CN117389322B - Unmanned aerial vehicle control method - Google Patents
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Abstract
The invention provides an unmanned aerial vehicle control method, which comprises a horn flick control algorithm and a high-speed dive control strategy. The invention has the beneficial effects that: the attitude of the aircraft can be effectively stabilized, and the time for unfolding the arm body of the unmanned aerial vehicle is reasonable, so that the flight control can conveniently control the attitude of the aircraft; the dive speed of the multi-rotor unmanned aerial vehicle can be increased on the premise that additional equipment is not added, and the action speed of the unmanned aerial vehicle is improved.
Description
Technical Field
The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to an unmanned aerial vehicle control method.
Background
Along with the perfection and wide use of unmanned aerial vehicle technology in recent years, unmanned aerial vehicle plays an increasingly larger role in various fields of society, and unmanned aerial vehicle especially many rotor unmanned aerial vehicle also increasingly shows its advantages that are convenient and easy to use: the functions of a single complete comprehensive platform are integrated into zero, the functions are dispersed into a large number of low-cost multi-rotor unmanned aerial vehicle platforms with single functions, and the multiplication benefit of the system enables the unmanned aerial vehicle group to have the capability of far exceeding the single comprehensive platform; secondly, the cost of the multi-rotor platform is lower than the cost of the effective fee exchange ratio, and when the actual task is carried out, the cost of tens of times or hundreds of times of cost of a large number of unmanned aerial vehicle individuals is consumed for defense.
However, the current control or regulation system of the miniature multi-rotor unmanned aerial vehicle has severe requirements on a take-off field in the take-off process, and the control or regulation system of the miniature multi-rotor unmanned aerial vehicle is difficult to realize high-speed dive through monitoring and controlling an unfolding motor in the task process, so that the task airspace deployment and task realization at any position are difficult to realize. Therefore, a control method for the flying and autonomous flight of the micro unmanned aerial vehicle is urgently needed to solve the current problem.
Disclosure of Invention
In view of the foregoing, the present invention is directed to a control method of an unmanned aerial vehicle, so as to solve at least one of the problems in the prior art.
In order to achieve the above purpose, the technical scheme of the invention is realized as follows:
the unmanned aerial vehicle control method comprises a high-speed dive control strategy, which is used for controlling a high-speed dive to a target when an ejection unmanned aerial vehicle executes a task, and comprises the following steps of:
b3, establishing a coordinate system by using the unmanned aerial vehicle body, and solving the coordinates of the target point in the body coordinate system to obtain a target coordinate in the body coordinate system;
b4, solving course angle YAW of unmanned aerial vehicle a Unmanned aerial vehicle pitch angle PIT a Unmanned aerial vehicle ROLL angle ROLL a The method comprises the steps of carrying out a first treatment on the surface of the Unmanned plane heading angle YAW a Unmanned aerial vehicle pitch angle PIT a Unmanned aerial vehicle ROLL angle ROLL a The attitude angles of the unmanned aerial vehicle are respectively;
b5, establishing a coordinate system with the earth, and solving azimuth angle YAW of the target point relative to the geometric center of the unmanned aerial vehicle under the earth coordinate system by combining the target coordinate under the body coordinate system in the step B3 with the attitude angle of the unmanned aerial vehicle obtained in the step B4 t Pit of pitch angle t ；
B6, establishing a stress decomposition relation of the unmanned aerial vehicle, and synchronously decomposing wind resistance and gravity borne by the unmanned aerial vehicle to the speed direction of the unmanned aerial vehicle and the vertical direction of the speed direction of the unmanned aerial vehicle;
b7, establishing a trajectory equation of the unmanned aerial vehicle falling under no power according to the stress of the unmanned aerial vehicle, and calculating the acceleration direction and the final speed of the unmanned aerial vehicle;
b8, the unmanned aerial vehicle carries out acceleration and direction adjustment according to the acceleration direction and the final speed which are calculated by the track equation established in the step B7, and the unmanned aerial vehicle power is closed to enter a free falling mode after the speed and the direction are adjusted in place;
b9, obtaining actual track data in the free falling mode movement;
b10, selecting a time interval T, discretizing an ideal track according to the time interval T, and comparing the actual track data in the step B9 with a route calculated by an ideal track equation; enabling the power of the unmanned aerial vehicle to carry out track correction; until the target actual position is reached.
