An optimal guidance method under weak overload capability constraint

Abstract

The application discloses an optimal guidance method under weak overload capacity constraint, and establishes a relative coordinate system with a mobile target as an origin to reduce the degree of kinematic nonlinearity; on the basis of a normal optimal interception method obtained by solving in the relative coordinate system, an optimal control problem is established to design a bias term with variable coefficients considering the overload capacity limitation; autonomous operation is realized throughout the whole process, and accurate interception of a high-maneuvering mobile target is realized under the premise that the overload capacity and the target maneuvering capacity are weak.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of unmanned aerial vehicle control, in particular to an optimal guidance method under weak overload capacity constraint. BACKGROUND

[0002] With the improvement of intelligent level, unmanned aerial vehicles play an important role in various fields due to their low cost, flexible deployment and strong operability. However, due to the low cost and small size of unmanned aerial vehicles, there are certain physical characteristic limitations, such as speed limitation, field of view angle limitation of carrying photoelectric pod, overload limitation, etc. Among them, the overload limitation plays an important role in the working effect of the unmanned aerial vehicle. This is because the control command issued to the unmanned aerial vehicle is usually an acceleration command, and the traditional guidance law can only meet the position constraint of reaching the target, without considering the overload ratio between the unmanned aerial vehicle and the target. When the acceleration command exceeds the overload limitation of the unmanned aerial vehicle, especially when the overload capacity of the unmanned aerial vehicle is less than the maximum overload of the maneuvering target, the terminal intersection precision will be seriously affected, resulting in target escape and failure of the interception task.

[0003] Therefore, there is a need for a method that can still guarantee accurate interception of high maneuvering targets in a balanced or weak situation. The existing methods for constraining the overload command mainly include nonlinear control and linear control. Among them, the nonlinear control is mainly based on sliding mode control, which constructs a sliding surface related to acceleration constraint and a reaching law, introduces a saturation function in the second-order dynamics, and proves its stability and convergence based on Lyapunov function. However, the above nonlinear method is prone to energy waste due to the lack of performance index. In the linear control method, an energy consumption optimization function containing weight coefficients is constructed, and the optimal guidance law with miss distance as the terminal constraint is derived using the Schwarz inequality, or a suboptimal guidance scheme is proposed based on linear quadratic optimal control. However, the above methods only consider the constraint of the overload of the unmanned aerial vehicle itself, but do not constrain the overload ratio of both sides, often requiring the overload capacity of the task unmanned aerial vehicle to be superior to the maximum maneuvering of the target.

[0004] Due to the above reasons, the present inventors have conducted in-depth research on the guidance interception problem of intercepting high maneuvering targets under overload capacity disadvantage, in the hope of designing an optimal guidance method under weak overload capacity constraint. SUMMARY

[0005] In order to overcome the above problems, the present inventors have made intensive research and designed an optimal guidance method under weak overload capacity constraint, which establishes a relative coordinate system with a mobile target as the origin to reduce the degree of kinematic nonlinearity; on the basis of the normal optimal interception method obtained in the relative coordinate system, an optimal control problem is established to design a variable coefficient bias term considering the overload capacity limitation; the whole autonomous operation is realized, the precise interception of the high-maneuvering mobile target is realized under the premise of the weak overload capacity and the target maneuvering capacity, and thus the present application is completed.

[0006] Specifically, the present application aims to provide an optimal guidance method under weak overload capacity constraint, which comprises the following steps:

[0007] S1, according to the motion state information of the target and the maximum acceleration of the task unmanned aerial vehicle itself, the initial zero-control miss distance is used to determine whether the initial speed direction of the task unmanned aerial vehicle meets the interception requirement, and the task unmanned aerial vehicle is launched in the case that the initial speed direction of the task unmanned aerial vehicle meets the interception requirement;

[0008] S2, the motion state information of the target is obtained in real time by the photoelectric pod carried on the task unmanned aerial vehicle;

[0009] S3, the speed and acceleration of the target are obtained in real time according to the motion state information of the target;

[0010] S4, the normal guidance instruction with time-varying coefficient is obtained in real time based on the minimization of control consumption, and the precise intersection with the mobile target is realized under the premise of meeting the equal potential overload limitation by controlling the task unmanned aerial vehicle through the normal guidance instruction.

[0011] Wherein, before S2 is executed, the target is photographed by the photoelectric pod carried on the task unmanned aerial vehicle to obtain continuous images containing the target; the state estimation of the target is obtained through the image pixel deviation and angle information, and the photoelectric pod continuously observes the target through the angular rate instruction.

