Optimal guidance method under weak overload capacity constraint

Abstract

The invention discloses an optimal guidance method under weak overload capacity constraint, and the method comprises the steps: building a relative coordinate system with a maneuvering target as an original point, and reducing the nonlinear degree of kinematics; on the basis of a normal optimal interception method obtained by solving in a relative coordinate system, designing a variable coefficient-containing offset item considering overload capacity limitation by establishing an optimal control problem; the whole-course autonomous operation is realized, and the precise interception of the high-maneuverability moving target is realized on the premise that the self overload capacity and the target maneuverability are vulnerable.

Description

Technical Field

[0001] The present invention relates to the field of UAV control, and particularly to an optimal guidance method under the constraint of weak overload capacity. Background Art

[0002] With the improvement of the level of intelligence, unmanned aerial vehicles (UAVs) have played an important role in various fields due to their low cost, flexible deployment, and strong operability. However, due to the characteristics of low cost and small volume of UAVs, there will inevitably be certain physical characteristic limitations, such as speed limitation, field of view limitation of the carried optoelectronic pod, overload limitation, etc. Among them, the overload limitation plays an important role in the working effect of UAVs. This is because the control commands sent to UAVs are often acceleration commands, and traditional guidance laws can only meet the position constraints of reaching the target, without considering the overload ratio between itself and the target. When the acceleration command exceeds the overload limit of the UAV itself, especially when the overload capacity of the UAV is less than the maximum overload of the maneuvering target, it will seriously affect the terminal intersection accuracy, resulting in the escape of the target and the failure of the interception mission.

[0003] Therefore, there is a need for a method that can still ensure the accurate interception of highly maneuverable targets in a situation of parity or disadvantage. The existing methods for constraining overload commands are mainly divided into two methods: nonlinear control and linear control. Among them, nonlinear control is mainly based on sliding mode control, constructing a sliding mode surface and reaching law related to acceleration constraints, introducing a saturation function in second-order dynamics, and proving its stability and convergence based on the Lyapunov function. However, the above nonlinear method is prone to waste of guidance energy due to the lack of performance indicators. In the linear control method, an energy consumption optimization function containing weight coefficients is constructed, and the optimal guidance law with the miss distance as the terminal constraint is deduced 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 UAV's own overload, and do not constrain the overload ratio between the two sides, and often require the overload capacity of our mission UAV to be better than the maximum maneuver of the target.

[0004] For the above reasons, the inventor of the present invention has conducted in-depth research on the guidance and interception problem of intercepting highly maneuverable targets in a situation of weak overload capacity, in order to design an optimal guidance method under the constraint of weak overload capacity. Summary of the Invention

[0005] To overcome the above problems, the present inventor has conducted intensive research and designed an optimal guidance method under the constraint of weak overload capacity. In this method, a relative coordinate system with the maneuvering target as the origin is established to reduce the degree of kinematic nonlinearity. Based on the normal optimal interception method obtained by solving in the relative coordinate system, an optimal control problem is established, and a variable coefficient bias term considering the overload capacity limitation is designed to achieve full-autonomous operation. Under the premise of its own overload capacity and the weakness of the target maneuvering ability, it can achieve precise interception of highly maneuvering moving targets, thus completing the present invention.

[0006] Specifically, the object of the present invention is to provide an optimal guidance method under the constraint of weak overload capacity, and the method includes the following steps:

[0007] S1. According to the motion state information of the target and the maximum acceleration of the mission UAV itself, judge whether the initial velocity direction of the mission UAV meets the interception requirement through the initial zero-control miss distance. If the initial velocity direction of the mission UAV meets the interception requirement, release the mission UAV.

[0008] S2. Obtain the motion state information of the target in real time through the optoelectronic pod carried on the mission UAV.

[0009] S3. Obtain the velocity and acceleration of the target in real time according to the motion state information of the target.