Further, the step B3 is preceded by steps B1 and B2;
b1, collecting azimuth angle YAW of miniature nacelle p Pit pitch angle p ；
B2, acquiring the off-target quantity of a target relative to the center of the image, wherein the transverse direction is x, and the vertical direction is y;
solving the coordinates of the target point in the machine body coordinate system by utilizing the results acquired in the step B1 and the step B2;
in step B4, solving the unmanned aerial vehicle course angle YAW by using Kalman filtering a ；
In the step B9, the accelerometer and the barometer are filtered by a filtering algorithm to obtain actual track data;
in the step B10, when the deviation of the height direction exceeds 2m and the deviation of the transverse direction and the longitudinal direction exceeds 0.5m, the unmanned aerial vehicle power is started to carry out track correction.
Further, the unmanned aerial vehicle is an catapult-assisted take-off multi-rotor unmanned aerial vehicle, and further comprises a horn pop-up control algorithm which is a last step task of a high-speed dive control strategy and is used for controlling the catapult-assisted unmanned aerial vehicle to pop up a horn body in a spin state, and the method comprises the following steps:
a3, establishing a matching relationship between the air resistance of the arm body and the centrifugal force;
a5, carrying out low-pass filtering on the acceleration of each axis by using a low-pass filtering model;
a6, filtering the angular velocity values of the shafts by using a notch filter;
a7, substituting the angular velocity filtered in the step A6 into a relation formula of centrifugal force and air resistance established in the step A3, and continuously solving the centrifugal force and the air resistance of the arm body; taking the maximum strength which can be born by the material of the arm body as a limit value, gradually releasing the opening angle of the arm body;
a8, establishing a perception model aiming at the unmanned aerial vehicle spin state, judging the current unmanned aerial vehicle state, and ensuring that the unmanned aerial vehicle is in a flight control controllable state.
Further, the step A3 is preceded by steps A1 and A2;
a1, establishing a matching relationship between the exposed area of the unmanned aerial vehicle arm body and the unfolding angle of the unmanned aerial vehicle arm body;
a2, establishing a matching relation between the rotation linear speed of the exposed area of the horn body and the unfolding angle of the horn body;
utilizing the results of the step A1 and the step A2 to establish a matching relationship between the air resistance of the arm body and the centrifugal force;
step A4 is also included between the step A3 and the step A5;
a4, acquiring angular velocity values of all the shafts of the unmanned aerial vehicle body by using a gyroscope, and acquiring acceleration values of all the shafts of the unmanned aerial vehicle body by using an accelerometer.
Further, in step A8, the current unmanned aerial vehicle state is determined from the two angle algorithm synthesis of the first method and the second method, and the first method includes:
a81a, setting the output angular velocity of the gyroscope to be Gi= [ g ] xi ,g yi ,g zi ]T, i=1, 2,..k, accelerometer output acceleration is a= [ a xi ,a yi ,a zi ]T,i＝1,2,...k；
Then the resultant angular velocity of the system isThe combined acceleration is；
A82a, setting the current state of the unmanned aerial vehicle to be delta, wherein delta=1 indicates that the system is in spin; δ=0 represents that the system is in a static or uniform motion state, and the system motion state judgment rule is as follows:
if it isAnd->Judging that the system is in a static or uniform motion state delta=0;
if it isOr->The system is in dynamic delta=1, n is the sampling number;
in step A8, the second method includes:
establishing a machine body coordinate system, and calculating the roll angle of a transverse roller under the machine body coordinate system by using a complementary filtering algorithm, wherein the method comprises the following steps:
a81b, setting the roll angle as R and the roll angular velocity as Gyro R The roll acceleration is Acc R ；
A82b sets the weighting coefficient of the complementary filter to lambda and the time constant to lambdaThe running period is d t Then；
A83b, the roll angle is；
A84b, the roll angle change rate K is；
The comprehensive judgment mode is as follows: if and only if delta=1 in method one and R in method two k When the change rate K of the unmanned aerial vehicle is smaller than 0.1, judging that the unmanned aerial vehicle is in a non-spinning state at the moment; at the moment, the flight control starts the power motor of the unmanned aerial vehicle to stabilize the attitude of the aircraft, and the next task is carried out.