[0012] Wherein, in S2, the motion state information of the target comprises: the line-of-sight angle q of the target relative to the task unmanned aerial vehicle, and the relative distance r between the task unmanned aerial vehicle and the target.

[0013] Wherein, in S4, the normal guidance instruction a M is the acceleration instruction perpendicular to the speed direction of the task unmanned aerial vehicle, which is obtained by the following formula (I):

[0014]

[0015] Wherein, a ⊥ represents the acceleration perpendicular to the relative speed direction between the task unmanned aerial vehicle and the target in the relative coordinate system, i.e. the relative acceleration instruction.

[0016] a T denotes the acceleration of the target in the inertial coordinate system;

[0017] γ R denotes the angle between the relative velocity between the mission UAV and the target and the X axis of the inertial coordinate system;

[0018] γ T denotes the velocity angle of the target;

[0019] γ M denotes the velocity angle of the mission UAV.

[0020] wherein the relative acceleration instruction a ⊥ is obtained in real time by the following formula (two):

[0021]

[0022] wherein N denotes a guidance coefficient;

[0023] ZEM denotes a zero-control miss distance;

[0024] r denotes the relative distance between the mission UAV and the target;

[0025] V R denotes the relative velocity between the mission UAV and the target;

[0026] C and θ each independently denote a convergence coefficient of the optimal control problem;

[0027] a Mc denotes the acceleration instruction of the mission UAV obtained by the prediction solution.

[0028] wherein the zero-control miss distance ZEM is obtained in real time by the following formula (three):

[0029]

[0030] wherein the acceleration instruction a Mc is obtained in real time by the following formula (four):

[0031]

[0032] wherein in S1, when the following formula (five) is established, the initial velocity direction of the mission UAV satisfies the interception requirement:

[0033]

[0034] wherein ZEM0 denotes the zero-control miss distance at the initial moment;

[0035] a M,maxrepresents the maximum acceleration of the task unmanned aerial vehicle itself;

[0036] a T,max represents the target maximum acceleration;

[0037] r0 represents the relative distance between the task unmanned aerial vehicle and the target at the initial moment;

[0038] N represents a guidance coefficient;

[0039] V R represents the relative velocity between the task unmanned aerial vehicle and the target.

[0040] wherein the zero-effort miss at the initial moment ZEM0 is obtained by the following formula (six):

[0041] ZEM0 = -r0 sin (q0 - γR0) (six)

[0042] wherein r0 represents the relative distance between the task unmanned aerial vehicle and the target at the initial moment;

[0043] q0 represents the line-of-sight angle of the target relative to the task unmanned aerial vehicle at the initial moment;

[0044] γ R0 represents the angle between the relative velocity between the task unmanned aerial vehicle and the target at the initial moment and the X-axis of the inertial coordinate system.

[0045] The present application has the beneficial effects including:

[0046] (1) According to the optimal guidance method under weak overload capacity constraint provided by the present application, the space target is identified and tracked through the machine vision technology of the airborne photoelectric pod, compared with radar and vehicle-mounted photoelectric detection equipment, the method has high precision, strong intuitiveness, low cost and is not affected by clutter interference;

[0047] (2) According to the optimal guidance method under weak overload capacity constraint provided by the present application, the method can estimate based on target motion and autonomously navigate accordingly; combined with a flexible and reliable task execution system, the method can quickly and stably track non-cooperative maneuvering targets in the shortest time, and can enable the task unmanned aerial vehicle with inferior overload capacity to intercept high maneuvering targets, and realize optimal guidance interception under acceleration limitation conditions;

[0048] (3) According to the optimal guidance method under weak overload capacity constraint provided by the present application, in the method, it is judged whether the initial velocity direction of the task unmanned aerial vehicle can meet the interception demand under the overload limitation before the aircraft takes off, if not, the initial velocity direction of the task unmanned aerial vehicle or the overload capacity of the task unmanned aerial vehicle is adjusted, and if yes, the task unmanned aerial vehicle is released. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 Fig. 1 shows the overall logic diagram of the optimal interception guidance method under weak overload capability constraint according to a preferred embodiment of the present application;

[0050] Figure 2 Fig. 4 shows the motion trajectory of the high-maneuverability target and the task UAV in the experimental example of the present application;

[0051] Figure 3 Fig. 5 shows the diagram of the relative distance between the task UAV and the high-maneuverability target varying with time in the experimental example of the present application;

[0052] Figure 4 Fig. 6 shows the acceleration variation curve of the task UAV with given acceleration limit in the experimental example of the present application. DETAILED DESCRIPTION

[0053] The present application will be further described in details by the accompanying drawings and examples. The features and advantages of the present application will become more apparent through these descriptions.

