft or an escape spacecraft, and the method includes:
s201: constructing a nonlinear dynamics model of a participating game spacecraft;
s202: in the current round, the decision spacecraft obtains initial state vectors of the decision spacecraft, the opponent spacecraft and the obstacle spacecraft through measurement, and obtains a state information sequence of the decision spacecraft with a set window length in a non-control state through the dynamics model based on the initial state vectors;
s203: predicting state information sequence estimation of the set window length of the opponent spacecraft by an opponent spacecraft objective function based on relative angles and distances according to the state information sequence of the decision spacecraft and the dynamics model in the current iteration;
s204: according to the estimation of the state information sequence of the opponent spacecraft, solving a decision spacecraft control sequence through the game objective function of the decision spacecraft and updating the state information sequence of the decision spacecraft;
s205: if the set iteration ending condition is not met, entering the next iteration; otherwise, ending iteration, and outputting the optimal control quantity of the decision spacecraft according to the control sequence of the decision spacecraft, so that the decision spacecraft enters a next round game after controlling the operation of the decision spacecraft according to the optimal control quantity.
For the solution shown in fig. 2, in some possible implementations, the building a nonlinear dynamics model of a participating game spacecraft includes:
the nonlinear dynamics model of the participating game spacecraft is constructed as follows:
wherein x is i ＝[x i ,y i ,z i ,v xi ,v yi ,v zi ] T I e { p, e, obs } represents all spacecraft in the gaming scenario, including tracking spacecraft p, escape spacecraft e, and other obstacles or third party spacecraft obs that may be present; t (T) s Representing a time interval; k represents a discrete time;
the dynamics model obeys nonlinear relative motion dynamics as shown in the following formula:
wherein x, y, z represent relative positions in the LVLH coordinate system, v x ,v y ,v z For the relative velocity in the LVLH coordinate system, n represents the orbital angular velocity, m represents the spacecraft mass, T x ,T y ,T z Represents the magnitude of the thrust component, μ represents the gravitational constant, R Earth Represents the earth radius, J 2 Representing global non-spherical perturbation, R c The reference orbit radius is denoted, alpha denotes the orbit inclination angle, and beta denotes the latitude argument.
For the technical solution shown in fig. 2, in some possible implementations, in the current iteration, according to the decision spacecraft state information sequence and the dynamics model, predicting, by an opponent spacecraft objective function based on a relative angle and a distance, state information sequence estimation of a set window length of the opponent spacecraft includes:
If the decision spacecraft is a tracking spacecraft, estimating the state information sequence of the escape spacecraft by solving the maximum value of a game objective function of the escape spacecraft under the constraint condition to predict the set window length according to the state information sequence of the decision spacecraft, namely the state information sequence of the tracking spacecraftThe following formula is shown:
wherein x is obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Represents the safe distance between the spacecraft, θ represents the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N represents the predicted window length,representing position constraints of the escape spacecraft, +.>Represents the control constraint of the escape spacecraft, M represents the maximum number of iterations, d represents the distance function, Q, Q N Representing the normalized weights.
It should be noted that, the game target of the escape spacecraft is to destroy the observation condition of the tracking spacecraft, i.e. ending in game relative time of day distance ||x pe (t f ) II is greater than the safe distance r emin And the terminal line of sight angle θ (t) f ) The smaller the better, d (x e ,x obs,i )≥(R obs +R rob ) Characterizing the distance constraint of an escape spacecraft from an obstacle spacecraft, x e (k+1)＝f e (x e (k),u e (k) Characterizing the dynamic constraints of the model,the position constraints of the escape spacecraft are characterized, Control constraints of the escape spacecraft are characterized.
If the decision spacecraft is an escape spacecraft, escaping the spacecraft state information sequence according to the decision spacecraft state information sequence, and predicting the tracking spacecraft state information sequence estimation with the set window length by solving the minimum value of the tracking spacecraft objective function under the constraint conditionThe following formula is shown:
wherein x is obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Represents the safe distance between the spacecraft, θ represents the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N represents the predicted window length,representing the position constraint of tracking spacecraft, +.>Representing control constraints for tracking spacecraft, M tablesShows the maximum number of iterations, d represents the distance function, Q, Q N Representing the normalized weights.