[0010] S4. Based on minimizing the control consumption, obtain the normal guidance command with time-varying coefficients in real time. Through this normal guidance command, control the mission UAV to achieve precise intersection with the maneuvering target under the premise of meeting the equal potential overload limit.

[0011] Among them, before executing S2, photograph the target through the optoelectronic pod carried on the mission UAV to obtain continuous images containing the target; obtain the state estimation of the target through the image pixel deviation and angle information, and continuously observe the target by controlling the optoelectronic pod with the angular rate command.

[0012] Among them, in S2, the motion state information of the target includes: the line-of-sight angle q of the target relative to the mission UAV, and the relative distance r between the mission UAV and the target.

[0013] Among them, in S4, the normal guidance command a M is the acceleration command perpendicular to the velocity direction of the mission UAV, and is obtained through the following formula (1):

[0014]

[0015] Among them, a ⊥ represents the acceleration perpendicular to the relative velocity direction between the mission UAV and the target in the relative coordinate system, that is, the relative acceleration command;

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

[0017] γ R represents 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 represents the velocity angle of the target;

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

[0020] Among them, the relative acceleration command a ⊥ is obtained in real time through the following formula (two):

[0021]

[0022] Among them, N represents the guidance coefficient;

[0023] ZEM represents the zero-effort miss;

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

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

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

[0027] a Mc represents the acceleration command of the mission UAV obtained by predictive solution.

[0028] Among them, the zero-effort miss ZEM is obtained in real time through the following formula (three):

[0029]

[0030] Among them, the acceleration command a of the mission UAV obtained by predictive solution Mc is obtained in real time through the following formula (four):

[0031]

[0032] Among them, in S1, when the following formula (five) holds, the initial velocity direction of the mission UAV meets the interception requirement;

[0033]

[0034] Among them, ZEM0 represents the zero-effort miss at the initial moment;

[0035] a M,maxRepresents the maximum acceleration of the mission UAV itself;

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

[0037] r0 represents the relative distance between the mission UAV and the target at the initial moment;

[0038] N represents the guidance coefficient;

[0039] V R Represents the relative velocity between the mission UAV and the target.

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

[0041] ZEM0 = -r0 sin(q0 - γR0) (six)

[0042] Among them, r0 represents the relative distance between the mission UAV and the target at the initial moment;

[0043] q0 represents the line-of-sight angle of the target relative to the mission UAV at the initial moment;

[0044] γ R0 Represents the angle between the relative velocity between the mission UAV and the target at the initial moment and the X-axis of the inertial coordinate system.

[0045] The beneficial effects of the present invention include:

[0046] (1) According to an optimal guidance method under weak overload capacity constraints provided by the present invention, this method uses the machine vision technology of the airborne optoelectronic pod to identify and track space targets. Compared with detection devices such as radar and vehicle-mounted optoelectronics, it has high precision, strong intuitiveness, low cost, and is not affected by clutter interference;

[0047] (2) According to an optimal guidance method under weak overload capacity constraints provided by the present invention, this method can estimate based on the target motion and perform autonomous navigation accordingly; combined with a flexible and reliable mission execution system, it has the ability to quickly and stably track non-cooperative maneuvering targets in the shortest time, enabling a mission UAV with a disadvantaged overload capacity to intercept high-maneuver targets and achieve optimal guidance interception under acceleration limit conditions;

[0048] (3) According to an optimal guidance method under weak overload capacity constraints provided by the present invention, in this method, it is judged before the aircraft takes off whether the initial velocity direction of the mission UAV can meet the interception requirements under overload constraints. If not, continue to adjust the initial velocity direction of the mission UAV or the overload capacity of the mission UAV. If it meets, release the mission UAV. Description of the Drawings

[0049] Figure 1 Shows the overall logic diagram of the optimal interception guidance method under the constraint of weak overload capacity according to a preferred embodiment of the present invention;

[0050] Figure 2 Shows the movement trajectories of the highly maneuverable target and the mission UAV in the experimental example of the present invention;

[0051] Figure 3 Shows the graph of the relative distance between the mission UAV and the highly maneuverable target changing with time in the experimental example of the present invention;

[0052] Figure 4 Shows the acceleration change curve of the mission UAV with a given acceleration limit in the experimental example of the present invention. Detailed implementation manners

[0053] The present invention will be further described in detail below with reference to the drawings and embodiments. Through these descriptions, the features and advantages of the present invention will become more clear and definite.