[0054] The word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any implementation described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other implementations. Unless specifically indicated otherwise, the drawings are not necessarily to scale.

[0055] The present application provides an optimal guidance method under weak overload capability constraint, as shown in Figure 1 the method comprises the following steps,

[0056] S1, judging whether the initial velocity direction of the task UAV meets the interception requirement according to the motion state information of the target and the maximum acceleration of the task UAV itself through the initial zero-control miss distance, and launching the task UAV in the case that the initial velocity direction of the task UAV meets the interception requirement;

[0057] S2, obtaining the motion state information of the target in real time through the photoelectric pod carried on the task UAV;

[0058] S3, obtaining the velocity and acceleration of the target in real time according to the motion state information of the target;

[0059] S4, obtaining the normal guidance instruction with time-varying coefficient in real time based on the minimization of control consumption, and realizing the accurate intersection with the maneuverable target under the premise of meeting the equal-potential overload limit through the normal guidance instruction to control the task UAV.

[0060] Preferably, the task unmanned aerial vehicle is preferably selected as a rotor unmanned aerial vehicle, in particular an unmanned aerial vehicle with four or more than four propellers; the real-time obtained acceleration instruction is input into a rotor control system of the task unmanned aerial vehicle, the rotor control system can adjust the rotor propeller rotating speed according to the input acceleration instruction, the rotating speed change causes the rotor lift change, and then the attitude and position of the task unmanned aerial vehicle are controlled.

[0061] The optoelectronic pod can be selected from the existing optoelectronic pod in the art, which can execute target tracking, and output the line-of-sight angle and line-of-sight angle rate of the target relative to the multi-rotor aircraft.

[0062] The velocity, position and acceleration information of the target in the application are all velocity, position information in the inertial system, the inertial system refers to taking the mass center of the task unmanned aerial vehicle as the origin, the geographical east direction as the x axis, the z axis upward as positive, and the y axis determined by the right-hand rule. The relative coordinate system takes the mass center of the target unmanned aerial vehicle as the origin, the geographical east direction as the x axis, the z axis upward as positive, and the y axis determined by the right-hand rule.

[0063] In a preferred embodiment, before S2 is executed, the target is photographed by the optoelectronic pod carried on the task unmanned aerial vehicle to obtain continuous images containing the target; the state estimation of the target is obtained through image pixel deviation and angle information, and the optoelectronic pod continuously observes the target through the angle rate instruction.

[0064] Specifically, the continuous images containing the target unmanned aerial vehicle are processed by the on-board machine vision algorithm to give the state estimation of the target unmanned aerial vehicle as the control information source of the optoelectronic pod on the multi-rotor aircraft;

[0065] Preferably, the target is tracked in real time and the position of the unmanned aerial vehicle relative to the camera is calculated in real time through the existing on-board machine vision algorithm in the application.

[0066] In a preferred embodiment, in S2, the motion state information of the target includes: the line-of-sight angle q of the target relative to the task unmanned aerial vehicle, and the relative distance r between the task unmanned aerial vehicle and the target.

[0067] Preferably, in step S2, the velocity and acceleration components of the target can be obtained by the existing target state estimation algorithm, and are consistent with the true situation;

[0068] The predicted values of the motion information can be obtained by the existing Kalman filtering algorithm.

[0069] In a preferred embodiment, in S4, the normal guidance instruction a M is the acceleration instruction in the inertial coordinate system perpendicular to the direction of the task unmanned aerial vehicle velocity, which is obtained by the following formula (I):

[0070]

[0071] wherein a ⊥ represents an acceleration perpendicular to the relative velocity between the task UAV and the target in the relative coordinate system, i.e. the relative acceleration command;

[0072] a T represents the acceleration of the target in the inertial coordinate system;

[0073] γ R represents the angle between the relative velocity between the task UAV and the target and the X axis of the inertial coordinate system;

[0074] γ T represents the angle of velocity of the target;

[0075] γ M represents the angle of velocity of the task UAV.

[0076] Preferably, the relative acceleration command a ⊥ is obtained in real time by the following formula (II):

[0077]

[0078] wherein N represents a guidance coefficient, preferably a constant, more preferably 4;

[0079] ZEM represents the zero-effort miss;

[0080] r represents the relative distance between the task UAV and the target;

[0081] V R represents the relative velocity between the task UAV and the target;

[0082] C and θ each independently represent a convergence coefficient of the optimal control problem, preferably C is 3-5, more preferably 4; preferably θ is 0.1;

[0083] a Mc represents the predicted task UAV acceleration command obtained by solving.