It should be noted that, tracking the game target of the spacecraft is to attempt to achieve a predetermined observation condition, i.e., the relative distance of game end time ||x pe (t f ) II is smaller than the imaging distance r pmax And the terminal line of sight angle θ (t) f ) The larger and better, d (x p ,x obs,i )≥(R obs +R rob ) Characterizing a distance constraint between a tracking spacecraft and an obstacle spacecraft, x p (k+1)＝f p (x p (k),u p (k) Characterizing the dynamic constraints of the model, The position constraints of the tracking spacecraft are characterized,control constraints for tracking a spacecraft are characterized.
It should be further noted that, in the first iteration process, the decision spacecraft predicts that the state information sequence of the opponent spacecraft needs initial state information x obtained based on measurement e (0)、x p (0)、x obs (0) The state information of the window length (namely N stages) of the decision spacecraft is set, and the decision spacecraft is considered to be in an uncontrolled state in the first iteration, so that the state information of the N stages of the decision spacecraft is obtained according to a dynamics model in the uncontrolled state; because the obstacle spacecraft or the third-party spacecraft does not carry out game control, the corresponding control input is considered to be 0; in the subsequent iteration, when predicting the opponent spacecraft control sequence estimation, updating and obtaining state information of N stages of the decision spacecraft according to the state information of the decision spacecraft obtained by solving in the previous iteration; it can also be seen that by adopting the nonlinear model predictive control method, only the current state information of the opponent spacecraft is obtained through measurement, and the same minimization or maximization problem is solved circularly and iteratively for both game parties, so that the optimal solution of the control law of the decision spacecraft is obtained, and the constraint of an executing mechanism can be better considered; this is In addition, the design of the objective function does not take control input as an optimization target, so that the problem that the optimal strategy cannot be realized due to considering fuel consumption as much as possible is avoided when two game parties perform vigorous chase games.
For the technical solution shown in fig. 2, in some possible implementations, the solving, according to the estimation of the state information sequence of the opponent spacecraft, the control sequence of the decision spacecraft and updating the corresponding state information sequence of the decision spacecraft by the game objective function of the decision spacecraft includes:
if the decision spacecraft is a tracking spacecraft, acquiring a tracking spacecraft control sequence by solving a tracking spacecraft objective function minimum value according to the state information sequence estimation of the opponent spacecraft (namely the escape spacecraft) obtained by prediction, and updating the corresponding tracking spacecraft state information sequence, wherein the following formula is shown as follows:
wherein,estimating, x, the state information sequence of the escape spacecraft predicted in the current iteration obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Represents the safe distance between the spacecraft, θ represents the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N represents the predicted window length, Representing position constraints of the escape spacecraft, +.>Representation ofEscape spacecraft control constraint, M represents maximum iteration number, d represents distance, Q, Q N Representing the normalized weights.
If the decision spacecraft is an escape spacecraft, solving the maximum value of an objective function of the escape spacecraft according to the predicted state information sequence estimation of the opponent spacecraft (namely the tracking spacecraft) to obtain an escape spacecraft control sequence and updating the corresponding escape spacecraft state information sequence, wherein the maximum value is represented by the following formula:
wherein,estimating, x, a sequence of state information of the tracking spacecraft predicted in the current iteration obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Represents the safe distance between the spacecraft, θ represents the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N represents the predicted window length,representing position constraints of the escape spacecraft, +.>Represents the control constraint of the escape spacecraft, M represents the maximum number of iterations, d represents the distance, Q, Q N Representing the normalized weights.
For the solution shown in fig. 2, in some possible implementations, if the set iteration end condition is not satisfied, the next iteration is entered; otherwise, ending the iteration, outputting the optimal control quantity of the decision spacecraft according to the control sequence of the decision spacecraft, and comprising the following steps:
Manually setting the maximum iteration times according to the allowed decision time;
ending the iteration if the current iteration reaches the maximum iteration times, wherein the first action of the control sequence of the decision spacecraft obtained by the last iteration calculation is the optimal control quantity of the decision spacecraft;
if the current iteration does not reach the maximum iteration number, if the objective function values of the decision spacecraft and the opponent spacecraft of the last iteration meet |J p -J e The first control quantity of the control sequence of the decision spacecraft obtained by the last iterative calculation is the optimal control quantity of the decision spacecraft; otherwise, the next iteration is entered.