Further, in step A1, establishing a matching relationship between the exposed area of the unmanned aerial vehicle horn body and the deployment angle of the horn body includes:
the width of the horn body is set to be b, the total length of the horn body is L, the distance between the rotating shaft and the unmanned aerial vehicle body is set to be b1, and the unfolding angle of the horn body is set to beThe exposed length of the arm body is L1, and the exposed area A of the arm body is;
the approximation can be obtained:
；
the exposed area is as follows:
。
further, in step A2, establishing a matching relationship between the rotation linear speed of the exposed area of the horn body and the deployment angle of the horn body includes:
setting the distance between the rotating shaft and the axis of the unmanned aerial vehicle body as b 2 The linear speed of the top end of the exposed area of the horn body is V, and the distance between the top end of the horn body and the axis of the unmanned aerial vehicle body is b 3 The rotation angular velocity of the unmanned plane body is omega;
the approximation can be obtained:
；
；
wherein: l is the total length of the arm body.
Further, in step A3, establishing a matching relationship between the air resistance of the horn body and the centrifugal force includes:
setting the centrifugal force at the power motor of the horn body as F, setting the air resistance received by the side surface of the horn body as F, and setting the weight of the horn body as m;
the method can obtain:
；
；
wherein:is the coefficient of air resistance and is used for the air resistance,is air density, omega is rotation angular velocity of unmanned aerial vehicle body, b is width of the horn body, b 2 For the distance between the rotating shaft and the axis of the unmanned aerial vehicle body, A is the exposed area of the horn body, L is the total length of the horn body, L1 is the exposed length of the horn body, and V is the linear speed of the top end of the exposed area of the horn body.
Further, in step A6, filtering the signal acquired by the gyroscope with a notch filter includes:
the transfer function of the continuous system quadratic notch filter is as follows:
；
wherein,is notch width, unit rad/s; />The unit rad/s is the notch center frequency, and s is the input signal frequency;
a62, discretizing the step A61 by adopting a pole-zero matching method, wherein the formula is as follows:
；
wherein: j is an imaginary number and is represented by the imaginary number,is notch width, unit rad/s;for notch centre frequency, singlyThe number of bits of rad/s,is a constant value, and is used for the treatment of the skin,；、are all the poles of the notch filter,，the method comprises the steps of carrying out a first treatment on the surface of the Has the following components，，The value is represented by the pole value part 1,a pole value part 2, s is the frequency of the input signal;
a63, the zero pole in the complex frequency domain is corresponding to the z domain, and the corresponding relation of the ith zero pole is as follows:
；
wherein:for an input frequency in a polar coordinate system,in order to discretize the sampling time of the sample,is straight atAn input frequency in an angular coordinate system;
a64, substituting the zero pole of the step A63 into the formula of the step A62, and obtaining an equation under the z domain by means of the Euler formula as follows:
；
wherein:in order to replace the factor(s),，T s for the discretized sampling time, the unit s,in order to notch the center frequency of the wave,in order for the filter constant to be a constant,is the input frequency in the polar coordinate system;
a65, when the complex frequency domain is 0, the z domain is 1, namely；
A66, combining the step A65 with the step A62 and the step A64 to obtain:
；
the simplification can be obtained:
；
wherein:in order for the filter constant to be a constant,in order to replace the factor(s),the value is represented by the pole value part 2,in order to notch the center frequency of the wave,in order to discretize the sampling time of the sample,is the input frequency in the polar coordinate system;
a67, integrating the step A64 to obtain:
；
using variable substitution to make available:
；
wherein:，/>，/>，/>，；
the discretization differential equation of the notch filter based on the zero pole matching method is obtained by the method:
；
wherein: y (k) is the output quantity of the notch filter, y (k-1) is the last output quantity of the notch filter, and y (k-2) is the last two output quantities of the notch filter; gamma (k) is the input of the notch filter, gamma (k-1) is the last input of the notch filter, gamma (k-2) is the last two inputs of the notch filter,、、、b 1 、b 2 all are parameters of the digital notch filter;
and carrying out data filtering iteration by using a discretized differential equation.
Further, in step B9, the filtering algorithm includes:
b91, establishing a mapping relation between pressure and height:
；
wherein: h represents altitude, the unit is m, P is the atmospheric pressure value of the current position acquired by the atmospheric pressure sensor, and P 0 Is a standard atmospheric pressure value;
and B92, correcting the altitude value converted in the step B91, wherein the correction formula is as follows:
summing formula of altitude value H for the first N times in static state under initialization, N is number of altitude values, H sum Is the sum of the N altitude values:
；
formula for averaging N times of initial data, H average The average value is:
；
corrected relative altitude value formula, where H relative The relative height value of the carrier with respect to the initial position is:
；
and B93, acquiring X, Y, Z triaxial acceleration values by an acceleration sensor, extracting motion characteristics by adopting a triaxial acceleration vector sum value, and calculating the triaxial acceleration vector sum as follows:
；
wherein: a is that XYZ Representing the value of the triaxial acceleration vector sum, A X Representing acceleration value in X-axis direction, A Y Representing the acceleration value in the Y-axis direction, A Z Representing the acceleration value in the Z-axis direction;
b94, data H relative And A XYZ Respectively carrying out low-pass filtering to remove data acquisition noise;
b95 value A of the triaxial acceleration vector sum XYZ Calculating the slope D A ；
B96, pair D A Setting a threshold value when D A If the height is greater than the threshold value, the barometer is considered to collect the height reliably when the height is changed, otherwise D is removed A Values.
