An efficient energy planning method for beyond-visual-range maneuvering of aircraft based on control parameterization

Abstract

The present invention discloses a method for efficient beyond-visual-range maneuvering energy planning for aircraft based on control parameterization, which mainly solves the problems of poor versatility of existing planning algorithms and inability to guarantee real-time performance in airborne conditions. The method first considers modeling the energy changes during the aircraft maneuvering process, calculating the current energy possessed by the aircraft, and then predicting the current maximum available overload of the aircraft. The energy machine process carried out by the aircraft to reach the target instruction is then established as an optimization problem and then solved. Finally, the control parameterization method is used to solve the problem and the aircraft energy maneuvering process is obtained online. Compared with other algorithms based on model prediction, the present invention has a shorter solution time and better real-time performance in airborne applications.

Description

Technical Field

[0001] The present invention belongs to the technical field of aircraft energy planning, and in particular relates to a method for planning aircraft beyond visual range high-efficiency maneuvering energy based on control parameterization. Background Art

[0002] With the rapid advancement of modern weapons and radar technology, fighter jet combat has long since moved beyond the traditional reliance on visual targeting and gunfire. Beyond-visual-range (BVR) air combat has become a staple of modern air warfare. In BVR combat, fighters primarily maneuver to position themselves for advantage, evading enemy missiles while simultaneously launching missiles to shoot down the enemy. Therefore, the ultimate outcome of an air battle hinges primarily on the reconnaissance capabilities, weapons strike capabilities, and maneuverability of both aircraft. As aircraft accelerate, decelerate, climb, descend, and hover during maneuvers, energy and overload fluctuate. In modern air combat, the reconnaissance and strike capabilities of both sides are often comparable, so efficient planning of maneuvering energy can maximize combat advantage.

[0003] Domestic and international research on beyond-visual-range air combat maneuver energy planning mainly focuses on the analysis of longitudinal flight trajectories, and is based on the current state. This has the following problems: (1) Only the longitudinal trajectory of the aircraft is analyzed, which cannot be applied in all scenarios. (2) The energy planning of the aircraft to achieve the target state can only be simply set, and it is impossible to achieve multiple states at the same time. (3) During the process of aircraft maneuver energy decision-making, the aircraft state is not updated, so the results are somewhat different from expectations. (4) Traditional model prediction algorithms require a lot of computing resources and cannot guarantee the real-time and precision of the calculation in the airborne situation.

[0004] The above methods have the following technical problems: (1) the planning algorithm has poor versatility; (2) the real-time performance cannot be guaranteed in the airborne case. Summary of the Invention

[0005] The purpose of the present invention is to provide an aircraft beyond visual range efficient maneuver energy planning method based on control parameterization, which mainly solves the problems that the existing planning algorithms have poor versatility and cannot guarantee real-time performance under airborne conditions.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A method for efficient beyond-visual-range maneuvering energy planning for an aircraft based on control parameterization comprises the following steps:

[0008] S1, establish the three-degree-of-freedom dynamic equation of the aircraft's angle of attack and calculate the aircraft's overload;

[0009] S2, establish an energy model for the aircraft's maneuvering process and calculate the current energy possessed by the aircraft;

[0010] S3, based on the current total energy available to the aircraft, calculate the upper and lower limits of the aircraft's available overload;

[0011] S4, establishing an objective function of the interception time that satisfies the aircraft kinematic model;

[0012] S5, using the aircraft's performance constraints and the aircraft's load factor as the constraints of the objective function, establishes the optimal control problem of beyond-visual-range air combat maneuver energy planning;

[0013] S6, using the control parameter method to solve the optimal control problem, and finally outputting the control sequence for the aircraft to intercept the target speed instruction, so as to achieve the fastest speed and meet the optimal maneuver of intercepting the instruction with the energy consumption not exceeding the total energy of the aircraft.

[0014] Furthermore, in step S1, the three-degree-of-freedom dynamic equation is:

[0015]

[0016] x(t)=[x(t), y(t), z(t), V(t), γ(t), χ(t)] T

[0017] u(t)=[T(t),α(t),μ(t)] T

[0018] Where the state variables x are the position coordinates (x, y, z), the climb angle γ, the yaw angle χ, and the velocity V; the control variables u are the aircraft thrust T, the aircraft angle of attack α, and the roll angle μ; D is the drag during flight, W is the total weight of the aircraft, and g is the acceleration due to gravity; the overload of the aircraft is:

[0019]

[0020] Where n x is the tangential overload of the aircraft, that is, the overload pointing to the flight direction, n n It is normal overload, and its direction is perpendicular to the flight direction.

[0021] Furthermore, in step S2, the energy model of the maneuvering process is:

[0022]

[0023] Where, E T is the total energy of the aircraft, which is composed of the kinetic energy and potential energy of the aircraft; E D is the kinetic energy of the aircraft, E Sis the potential energy of the aircraft; m is the mass of the aircraft, g is the acceleration due to gravity, and z is the flight altitude of the aircraft.