In the chase-back scene, both the chase-back spacecraft perform zero and game, namely:
tracking spacecraft and escape spacecraft are described using the same objective function, namely:
J(U p ,U e )＝J p (U p ,U e )＝-J e (U p ,U e )＝t f
the respective targets of the escape spacecraft and the tracking spacecraft may be described as:
in the zero and game case, when Nash equilibrium is reached, the value function satisfiesIn practical cases a completely equal value function is difficult to obtain when +.>When an approximate Nash equilibrium is considered to be reached. Usually solving Nash equilibrium is a very difficult problem, especially in the case of constraint, the embodiment of the invention uses the iterative optimal response method to solve the local approximate Nash equilibrium, FIG. 3 shows a schematic diagram of the iterative optimal response algorithm provided by the embodiment of the invention, after both sides of the escape spacecraft acquire the state information of themselves and the opposite side through measurement, the tracking spacecraft P needs to solve the strategy of the opponent spacecraft E before solving the problem P', and the strategy of the opponent spacecraft E solves the problem through the strategy of the opponent spacecraft E >Obtaining, solving the opponent spacecraft problem->When the opponent spacecraft is in the uncontrolled state according to the tracking spacecraft P. After the tracking spacecraft P responds to the strategy of the opponent spacecraft E, the updated strategy of the escape spacecraft is continuously solved, and then the own updated strategy is further solved. Repeating the above processes until both sides can not continuously update their own strategies, thereby achieving Nash equilibrium, and then outputting the optimal strategy for tracking the spacecraft, namely +.>Likewise, the minimization problem is first solved +.>Obtaining an optimal strategy of a counter party, then taking the obtained output as an input to solve a maximized problem E' for strategy updating, and continuously carrying out strategy iteration until the optimal strategy is reached; it can be understood that, after iteratively predicting the state information sequence of the opponent spacecraft, solving and updating the control sequence of the opponent spacecraft, only calculating the game problem within a certain range by utilizing the concept of local approximation and rolling optimization, unlike the living differential game problem which aims at the game time, the game of in-orbit real-time game is performed because the time when the future game is finished is unknownThe optimization target is a local objective function in a prediction window, so that the calculation pressure is reduced.
Based on the technical scheme, the embodiment of the invention carries out simulation experiments aiming at the game scene of the rear-flight spacecraft without barrier constraint and with barrier constraint, and the simulation parameters are set as follows:
consider a circular reference orbit, the orbit parameters are as follows:
orbit semimajor axis a=12756 km, orbit eccentricity e=0, orbit inclination angle α=0°, latitude argument β=0°, ascending intersection point right angle Ω=0°;
tracking spacecraft and escape spacecraft have the same mass m p ＝m e =2000 kg, maximum thrust T p ＝300N，T e =100n, the chase-back spacecraft initial state information parameters are shown in table 1 below:
TABLE 1
The objective function is the direct implementation of game targets of the game spacecraft, and in order to balance the magnitude difference between the relative included angle and the relative distance, the objective function is unified to the same size, and weight parameters in the objective function are selected as follows:
Q(x)＝10I，Q(x) N ＝5000I，Q(θ)＝10，Q(θ) N ＝10；
wherein different weights represent the attention degree of the game spacecraft to the relative distance and the relative angle, and the prediction time T of model prediction s ＝100s,N＝10,C N =10; calculating the iteration number M=4 of each round in the approximate Nash equalization process by considering the calculation time; since there is no time when the game ends, the simulation time takes approximately one orbit period 14000s in order to analyze the performance of the chase spacecraft in the whole game process.