Compared with the prior art, the unmanned aerial vehicle control method has the following advantages:
the unmanned aerial vehicle control method can effectively stabilize the attitude of the aircraft, and ensure that the moment for unfolding the arm body of the unmanned aerial vehicle is reasonable, so that the flight control can conveniently control the attitude of the aircraft; the dive speed of the multi-rotor unmanned aerial vehicle can be increased on the premise that additional equipment is not added, and the action speed of the unmanned aerial vehicle is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention. In the drawings:
fig. 1 is a schematic view of a unmanned aerial vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic view of an interior of four horn assemblies according to an embodiment of the present invention;
FIG. 3 is a schematic view of a horn assembly according to an embodiment of the present invention;
fig. 4 is a schematic diagram of parameters of the arm during deployment according to an embodiment of the present invention.
Reference numerals illustrate:
1. an unmanned aerial vehicle body; 2. a horn body; 3. a rotation shaft; 4. a power motor; 5. and (5) unfolding the motor.
Detailed Description
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", etc. may explicitly or implicitly include one or more such feature. In the description of the present invention, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art in a specific case.
The invention will be described in detail below with reference to the drawings in connection with embodiments.
As shown in fig. 1 to 4, the unmanned aerial vehicle control method comprises a horn flick control algorithm and a high-speed dive control strategy;
before the catapult-assisted take-off of the unmanned aerial vehicle, four horn assemblies of the unmanned aerial vehicle are contained in the unmanned aerial vehicle body 1 with a cylindrical structure. Wherein, horn subassembly includes horn body 2, rotation axis 3, power motor 4, expandes motor 5, and rotation axis 3, expandes motor 5 and set up in horn body 2 top, and power motor 4 sets up in horn body 2 bottom, for solving the unmanned aerial vehicle in-process that launches and take off can realize the flight of furthest distance, therefore need guarantee that unmanned aerial vehicle possesses certain spin speed along the axis of unmanned aerial vehicle organism 1 (unmanned aerial vehicle organism 1's length direction) when the transmission. However, due to the spin speed and the high spin speed, the horn body 2 is destroyed by air resistance and centrifugal force if the spin speed is still very high when the horn body 2 is deployed. Therefore, an unmanned aerial vehicle active rotation reducing algorithm, namely a horn flick control algorithm is required to be designed, and the method specifically comprises the following steps:
1. establishing a matching relationship between the exposed area of the unmanned aerial vehicle arm body (namely the windward area when the arm body 2 is unfolded from the unmanned aerial vehicle body 1) and the unfolding angle of the arm body 2;
the width of the arm body 2 is set as b, the total length is L, the width distance between the rotating shaft 3 and the unmanned aerial vehicle body 1 is set as b1, and the unfolding angle of the arm body 2 is set asThe exposed length of the arm body 2 is L1, and the exposed area A of the arm body 2 is;
the approximation can be obtained:
；
the exposed area is as follows:
。
2. establishing a matching relation between the rotation linear speed of the exposed area of the horn body 2 and the unfolding angle of the horn body 2:
setting the distance between the rotating shaft 3 and the axis of the unmanned plane body 1 as b 2 The linear speed of the top end of the exposed area of the horn body 2 is V, and the axial distance between the top end of the horn body 2 and the unmanned aerial vehicle body 1 is b 3 The rotational angular velocity of the unmanned aerial vehicle body 1 is。
The approximation can be obtained:
；
。
3. establishing a matching relation between the air resistance and the centrifugal force of the horn body 2:
setting the centrifugal force at the power motor 4 of the horn body 2 as F, the air resistance received by the side surface of the horn body 2 as F, and the weight of the horn body 2 as m;
the method can obtain:
；
。
4. the angular velocity value and the acceleration value of each shaft of the unmanned aerial vehicle body 1 are collected by using a gyroscope and an accelerometer.