[0024] Furthermore, in step S4, the objective function is:

[0025]

[0026] where t f is the terminal time, that is, the optimization goal can be described as reaching the target in the shortest time.

[0027] Furthermore, the optimal control problem obtained in step S5 is:

[0028]

[0029]

[0030] x(0)=x0

[0031] u(t)=[T(t),α(t),μ(t)] T

[0032]

[0033]

[0034]

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] (1) The present invention considers both longitudinal and lateral maneuvers of the aircraft and analyzes the entire energy planning process. The aircraft status can be updated during the planning process. Compared with other algorithms based on model prediction, the present invention has a shorter solution time and better real-time performance for airborne applications.

[0037] (2) The present invention can design diversified instructions for interception by aircraft terminals, making it applicable to more scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a principle block diagram of the present invention.

[0039] Figure 2 This is a graph showing the fastest target speed interception in an embodiment of the present invention.

[0040] Figure 3 This is a graph showing the minimum energy target speed interception in an embodiment of the present invention.

[0041] Figure 4 This is a curve diagram of the target height captured at the fastest speed in an embodiment of the present invention.

[0042] Figure 5 This is a graph showing the minimum energy target height interception in an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The present invention will be further described below with reference to the accompanying drawings and examples. The embodiments of the present invention include but are not limited to the following examples.

[0044] like Figure 1 As shown, the present invention discloses a method for efficient beyond-visual-range (BVR) maneuvering energy planning based on control parameterization. This method first models the energy changes during the maneuvering process, calculates the aircraft's current energy, and then predicts the aircraft's current maximum available overload. The energy process required to achieve the target command is then formulated as an optimization problem and solved. Finally, the control parameterization method is used to solve the problem, resulting in an online calculation of the aircraft's energy maneuvering process.

[0045] The present invention uses a nonlinear predictive control method to optimize the energy during the aircraft maneuvering process. The three-degree-of-freedom dynamic equation considering the aircraft's angle of attack is as follows:

[0046]

[0047] x(t)=[x(t), y(t), z(t), V(t), γ(t), χ(t)] T

[0048] u(t)=[T(t),α(t),μ(t)] T

[0049] Wherein, the state variables x are the position coordinates (x, y, z), the climb angle γ, the yaw angle χ, and the velocity V, respectively; the control variables u are the aircraft thrust T, the aircraft angle of attack α, and the roll angle μ; L is the aircraft lift, D is the drag during flight, W is the total weight of the aircraft, and g is the acceleration due to gravity;

[0050]

[0051] where n x is the tangential overload of the aircraft, that is, the overload pointing to the flight direction, n n It is normal overload, and its direction is perpendicular to the flight direction.

[0052] After establishing the dynamic equations, the energy model of the aircraft's maneuvering process is established. According to the analysis of energy changes during the aircraft's flight, the total energy can be expressed as:

[0053]

[0054] Where, ET is the total energy of the aircraft, which is composed of the kinetic energy and potential energy of the aircraft; E D is the kinetic energy of the aircraft, E S is the potential energy of the aircraft; m is the mass of the aircraft, g is the acceleration due to gravity, and z is the flight altitude of the aircraft.

[0055] Assuming that the initial thrust of the aircraft offsets the aircraft's drag during level flight, and that the drag experienced by the aircraft does not change when the flight state changes, the thrust and flight state increment equations can be expressed as:

[0056]

[0057] The change in thrust is proportional to the rate of change of the vehicle's energy per unit. The analysis approximates that elevator and rudder deflections do not alter the vehicle's total energy. This indicates that rudder deflection can be used to convert the vehicle's kinetic and potential energies into each other without significant energy loss. Therefore, the upper and lower limits of the vehicle's available overload can be calculated based on the vehicle's current total available energy, providing a basis for subsequent planning algorithms.

[0058] For example, when the interception target is a speed instruction, the current total energy is calculated based on our state, the goal is set to intercept the target speed instruction at the fastest speed, and the objective function is established based on the interception time:

[0059]

[0060] where t f is the terminal time, that is, the optimization goal can be described as reaching the target in the shortest time.

[0061] The objective function satisfies the aircraft kinematic model:

[0062]

[0063] x(0)=x0

[0064] Considering the performance constraints of the aircraft, the value range of the aircraft's load factor should meet the following requirements:

[0065] T min ≤T(t)≤T max

[0066] α min ≤α(t)≤α max

[0067] μ min ≤μ(t)≤μ max

[0068] E(t)≤E Tmax

[0069] V min ≤V(t)≤V max

[0070] χ min ≤χ(t)≤χ max

[0071] γ min ≤γ(t)≤γ max

[0072] Among them, E Tmax The upper and lower limits of the control quantity [T, α, μ] are determined by the performance of the aircraft itself, and the upper and lower limits of the state quantity are determined by the performance of the aircraft itself and the specific scenario.