Based on the simulation parameters, the simulation is performed according to the technical scheme shown in the foregoing fig. 2, and the simulation results are as follows: FIG. 4 shows a simulation diagram of a game planning trajectory for an unobstructed scene using the technical scheme of the embodiment of the invention; FIG. 5 shows an embodiment of the present inventionA simulation diagram of the relative position and the relative angle change of the barrier-free scene game process; FIG. 6 shows a simulation diagram of relative position components of a barrier-free scene gaming process provided by an embodiment of the invention; FIG. 7 shows a simulation diagram of a speed component of a barrier-free scene game process provided by an embodiment of the invention; FIG. 8 illustrates a simulation diagram of a barrier-free scene gaming process control input component provided by an embodiment of the invention; FIG. 9 shows a simulation diagram of a barrier-free scene game process control input provided by an embodiment of the invention; FIG. 10 shows a simulation diagram of the change of the value function of the barrier-free scene game process provided by the embodiment of the invention. As can be seen from fig. 4, both the tracking and escaping parties play around the half-plane of the sun's line of sight, both try to occupy the forward-looking position, but can be in the dominant position because of the dominance of the tracking spacecraft's maneuverability; as can be seen from fig. 5, the relative distance of the tracking spacecraft is gradually increased at the beginning of the game, but then rapidly decreased, the relative distance of the tracking spacecraft is minimum at 66.76km at about 6000s, and is in a smooth observation condition, then the relative distance between the game spacecraft fluctuates within a certain range, and the relative included angle also fluctuates near the half plane, which indicates that the tracking spacecraft is always pressed by the tracking spacecraft; as can be seen from fig. 6 and 7, the tracking spacecraft tries to replicate the trajectory of the escape spacecraft and remains in the forward light direction, and as the game proceeds, the amplitude of the fluctuation gradually decreases, indicating that the tracking spacecraft is dominant, consistent with the conclusion that the game trajectory in fig. 4 is more and more similar; as can be seen from fig. 9, the two sides of the chase-and-flee game always select the maximum acceleration for maneuver in a plurality of times; as can be seen from FIG. 10, when the iterative optimal response is used to solve the Nash equilibrium strategy, when the two-party value functions converge to a common value, the two parties reach the optimal strategy at the same time, i.e However, given a certain number of iterations, consider the calculation time, achieve +.>When two parties are considered to achieve approximate Nash equilibrium.
The obstacle constraint scene 1 considers game behavior when a third-party obstacle spacecraft exists, and sets obstacle spacecraft constraint on an optimal path, namely the game spacecraft needs to avoid approaching the obstacle spacecraft, and sets an obstacle region R for avoiding the spacecraft obs =20 km, the obstacle spacecraft position parameters were set as shown in table 2 below:
TABLE 2
FIG. 11 shows a simulation diagram of a game planning trajectory for the obstacle constraint scenario 1 provided by an embodiment of the present invention; FIG. 12 is a simulation diagram of the relative position and relative angle change of the barrier constraint scene 1 game process provided by the embodiment of the invention; as can be seen from fig. 11, tracking the spacecraft during the game chooses to avoid the first obstacle first, while escaping the spacecraft can only choose to shuttle in the obstacle due to the limitation of the obstacle; comparing the simulation of the relative distance and relative angle changes in the game process of the spacecraft with or without the obstacle with fig. 12 and 5, it can be found that when the obstacle exists, the nearest relative distance 40.687km is caused at about 7500 seconds, the relative angle is larger, and from the simulation result, the influence of the existence of the obstacle on the escaping spacecraft is larger, so that the influence is caused to fall behind in the initial stage of the game.
The obstacle constraint scene 2 considers that an obstacle spacecraft is arranged on a path of a tracking spacecraft, and the position parameters of the obstacle spacecraft are set as shown in the following table 3:
TABLE 3 Table 3
FIG. 13 shows a simulation diagram of a barrier constraint scene 2 game planning trajectory provided by an embodiment of the present invention; FIG. 14 is a simulation diagram of relative position and relative angle changes in a barrier constraint scene 2 game process provided by an embodiment of the invention; as can be seen from fig. 13 and 14, the relative distance increases gradually in the initial game stage, since the presence of the obstacle causes the tracking spacecraft to reach a minimum relative distance 58.075km at 7400 seconds, after 4000 seconds, at which time the tracking spacecraft has traversed the obstacle region, the relative distance decreases rapidly, the relative angle increases rapidly, and reaches a peak around 5000 seconds, which is the rapid lifting stage of the tracking spacecraft, after which the escape spacecraft continuously decreases the relative angle, but the relative distance remains in a relatively stable stage. Compared with simulation tests of the tracking spacecraft and the escape spacecraft affected by the obstacle, the tracking spacecraft is difficult to realize smaller relative distance after passing through the obstacle area due to the existence of the obstacle, and once entering a relatively stable dynamic interval, two game parties are difficult to further optimize and are in a dynamic balance stage of the balance.