[0084] Preferably, the zero-effort miss ZEM is obtained in real time by the following formula (III):

[0085]

[0086] Preferably, the predicted task UAV acceleration command a Mc is obtained in real time by the following formula (IV):

[0087]

[0088] In a preferred embodiment, in S1, when the following formula (five) is satisfied, the initial velocity direction of the task UAV meets the interception requirement:

[0089]

[0090] wherein ZEM0 represents the zero-control miss distance at the initial moment;

[0091] a M,max represents the maximum acceleration of the task UAV itself;

[0092] a T,max represents the maximum acceleration of the target;

[0093] r0 represents the relative distance between the task UAV and the target at the initial moment;

[0094] N represents the guidance coefficient;

[0095] V R represents the relative velocity between the task UAV and the target.

[0096] Preferably, the zero-control miss distance ZEM0 at the initial moment is obtained by the following formula (six):

[0097] ZEM0 = -r0 sin(q0-γR0) (six)

[0098] wherein r0 represents the relative distance between the task UAV and the target at the initial moment;

[0099] q0 represents the line-of-sight angle of the target relative to the task UAV at the initial moment;

[0100] γ R0 represents the angle between the relative velocity between the task UAV and the target at the initial moment and the X-axis of the inertial coordinate system; the angle is obtained by the initial velocity direction of the task UAV and the velocity direction of the target.

[0101] Although it is the optimal scheme that the takeoff direction of the aircraft points to the target, it is difficult to ensure that the takeoff direction points to the target in any case in actual operation. Based on this, in the present application, it is judged whether the initial velocity direction of the task UAV meets the interception requirement before the aircraft takes off. If not, the initial velocity direction of the task UAV or the overload capacity of the task UAV is continuously adjusted. If yes, the task UAV is launched. By making a prediction before the task UAV takes off, the interception effect of the task UAV can be further improved.

[0102] Experimental Example

[0103] The initial position (x t0 ,y t0 ) of the target UAV = (8000, 0) m;

[0104] Initial speed V of target UAV t0 = 300 m / s

[0105] The target UAV makes two-dimensional maneuvering motion in the air, and the acceleration perpendicular to the target speed direction in the inertial system is as follows:

[0106]

[0107] Wherein, g = 9.8 m / s 2

[0108] The initial position, initial speed and overload limit of the task UAV are as shown in the following table

[0109]

[0110]

[0111] It is judged that the following formula (five) is established, and the task UAV is launched;

[0112]

[0113] Wherein, ZEM0 represents the zero-control miss distance at the initial time;

[0114] a M,max represents the maximum acceleration of the task UAV itself;

[0115] a T,max is the maximum acceleration of the target;

[0116] r0 represents the relative distance between the task UAV and the target at the initial time;

[0117] N represents the guidance coefficient;

[0118] V R represents the relative speed between the task UAV and the target.

[0119] The zero-control miss distance ZEM0 at the initial time is obtained by the following formula (six):

[0120] ZEM0 = -r0 sin(q0-γ R0 )(six)

[0121] Wherein, r0 represents the relative distance between the task UAV and the target at the initial time;

[0122] q0 represents the line-of-sight angle of the target relative to the task UAV at the initial time;

[0123] γ R0 represents the angle between the relative speed between the task UAV and the target at the initial time and the X-axis of the inertial coordinate system. ​

[0124] The target is tracked by the optical pod, and the guidance instructions of the task unmanned plane are solved in real time by the following formulas (I) and (II):

[0125]

[0126] N represents a guide coefficient, and is 4;

[0127] ZEM represents a zero-control miss distance;

[0128] r represents a relative distance between the task unmanned plane and the target;

[0129] V R represents a relative speed between the task unmanned plane and the target;

[0130] C and θ are convergence coefficients of the optimal control problem, C is 4, and θ is 0.1;

[0131] a T represents an acceleration of the target in the inertial coordinate system;

[0132] a Mc represents an acceleration instruction of the task unmanned plane obtained by prediction and solving;

[0133] ZEM can be obtained in real time according to the following formula (III):

[0134]

[0135] γ R represents an angle between the relative speed between the task unmanned plane and the target and the X axis of the inertial coordinate system;

[0136] γ M is a speed angle of the task unmanned plane;

[0137] a Mc is obtained in real time by the following formula (IV):

[0138]

[0139] γ T represents a speed angle of the target;

[0140] The motion trajectories of the task unmanned plane and the high-maneuvering target are shown in FIG. 1, and it can be known from FIG. 2 that the optimal guidance method under weak overload capacity constraint provided in the application can successfully intercept the high-maneuvering target. Figure 2 Figure 2 The relative distance between the task unmanned plane and the high-maneuvering target changes with time, as shown in FIG. 3. In combination with FIG. 1 and FIG. 2,

[0141] Figure 3 Figure 2 Figure 3 ​​​​It can be known that the optimal guidance method under weak overload capacity constraint can make the unmanned vehicle hit the mobile target and meet the off-target requirement that the relative distance with the target is less than 0.3 m.