[0073] The optimal control problem of beyond visual range air combat maneuver energy planning is: satisfying the system dynamic equation constraint:

[0074]

[0075] x(0)=x0

[0076] And the performance inequality constraints:

[0077] T min ≤T(t)≤T max

[0078] α min ≤α(t)≤α max

[0079] μ min ≤μ(t)≤μ max

[0080] E(t)≤E Tmax

[0081] V min ≤V(t)≤V max

[0082] χ min ≤χ(t)≤χ max

[0083] γ min ≤γ(t)≤γ max

[0084] Considering constraints such as the radar frame angle, the objective function is minimized, and the target capture instruction is set as the terminal constraint. The threshold and constraint form in the performance inequality constraint are different for different scenarios.

[0085] For the above energy planning optimal control problem, the control parameter method is used to solve it, and finally the aircraft control sequence for intercepting the target speed instruction is output, which achieves the fastest speed and satisfies the optimal maneuver of intercepting the instruction with energy consumption not exceeding the total energy of the aircraft.

[0086] The above-mentioned continuous-time aircraft particle model can be regarded as a discrete system within a short step size, and the continuous system can be approximated by a discrete difference system. The time periods are equally discretized, and the continuous-time maneuver decision control quantity is approximated by parameter discretization. When the optimization time domain is short, further optimization of the tracking control hysteresis and calculation time of the underlying controller can be considered.

[0087] Taking actual operation as an example, the intercepted target speed is analyzed. The specific values ​​of the performance parameters and optimization problem parameters in the simulation are shown in Table 1. The simulation environment is Matlab 2019a, and Fmincon is used to solve the optimization problem.

[0088] Table 1 Aircraft maneuverability parameters and optimization problem parameters

[0089]

[0090]

[0091] Consider that the aircraft reaches a given height and speed, and intercepts the given command in the fastest and least energy-consuming manner. Set the initial state of the aircraft to:

[0092] [x, y, z, V, χ, γ] T =[30000, 0, 5000, 160, π, 0] T

[0093] Set the target height to h tf =6500m, set the target speed to V tf =200m / s, by Figures 2 to 5 As can be seen, when the aircraft wants to reach the target speed as quickly as possible, it requires greater thrust for acceleration. If it wants to reach the target speed with less energy, it chooses to trade altitude for speed and dive downward. The situation is similar for reaching the target altitude. The energy consumed and time required to reach the target command are shown in Table 2.

[0094] Table 2. Aircraft energy maneuvering results in beyond visual range air combat

[0095]

[0096] Through the above design, the present invention simultaneously considers the longitudinal and lateral maneuvers of the aircraft, and analyzes the entire energy planning process. The aircraft status can be updated during the planning process. Compared with other algorithms based on model prediction, the present invention has a shorter solution time and better real-time performance in airborne applications.

[0097] The above embodiment is only one of the preferred implementation methods of the present invention and should not be used to limit the scope of protection of the present invention. Any changes or modifications that have no substantive meaning made to the main design concept and spirit of the present invention, as long as the technical problems solved are still consistent with the present invention, should be included in the scope of protection of the present invention.

Claims

1. A method for efficient beyond-visual-range maneuvering energy planning for an aircraft based on control parameterization, characterized in that: The steps include: S1, establish the three-degree-of-freedom dynamic equation of the aircraft's angle of attack and calculate the aircraft's overload; the three-degree-of-freedom dynamic equation is: x(t)=[x(t),y(t),z(t),V(t),γ(t),χ(t)] T u(t)=[T(t),α(t),μ(t)] T Where the state variables x are the position coordinates (x, y, z), the climb angle γ, the yaw angle χ, and the velocity V; the control variables u are the aircraft thrust T, the aircraft angle of attack α, and the roll angle μ; L is the aircraft lift, D is the drag during flight, W is the total weight of the aircraft, and g is the acceleration due to gravity; the overload of the aircraft is: where n x is the tangential overload of the aircraft, that is, the overload pointing to the flight direction, n n It is normal overload, and its direction is perpendicular to the flight direction; S2, establish an energy model for the aircraft's maneuvering process and calculate the current energy of the aircraft; the energy model for the maneuvering process is: Where, E T is the total energy of the aircraft, which is composed of the kinetic energy and potential energy of the aircraft; E D is the kinetic energy of the aircraft, E S is the potential energy of the aircraft; m is the mass of the aircraft, g is the acceleration due to gravity, and z is the flight altitude of the aircraft; S3, based on the current total energy available to the aircraft, calculate the upper and lower limits of the aircraft's available overload; S4, establish the objective function of the interception time that satisfies the aircraft kinematic model: where t f To optimize the terminal time of the problem, that is, the goal is to consume the least time to achieve the goal; S5, using the aircraft performance constraint and the aircraft load factor as the constraint conditions of the objective function, establish the optimal control problem of beyond visual range air combat maneuver energy planning: S6, using the control parameter method to solve the optimal control problem, and finally outputting the control sequence for the aircraft to intercept the target speed instruction, so as to achieve the fastest speed and meet the optimal maneuver of intercepting the instruction with the energy consumption not exceeding the total energy of the aircraft.

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