[0054] The special term "exemplary" here means "serving as an example, embodiment or illustrative". Any embodiment described as "exemplary" here does not have to be construed as superior to or better than other embodiments. Although various aspects of the embodiments are shown in the drawings, the drawings do not have to be drawn to scale unless otherwise specified.

[0055] The present invention provides an optimal guidance method under the constraint of weak overload capacity, as Figure 1 shown in, the method includes the following steps,

[0056] S1. According to the motion state information of the target and the maximum acceleration of the mission UAV itself, judge whether the initial velocity direction of the mission UAV meets the interception requirement through the initial zero-control miss distance. If the initial velocity direction of the mission UAV meets the interception requirement, release the mission UAV;

[0057] S2. Obtain the motion state information of the target in real time through the optoelectronic pod carried on the mission UAV;

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

[0059] S4. Based on minimizing the control consumption, obtain the normal guidance command with time-varying coefficients in real time, and control the mission UAV through this normal guidance command to achieve precise intersection with the maneuvering target on the premise of meeting the equal potential overload limit.

[0060] Preferably, the mission UAV is preferably selected as a rotary-wing UAV, specifically a UAV with more than four propellers; the acceleration command obtained in real time is input into the rotor control system of the mission UAV, and the rotor control system can adjust the rotational speed of the rotor propellers according to the input acceleration command. The change in rotational speed causes a change in the lift of the rotor, thereby controlling the attitude and position of the mission UAV.

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

[0062] The speed, position, and acceleration information of the target in this application all refer to the speed and position information in the inertial system. The inertial system refers to a system with the centroid of the mission UAV as the origin, the geographical eastward 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 has the centroid of the target UAV as the origin, the geographical eastward 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 performing S2, the target is photographed by the optoelectronic pod carried on the mission UAV 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 optoelectronic pod is controlled to continuously observe the target through the angular rate command.

[0064] Specifically, the continuous images containing the target UAV are processed by the onboard machine vision algorithm to give the state estimation of the target UAV, which serves as the control information source for the optoelectronic pod on the multi-rotor aircraft.

[0065] Preferably, in this application, the existing onboard machine vision algorithm is used to track the target in real time and calculate the position of the UAV relative to the camera in real time.

[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 mission UAV, and the relative distance r between the mission UAV and the target.

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

[0068] The predicted values of the motion information can all be obtained through the existing Kalman filter algorithm.

[0069] In a preferred embodiment, in S4, the normal guidance command a M is the acceleration command perpendicular to the velocity direction of the mission UAV in the inertial coordinate system and is obtained through the following formula (1):

[0070]

[0071] Among them, a ⊥ represents the acceleration perpendicular to the relative velocity direction between the mission UAV and the target in the relative coordinate system, that is, 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 mission UAV and the target and the X-axis of the inertial coordinate system;

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

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

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

[0077]

[0078] where N represents the guidance coefficient, preferably a constant, and more preferably takes a value of 4;

[0079] ZEM represents the zero-effort miss;

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

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

[0082] C and θ each independently represent the convergence coefficients of the optimal control problem. Preferably, the value of C is 3 to 5, and more preferably takes a value of 4; preferably, the value of θ is 0.1;

[0083] a Mc represents the acceleration command of the mission UAV obtained by predictive solution.