5. And (3) carrying out low-pass filtering on the acceleration of each axis acquired by the accelerometer, wherein a low-pass filtering model is as follows:
；
wherein K is a filter coefficient, K=dT/T, K is between 0 and 1, dT is an operation step length, and T is a time constant; u is the input signal; y is the output signal.
6. The signals collected by the gyroscope are filtered by a notch filter, and the process is as follows:
1) The continuous system quadratic notch filter transfer function is as follows:
；
wherein the method comprises the steps ofIs notch width, unit rad/s; />Is the notch center frequency, in rad/s;
2) The above method is discretized by adopting a zero pole matching method, and is expressed as follows:
；
wherein the method comprises the steps of；/>For the pole of the notch filter there is +.>，；
3) The zero poles in the complex frequency domain are corresponding to the z domain, and the ith zero pole corresponds to:
；
4) Substituting the zero pole of the step 3) into the formula of the step 2), and obtaining the following formula in the z domain by means of the Euler formula:
；
wherein the method comprises the steps of，T s The unit s is discretized sampling time;
5) When the complex frequency domain is 0, the z domain is 1, i.e；
6) Combining step 5) with the above:
；
the simplification can be obtained:
；
7) Integrating the step 4) can obtain:
；
using variable substitution to make available:
；
wherein:，/>，/>，/>，；
the discretization differential equation of the notch filter based on the pole-zero matching method can be obtained by the method:
；
and carrying out data filtering iteration by using the formula.
7. And substituting the angular velocity filtered in the step 6 into the centrifugal force and air resistance relation formula established in the step 3 to continuously solve the centrifugal force and air resistance of the arm body 2. Taking the maximum strength which can be born by the material of the arm body 2 as a limit value, gradually releasing the opening angle of the arm body 2.
8. A perception model is established for the spinning state of the unmanned aerial vehicle, and the attitude of the unmanned aerial vehicle in the air is critical to the control of the flight control, so that the current unmanned aerial vehicle state needs to be calculated and judged simultaneously from two different angle algorithms, and the unmanned aerial vehicle is ensured to be in the flight control controllable state. The following are two calculation methods:
the method comprises the following steps:
1) A81a, setting the output angular velocity of the gyroscope to be Gi= [ g ] xi ,g yi ,g zi ]T, i=1, 2,..k, accelerometer output acceleration is a= [ a xi ,a yi ,a zi ]T,i＝1,2,...k；
Then the resultant angular velocity of the system isThe combined acceleration is；
2) Setting the current state of the unmanned aerial vehicle as delta, wherein delta=1 indicates that the system is in spin; δ=0 represents that the system is in a static or uniform motion state, and the system motion state judgment rule is as follows:
if it isAnd->Judging that the system is in a static or uniform motion state delta=0;
if it isOr->The system is in dynamic delta=1 and n is the number of samples.
The second method is as follows:
since the unmanned aerial vehicle is in a state of spinning along the unmanned aerial vehicle body 1, after the horn body 2 is unfolded, the spin speed of the unmanned aerial vehicle body 1 can be perceived by calculating the change rate of the attitude angle.
1) Establishing a machine body coordinate system, and calculating the roll angle of a transverse rolling shaft under the machine body coordinate system by using a complementary filtering algorithm;
2) Setting the roll angle as R and the roll angular speed as Gyro R The roll acceleration is Acc R ；
3) Setting the weighting coefficient of the complementary filter as lambda, the time constant as tau and the running period as d t Then；
4) The roll angle is；
5) The change rate K of the roll angle is。
Because the first and second methods are to determine whether the drone is spinning from two angles, if and only if delta=1 in the first method and R in the second method k When the change rate K of (2) is less than 0.1, it is determined that the unmanned aerial vehicle is already in a non-spinning state at this time. At the moment, the flight control timely starts the power motor 4 of the unmanned aerial vehicle to stabilize the attitude of the aircraft, and the next task is carried out.
As shown in fig. 3 and 4, the directly controlled object of the horn pop-up control algorithm is a deployment motor 5 of the horn body 2, and the algorithm achieves the purpose of controlling the deployment of the horn body 2 by controlling the deployment motor 5.