Based on the same inventive concept as the foregoing technical solution, referring to fig. 15, there is shown an online game planning device 150 for a spacecraft, which is provided by an embodiment of the present invention and takes into consideration obstacle constraints, where the device 150 includes: a modeling section 1501, a measuring section 1502, a predicting section 1503, a solving section 1504, and a deciding section 1505; wherein,
the modeling portion 1501 is configured to construct a nonlinear dynamics model of a participating gaming spacecraft;
the measurement part 1502 is configured to obtain initial state vectors of the decision spacecraft, the opponent spacecraft and the obstacle spacecraft by measurement in the current round, and obtain a state information sequence of the decision spacecraft with a set window length in a non-control state by the dynamics model based on the initial state vectors;
the predicting part 1503 is configured to predict, at a current iteration, a state information sequence estimation of a set window length of the opponent spacecraft by an opponent spacecraft objective function based on a relative angle and a distance according to the decision spacecraft state information sequence and the dynamics model;
the solving part 1504 is configured to solve a decision spacecraft control sequence through the decision spacecraft game objective function according to the opponent spacecraft state information sequence estimation and update the decision spacecraft state information sequence;
The decision part 1505 is configured to enter the next iteration if the set iteration end condition is not satisfied; otherwise, ending iteration, and outputting the optimal control quantity of the decision spacecraft according to the control sequence of the decision spacecraft, so that the decision spacecraft enters a next round game after controlling the operation of the decision spacecraft according to the optimal control quantity.
For the specific implementation of the functions configured by the "parts" in the above-mentioned device, reference may be made to the implementation manner and examples of the corresponding steps in the online game planning method for the spacecraft taking into consideration the barrier constraint shown in fig. 2, which are not described herein again.
It will be appreciated that in this embodiment, a "part" may be a part of a circuit, a part of a processor, a part of a program or software, etc., and of course may be a unit, or a module may be non-modular.
In addition, each component in the present embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional modules.
The integrated units, if implemented in the form of software functional modules, may be stored in a computer-readable storage medium, if not sold or used as separate products, and based on such understanding, the technical solution of the present embodiment may be embodied essentially or partly in the form of a software product, which is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or processor to perform all or part of the steps of the method described in the present embodiment. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Therefore, the embodiment provides a computer storage medium, wherein the computer storage medium stores a spacecraft online game planning program considering barrier constraints, and the spacecraft online game planning program considering barrier constraints realizes the steps of the spacecraft online game planning method considering barrier constraints in the technical scheme when the spacecraft online game planning program considering barrier constraints is executed by at least one processor.
In accordance with the above-described obstacle-constrained spacecraft online gaming planning apparatus 150 and computer storage media, and referring to fig. 16, a specific hardware architecture of a computing device 160 capable of implementing the above-described obstacle-constrained spacecraft online gaming planning apparatus 150 is provided, where the computing device 160 may be a wireless device, a mobile or cellular phone (including a so-called smart phone), a Personal Digital Assistant (PDA), a video game console (including a video display, a mobile video game device, a mobile video conferencing unit), a laptop computer, a desktop computer, a television set-top box, a tablet computing device, an electronic book reader, a fixed or mobile media player, and so forth. The computing device 160 includes: a communication interface 1601, a memory 1602 and a processor 1603; the various components are coupled together by a bus system 1604. It is appreciated that the bus system 1604 is used to enable connected communications between these components. The bus system 1604 includes a power bus, a control bus, and a status signal bus in addition to the data bus. But for clarity of illustration, the various buses are labeled as bus system 1604 in fig. 16. Wherein,
The communication interface 1601 is configured to receive and send signals during the process of receiving and sending information with other external network elements;
the memory 1602 for storing a computer program capable of running on the processor 1603;
the processor 1603 is configured to execute the steps of the spacecraft online game planning method that consider the obstacle constraint in the foregoing technical solution when running the computer program, and will not be described herein.
It is to be appreciated that memory 1602 in embodiments of the present invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable EPROM (EEPROM), or a flash Memory. The volatile memory may be random access memory (Random Access Memory, RAM) which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (Double Data Rate SDRAM), enhanced SDRAM (ESDRAM), synchronous DRAM (SLDRAM), and Direct RAM (DRRAM). The memory 1602 of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
While processor 1603 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in processor 1603. The processor 1603 described above may be a general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 1602, and the processor 1603 reads information in the memory 1602 and, in combination with its hardware, performs the steps of the method described above.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For a hardware implementation, the processing units may be implemented within one or more application specific integrated circuits (Application Specific Integrated Circuits, ASIC), digital signal processors (Digital Signal Processing, DSP), digital signal processing devices (DSP devices, DSPD), programmable logic devices (Programmable Logic Device, PLD), field programmable gate arrays (Field-Programmable Gate Array, FPGA), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units configured to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
Specifically, the processor 1603 is further configured to execute the steps of the method for online game planning of a spacecraft in consideration of the obstacle constraint in the foregoing technical solution when running the computer program, which is not described herein.