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

[0085]

[0086] Preferably, the acceleration command a of the mission UAV obtained by predictive solution Mc is obtained in real time through the following formula (four):

[0087]

[0088] In a preferred embodiment, in S1, when the following formula (V) holds, the initial velocity direction of the mission drone meets the interception requirement;

[0089]

[0090] where ZEM0 represents the zero-effort miss at the initial moment;

[0091] a M,max represents the maximum acceleration of the mission drone itself;

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

[0093] r0 represents the relative distance between the mission drone and the target at the initial moment;

[0094] N represents the guidance coefficient;

[0095] V R represents the relative velocity between the mission drone and the target.

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

[0097] ZEM0 = -r0 sin(q0 - γR0) (VI)

[0098] where, r0 represents the relative distance between the mission drone and the target at the initial moment;

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

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

[0101] Although it is the optimal solution that the takeoff direction of the aircraft points to the target, in the actual operation process, it is difficult to ensure that the takeoff direction points to the target in any case. Based on this, in this application, it is judged whether the initial velocity direction of the mission drone can meet the interception requirement before the aircraft takes off. If not, the initial velocity direction of the mission drone or the overload capacity of the mission drone is adjusted continuously. If it meets the requirement, the mission drone is released; by making a pre-judgment before the mission drone takes off, the interception effect of the mission drone can be further improved.

[0102] Experimental example

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

[0104] The initial velocity V of the target UAV t0 = 300 m / s;

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

[0106]

[0107] where, g = 9.8 m / s 2 ;

[0108] The initial position, initial velocity and overload limit of the mission UAV are shown in the following table

[0109]

[0110]

[0111] Judge that the following formula (V) holds, and launch the mission UAV;

[0112]

[0113] where, ZEM0 represents the zero-effort miss at the initial moment;

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

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

[0116] r0 represents the relative distance between the mission UAV and the target at the initial moment;

[0117] N represents the guidance coefficient;

[0118] V R represents the relative velocity between the mission UAV and the target.

[0119] The zero-effort miss ZEM0 at the initial moment is obtained by the following formula (VI):

[0120] ZEM0 = -r0 sin(q0 - γ R0 )(VI)

[0121] where, r0 represents the relative distance between the mission UAV and the target at the initial moment;

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

[0123] γ R0 represents the angle between the relative velocity between the mission UAV and the target and the X-axis of the inertial coordinate system at the initial moment.

[0124] Tracking the target through an optoelectronic pod, and calculating the guidance command of the mission UAV in real time according to the following formulas (1) and (2):

[0125]

[0126] Among them, N represents the guidance coefficient, and the value is 4;

[0127] ZEM represents the zero-effort miss;

[0128] r represents the relative distance between the mission UAV and the target;

[0129] V R represents the relative velocity between the mission UAV and the target;

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

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

[0132] a Mc represents the acceleration command of the mission UAV obtained by predictive solution;

[0133] ZEM can be obtained in real time according to the following formula (3)

[0134]

[0135] Among them, γ R represents the angle between the relative velocity between the mission UAV and the target and the X-axis of the inertial coordinate system;

[0136] γ M is the velocity angle of the mission UAV;

[0137] a Mc is obtained in real time through the following formula (4):

[0138]

[0139] Among them, γ T represents the velocity angle of the target;

[0140] The motion trajectories of the mission UAV and the highly maneuverable target are as shown in Figure 2 As can be seen from Figure 2 , an optimal guidance method under weak overload capacity constraints provided by this application can successfully intercept highly maneuverable targets.

[0141] The relative distance between the mission UAV and the highly maneuverable target changes with time as shown in Figure 3 As shown in. Combining Figure 2 , Figure 3It can be seen that the optimal guidance method provided by this application under the constraint of weak overload capacity can enable a disadvantageous overload-constrained unmanned aerial vehicle to hit a maneuvering target and meet the miss distance requirement that the relative distance from the target is less than 0.3 m.

[0142] Figure 4 The acceleration change curve of a mission unmanned aerial vehicle with a given acceleration limit is shown. From Figure 4 It can be seen that the optimal guidance method provided by this application under the constraint of weak overload capacity can meet the requirement of accurately intercepting a highly maneuvering moving target on the premise of the weakness of its own overload capacity and the target maneuvering capacity.