[0142] Figure 4 The acceleration change curve of the task unmanned vehicle under the given acceleration limit is shown. Figure 4 It can be known that the optimal guidance method under weak overload capacity constraint can meet the precise interception of the high mobile target under the premise that the overload capacity and the target mobile capacity are weak.

[0143] The above describes the present application in combination with the preferred embodiments, but these embodiments are only exemplary and are used for illustration only. On this basis, various substitutions and improvements can be made to the present application, and these all fall within the protection scope of the present application.

Claims

1. An optimal guidance method under weak overload capability constraint, characterized in that, The optimal guidance method comprises the following steps: S1, judging whether the initial speed direction of the task unmanned aerial vehicle meets the interception requirement according to the motion state information of the target and the maximum acceleration of the task unmanned aerial vehicle itself through the initial zero-control miss distance, and launching the task unmanned aerial vehicle in the case that the initial speed direction of the task unmanned aerial vehicle meets the interception requirement; In S1, the initial speed direction of the task unmanned aerial vehicle meets the interception requirement when the following formula (five) is established; (v) wherein, represents the zero-control miss distance at the initial time; denotes the maximum acceleration of the mission drone itself; Target maximum acceleration; represents the relative distance of the task UAV and the target at the initial moment; denotes a pilot coefficient; represents the relative velocity between the mission drone and the target; S2, obtaining the motion state information of the target in real time through the photoelectric pod carried on the task unmanned aerial vehicle; In S2, the motion state information of the target comprises: a line-of-sight angle of the target relative to the task unmanned aerial vehicle , a relative distance between the task unmanned aerial vehicle and the target ; S3, obtaining the speed and acceleration of the target in real time according to the motion state information of the target; S4, obtaining the normal guidance instruction containing time-varying coefficients in real time based on the minimization of control consumption, and realizing the precise intersection with the target under the premise of meeting the equal potential overload limit through the normal guidance instruction to control the task unmanned aerial vehicle. In S4, the normal guidance instruction is an acceleration instruction perpendicular to the direction of the mission UAV speed, obtained by the following formula (I): (I) wherein, represents the acceleration perpendicular to the relative velocity direction between the task UAV and the target in the relative coordinate system, i.e., the relative acceleration command; a represents the acceleration of the target in the inertial coordinate system; denotes the angle between the relative velocity between the mission drone and the target and the X-axis of the inertial coordinate system; denotes the velocity angle of the target; denotes the speed angle of the mission drone.

2. The optimal guidance method under weak overload capacity constraint according to claim 1, characterized in that, Before S2 is executed, the target is shot through the photoelectric pod carried on the task unmanned aerial vehicle to obtain continuous images containing the target; the state estimation of the target is obtained through the image pixel deviation and angle information, and the photoelectric pod continuously observes the target through the angular rate instruction.

3. The optimal guidance method under weak overload capacity constraint according to claim 1, characterized in that, the relative acceleration command in real time by the following equation (two): (ii) wherein denotes a pilot coefficient; represents the zero-control miss distance; represents the relative distance between the mission drone and the target; represents the relative velocity between the mission drone and the target; and each independently represents a convergence coefficient for the optimal control problem; represents the predicted solution of the task UAV acceleration command.

4. The optimal guidance method under weak overload capacity constraint according to claim 3, characterized in that, The zero-control miss distance is obtained in real time by the following equation (III): (Three).

5. The optimal guidance method under weak overload capacity constraint according to claim 3, characterized in that, The predicted solution of the task UAV acceleration instruction is obtained in real time by the following equation (four): (iv).

6. The optimal guidance method under weak overload capacity constraint according to claim 1, characterized in that, the zero-control miss distance at the initial time is obtained by the following equation (six) (vi) wherein, denotes the relative distance between the task UAV and the target at the initial moment. represents the line-of-sight angle of the target relative to the mission drone at the initial time instant; denotes the angle between the relative velocity of the task UAV and the target at the initial moment and the X-axis of the inertial coordinate system.

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