It should be understood that the above exemplary technical solutions of the spacecraft online game planning device 150 and the computing device 160 that consider the obstacle constraint are the same as the technical solutions of the spacecraft online game planning method that consider the obstacle constraint, and therefore, for details that are not described in detail in the technical solutions of the spacecraft online game planning device 150 and the computing device 160 that consider the obstacle constraint, reference may be made to the description of the technical solutions of the spacecraft online game planning method that consider the obstacle constraint. The embodiments of the present invention will not be described in detail.
It should be noted that: the technical schemes described in the embodiments of the present invention may be arbitrarily combined without any collision.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (3)
1. The spacecraft online game planning method considering barrier constraint is characterized by comprising the following steps of:
Constructing a nonlinear dynamics model of a participating game spacecraft;
in the current round, the decision spacecraft obtains initial state vectors of the decision spacecraft, the opponent spacecraft and the obstacle spacecraft through measurement, and obtains a state information sequence of the decision spacecraft with a set window length in a non-control state through the dynamics model based on the initial state vectors;
predicting state information sequence estimation of the set window length of the opponent spacecraft by an opponent spacecraft objective function based on relative angles and distances according to the state information sequence of the decision spacecraft and the dynamics model in the current iteration;
according to the estimation of the state information sequence of the opponent spacecraft, solving a decision spacecraft control sequence through the game objective function of the decision spacecraft and updating the state information sequence of the decision spacecraft;
if the set iteration ending condition is not met, entering the next iteration; otherwise, ending iteration, and outputting an optimal control quantity of the decision spacecraft according to the control sequence of the decision spacecraft, so that the decision spacecraft enters a next round game after controlling the operation of the decision spacecraft according to the optimal control quantity;
the method for constructing the nonlinear dynamics model of the participating game spacecraft comprises the following steps:
The nonlinear dynamics model of the participating game spacecraft is constructed as follows:
wherein x is i ＝[x i ,y i ,z i ,v xi ,v yi ,v zi ] T I e { p, e, obs } represents all spacecraft in the gaming scenario, including tracking spacecraft p, escape spacecraft e, and other obstacles or third party spacecraft obs that may be present; t (T) s Representing a time interval; k represents a discrete time;
the dynamics model obeys nonlinear relative motion dynamics as shown in the following formula:
wherein x, y, z represent relative positions in the LVLH coordinate system, v x ,v y ,v z For the relative velocity in the LVLH coordinate system, n represents the orbital angular velocity, m represents the spacecraft mass, T x ,T y ,T z Represents the magnitude of the thrust component, μ represents the gravitational constant, R Earth Represents the earth radius, J 2 Representing global non-spherical perturbation, R c Representing a reference orbit radius, alpha representing an orbit inclination angle, and beta representing a latitude argument angle;
predicting state information sequence estimation of the set window length of the opponent spacecraft according to the state information sequence of the decision spacecraft and the dynamics model through an opponent spacecraft objective function based on relative angles and distances in the current iteration, wherein the state information sequence estimation comprises the following steps:
if the decision spacecraft is a tracking spacecraft, predicting the escape of the set window length by solving the maximum value of the game objective function of the escape spacecraft under the constraint condition according to the decision spacecraft state information sequence, namely the tracking spacecraft state information sequence Running spacecraft state information sequence estimationThe following formula is shown:
wherein x is obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Represents the safe distance between the spacecraft, θ represents the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N represents the predicted window length,representing position constraints of the escape spacecraft, +.>Represents the control constraint of the escape spacecraft, M represents the maximum number of iterations, d represents the distance function, Q, Q N Representing the normalized weights;
if the decision spacecraft is an escape spacecraft, escaping the spacecraft state information sequence according to the decision spacecraft state information sequence, and predicting the tracking spacecraft state information sequence estimation with the set window length by solving the minimum value of the tracking spacecraft objective function under the constraint conditionThe following formula is shown:
wherein x is obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Represents the safe distance between the spacecraft, θ represents the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N represents the predicted window length,representing the position constraint of tracking spacecraft, +. >Represents a control constraint for tracking a spacecraft, M represents a maximum number of iterations, d represents a distance function, Q, Q N Representing the normalized weights;
the step of solving the control sequence of the decision spacecraft and updating the corresponding state information sequence of the decision spacecraft through the game objective function of the decision spacecraft according to the state information sequence estimation of the opponent spacecraft comprises the following steps:
if the decision spacecraft is a tracking spacecraft, acquiring a tracking spacecraft control sequence and updating a corresponding tracking spacecraft state information sequence by solving a tracking spacecraft objective function minimum value according to the predicted opponent spacecraft state information sequence estimation, wherein the following formula is shown:
wherein,estimating, x, the state information sequence of the escape spacecraft predicted in the current iteration obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Representing the safe distance between the spacecraft, θ representing the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N representing the predicted window length, < >>Representing position constraints of the escape spacecraft, +.>Represents the control constraint of the escape spacecraft, M represents the maximum number of iterations, D represents the distance, Q, Q N Representing the normalized weights;
if the decision spacecraft is an escape spacecraft, solving the maximum value of an objective function of the escape spacecraft according to the predicted state information sequence estimation of the opponent spacecraft to obtain an escape spacecraft control sequence and updating the corresponding escape spacecraft state information sequence, wherein the method is as follows:
wherein,estimating, x, a sequence of state information of the tracking spacecraft predicted in the current iteration obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Represents the safe distance between spacecrafts, and θ represents the chaseAn included angle between a connecting line of the tracking spacecraft and the escape spacecraft and a connecting line of the escape spacecraft and the sun, wherein N represents a predicted window length, < ->Representing position constraints of the escape spacecraft, +.>Represents the control constraint of the escape spacecraft, M represents the maximum number of iterations, d represents the distance, Q, Q N Representing the normalized weights;
if the set iteration ending condition is not met, entering the next iteration; otherwise, ending the iteration, outputting the optimal control quantity of the decision spacecraft according to the control sequence of the decision spacecraft, and comprising the following steps:
manually setting the maximum iteration times according to the allowed decision time;
ending the iteration if the current iteration reaches the maximum iteration times, wherein the first action of the control sequence of the decision spacecraft obtained by the last iteration calculation is the optimal control quantity of the decision spacecraft;
If the current iteration does not reach the maximum iteration number, if the objective function values of the decision spacecraft and the opponent spacecraft of the last iteration meet |J p -J e The first control quantity of the control sequence of the decision spacecraft obtained by the last iterative calculation is the optimal control quantity of the decision spacecraft; otherwise, the next iteration is entered.
2. The spacecraft online game planning device considering barrier constraint comprises a modeling part, a measuring part, a predicting part, a solving part and a deciding part; wherein,
the modeling part is configured to construct a nonlinear dynamics model of the participating game spacecraft;
the measurement part is configured to obtain initial state vectors of the decision spacecraft, the opponent spacecraft and the obstacle spacecraft by measurement in the current round, and obtain a state information sequence of the decision spacecraft with a set window length in a non-control state by the dynamics model based on the initial state vectors;
the prediction part is configured to predict state information sequence estimation of the set window length of the opponent spacecraft according to the state information sequence of the decision spacecraft and the dynamics model through an opponent spacecraft objective function based on relative angles and distances in the current iteration;
The solving part is configured to solve a decision spacecraft control sequence through the decision spacecraft game objective function according to the opponent spacecraft state information sequence estimation and update the decision spacecraft state information sequence;
the decision part is configured to enter the next iteration if the set iteration ending condition is not met; otherwise, ending iteration, and outputting an optimal control quantity of the decision spacecraft according to the control sequence of the decision spacecraft, so that the decision spacecraft enters a next round game after controlling the operation of the decision spacecraft according to the optimal control quantity;
the method for constructing the nonlinear dynamics model of the participating game spacecraft comprises the following steps:
the nonlinear dynamics model of the participating game spacecraft is constructed as follows:
wherein x is i ＝[x i ,y i ,z i ,v xi ,v yi ,v zi ] T I e { p, e, obs } represents all spacecraft in the gaming scenario, including tracking spacecraft p, escape spacecraft e, and other obstacles or third party spacecraft obs that may be present; t (T) s Representing a time interval; k represents a discrete time;
the dynamics model obeys nonlinear relative motion dynamics as shown in the following formula:
wherein x, y, z represent relative positions in the LVLH coordinate system, v x ,v y ,v z For the relative velocity in the LVLH coordinate system, n represents the orbital angular velocity, m represents the spacecraft mass, T x ,T y ,T z Represents the magnitude of the thrust component, μ represents the gravitational constant, R Earth Represents the earth radius, J 2 Representing global non-spherical perturbation, R c Representing a reference orbit radius, alpha representing an orbit inclination angle, and beta representing a latitude argument angle;