[0143] The present invention has been described in combination with preferred embodiments above, but these embodiments are only exemplary and only serve an illustrative role. On this basis, various substitutions and improvements can be made to the present invention, and these all fall within the protection scope of the present invention.

Claims

1. An optimal guidance method under weak overload capacity constraint, characterized in that: The method comprises the following steps: S1, according to the target's motion state information and the mission UAV's own maximum acceleration, judge whether the mission UAV's initial speed direction meets the interception requirement through the initial zero control miss amount, and release the mission UAV if the mission UAV's initial speed direction meets the interception requirement; S2, obtains the target's motion status information in real time through the optoelectronic pod carried by the mission UAV; S3, obtaining the speed and acceleration of the target in real time according to the motion state information of the target; S4, based on minimizing control consumption, obtains normal guidance instructions with time-varying coefficients in real time. Through this normal guidance instruction, the mission UAV is controlled to achieve precise intersection with the maneuvering target under the premise of meeting the equilibrium overload limit.

2. The optimal guidance method under weak overload capacity constraint according to claim 1, characterized in that: Before executing S2, the target is photographed by the optoelectronic pod carried by the mission UAV 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 optoelectronic pod is controlled to continuously observe the target through angular rate instructions.

3. The optimal guidance method under weak overload capacity constraint according to claim 1, characterized in that: In S2, the motion state information of the target includes: the sight angle q of the target relative to the mission UAV, and the relative distance r between the mission UAV and the target.

4. The optimal guidance method under weak overload capacity constraint according to claim 1, characterized in that: In S4, the normal guidance instruction a M is the acceleration command perpendicular to the speed direction of the mission UAV, obtained by the following formula (1): Among them, a ⊥ It represents the acceleration perpendicular to the relative velocity between the mission UAV and the target in the relative coordinate system, that is, the relative acceleration command; a T Indicates the acceleration of the target in the inertial coordinate system; γ R Represents the angle between the relative speed between the mission UAV and the target and the X-axis of the inertial coordinate system; γ T represents the velocity angle of the target; γ M Represents the velocity angle of the mission UAV.

5. The optimal guidance method under weak overload capacity constraint according to claim 4, characterized in that: The relative acceleration command a ⊥ Obtained in real time through the following formula (II): Where N represents the guidance coefficient; ZEM stands for zero miss magnitude; r represents the relative distance between the mission UAV and the target; V R Indicates the relative speed between the mission UAV and the target; C and θ independently represent the convergence coefficient of the optimal control problem; a Mc It represents the acceleration command of the mission UAV obtained by prediction.

6. The optimal guidance method under weak overload capacity constraint according to claim 5, characterized in that: The zero control miss amount ZEM is obtained in real time by the following formula (III):

7. The optimal guidance method under weak overload capacity constraint according to claim 5, characterized in that: The predicted mission UAV acceleration command a Mc Obtained in real time through the following formula (IV):

8. The optimal guidance method under weak overload capacity constraint according to claim 1, characterized in that: In S1, when the following formula (V) holds true, the initial speed direction of the mission UAV meets the interception requirements; Among them, ZEM0 represents the zero control miss distance at the initial moment; a M,max Indicates the maximum acceleration of the mission drone itself; a T,max is the target maximum acceleration; r0 represents the relative distance between the mission UAV and the target at the initial moment; N represents the guidance coefficient; V R Indicates the relative speed between the mission UAV and the target.

9. The optimal guidance method under weak overload capacity constraint according to claim 8, characterized in that: The zero control miss amount ZEM0 at the initial moment is obtained by the following formula (VI): ZEM0=-r0 sin(q0-γR0)(vi) Among them, r0 represents the relative distance between the mission UAV and the target at the initial moment; q0 represents the sight angle of the target relative to the mission UAV at the initial moment; γ R0 It represents the angle between the relative speed between the mission UAV and the target and the X-axis of the inertial coordinate system at the initial moment.

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