predicting state information sequence estimation of the set window length of the opponent spacecraft according to the state information sequence of the decision spacecraft and the dynamics model through an opponent spacecraft objective function based on relative angles and distances in the current iteration, wherein the state information sequence estimation comprises the following steps:
if the decision spacecraft is a tracking spacecraft, estimating the state information sequence of the escape spacecraft by solving the maximum value of a game objective function of the escape spacecraft under the constraint condition to predict the set window length according to the state information sequence of the decision spacecraft, namely the state information sequence of the tracking spacecraftThe following formula is shown:
wherein x is obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Representing the safe distance between the spacecraft, θ representing the connection of the tracking spacecraft and the escape spacecraft with the connection of the escape spacecraft and the sunThe angle between the lines, N, represents the prediction window length, Representing position constraints of the escape spacecraft, +.>Represents the control constraint of the escape spacecraft, M represents the maximum number of iterations, d represents the distance function, Q, Q N Representing the normalized weights;
if the decision spacecraft is an escape spacecraft, escaping the spacecraft state information sequence according to the decision spacecraft state information sequence, and predicting the tracking spacecraft state information sequence estimation with the set window length by solving the minimum value of the tracking spacecraft objective function under the constraint conditionThe following formula is shown:
wherein x is obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Represents the safe distance between the spacecraft, θ represents the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N represents the predicted window length,representing the position constraint of tracking spacecraft, +.>Representation ofTracking control constraints of the spacecraft, M representing the maximum number of iterations, d representing the distance function, Q, Q N Representing the normalized weights;
the step of solving the control sequence of the decision spacecraft and updating the corresponding state information sequence of the decision spacecraft through the game objective function of the decision spacecraft according to the state information sequence estimation of the opponent spacecraft comprises the following steps:
If the decision spacecraft is a tracking spacecraft, acquiring a tracking spacecraft control sequence and updating a corresponding tracking spacecraft state information sequence by solving a tracking spacecraft objective function minimum value according to the predicted opponent spacecraft state information sequence estimation, wherein the following formula is shown:
wherein,estimating, x, the state information sequence of the escape spacecraft predicted in the current iteration obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Representing the safe distance between the spacecraft, θ representing the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N representing the predicted window length, < >>Representing position constraints of the escape spacecraft, +.>Represents the control constraint of the escape spacecraft, M represents the maximum number of iterations, D represents the distance, Q, Q N Representing the normalized weights;
if the decision spacecraft is an escape spacecraft, solving the maximum value of an objective function of the escape spacecraft according to the predicted state information sequence estimation of the opponent spacecraft to obtain an escape spacecraft control sequence and updating the corresponding escape spacecraft state information sequence, wherein the method is as follows:
wherein,estimating, x, a sequence of state information of the tracking spacecraft predicted in the current iteration obs Representing state variables of an obstacle spacecraft, R obs Represents the radius of an obstacle spacecraft, R rob Representing the safe distance between the spacecraft, θ representing the angle between the connection of the tracking spacecraft and the escape spacecraft and the connection of the escape spacecraft and the sun, N representing the predicted window length, < >>Representing position constraints of the escape spacecraft, +.>Represents the control constraint of the escape spacecraft, M represents the maximum number of iterations, d represents the distance, Q, Q N Representing the normalized weights;
if the set iteration ending condition is not met, entering the next iteration; otherwise, ending the iteration, outputting the optimal control quantity of the decision spacecraft according to the control sequence of the decision spacecraft, and comprising the following steps:
manually setting the maximum iteration times according to the allowed decision time;
ending the iteration if the current iteration reaches the maximum iteration times, wherein the first action of the control sequence of the decision spacecraft obtained by the last iteration calculation is the optimal control quantity of the decision spacecraft;
if the current iteration does not reach the maximum iteration number, if the objective function values of the decision spacecraft and the opponent spacecraft of the last iteration meet |J p -J e The first control quantity of the control sequence of the decision spacecraft obtained by the last iterative calculation is the optimal control quantity of the decision spacecraft; otherwise, the next iteration is entered.
3. A computer storage medium, wherein the computer storage medium stores a spacecraft online game planning program considering barrier constraints, and the spacecraft online game planning program based on considering barrier constraints implements the steps of the spacecraft online game planning method considering barrier constraints according to claim 1 when the spacecraft online game planning program considering barrier constraints is executed by at least one processor.
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