After the unmanned aerial vehicle arm body 2 is unfolded and the flight control can stabilize the attitude of the airplane, target information including azimuth pitching angle and image off-target amount is provided by the miniature nacelle. And according to the azimuth pitch angle of the miniature nacelle and the image miss distance, calculating the azimuth pitch angle of the actual target relative to the unmanned aerial vehicle. The unmanned aerial vehicle is characterized in that the unmanned aerial vehicle needs to reach a target point at a high speed, but the upper speed limit of the unmanned aerial vehicle is lower than that of free falling body movement when the unmanned aerial vehicle is subjected to high-speed dive due to the inherent characteristics of the multi-rotor unmanned aerial vehicle, so that a control strategy is designed to provide the maximum dive speed for the unmanned aerial vehicle in a free falling body movement mode on the premise of ensuring accurate reaching of the target point. Namely a high-speed dive control strategy, which comprises the following specific steps:
1. collecting azimuth angle YAW of miniature nacelle p Pit pitch angle p ；
2. Collecting the off-target quantity of a target relative to the center of an image, wherein the transverse direction is x, and the vertical direction is y;
3. and establishing a coordinate system by using the unmanned aerial vehicle body 1, and solving the coordinates of the target point in the body coordinate system by using the information acquired in the first two steps.
4. Solving course angle YAW of unmanned aerial vehicle by Kalman filtering a Unmanned aerial vehicle pitch angle PIT a Unmanned aerial vehicle ROLL angle ROLL a 。
5. Establishing a coordinate system with the earth, solving azimuth angle YAW of the target point in the earth coordinate system by combining target coordinates in the machine body coordinate system with the attitude angle of the unmanned aerial vehicle t Pit of pitch angle t 。
6. And establishing a stress decomposition relation of the unmanned aerial vehicle, and synchronously decomposing wind resistance and gravity borne by the unmanned aerial vehicle to the speed direction of the unmanned aerial vehicle and the vertical direction of the speed direction of the unmanned aerial vehicle.
7. And establishing a trajectory equation of unmanned aerial vehicle falling under no power according to the stress of the unmanned aerial vehicle, and calculating a proper accelerating direction and a proper final speed of the unmanned aerial vehicle.
8. And (3) the unmanned aerial vehicle carries out acceleration and direction adjustment according to the acceleration direction and the final speed which are calculated by the falling track equation established in the last step, and the power of the unmanned aerial vehicle is closed to enter a free falling mode after the speed and the direction are adjusted in place.
9. In the free falling mode motion, the accelerometer and the barometer are filtered by using a filtering algorithm, and the unmanned aerial vehicle processor has limited computing capacity, so that a simple filtering algorithm needs to be designed, and then the altitude data is corrected by using correction conditions, so that actual track data is obtained by filtering.
The specific filtering algorithm is as follows:
1) Establishing a mapping relation between pressure and height:
；
wherein: h represents altitude, the unit is m, P is the atmospheric pressure value of the current position acquired by the atmospheric pressure sensor, and P 0 Is a standard atmospheric pressure value.
2) Correcting the converted altitude value, wherein the correction formula is as follows:
summing formula of altitude value H for the first N times in static state under initialization, N is number of altitude values, H sum Is the sum of the N altitude values:
；
formula for averaging N times of initial data, H average The average value is:
；
corrected relative altitude value formula, where H relative The relative height value of the carrier with respect to the initial position is:
；
3) The acceleration sensor has different mounting angles, and X, Y, Z triaxial acceleration values acquired by the sensor are different, so that the motion characteristics are extracted by adopting the value of triaxial acceleration vector sum, and the triaxial acceleration vector sum is calculated as follows:
；
in which A XYZ Representing the value of the triaxial acceleration vector sum, A X Representing acceleration value in X-axis direction, A Y Representing the acceleration value in the Y-axis direction, A Z Representing the acceleration value in the Z-axis direction;
4) For data H relative And A XYZ Respectively carrying out low-pass filtering to remove data acquisition noise;
5) Value A for the triaxial acceleration vector sum XYZ Calculating the slope D A ；
6) When D is A When the height change is larger than the threshold value, the barometer is considered to collect the height credibility, otherwise, the wild value is removed.
10. A time interval T is selected. And discretizing the ideal track according to the time interval T, and comparing the actual track with the route calculated by the ideal track equation. When the deviation is overlarge (the deviation of the height direction of the two is more than 2m and the deviation of the transverse direction and the longitudinal direction is more than 0.5 m), the unmanned aerial vehicle power is started in time to carry out track correction. Until the target actual position is reached.
The invention has the advantages that:
1. when the unmanned aerial vehicle spins, if the unmanned aerial vehicle expands the horn body 2, the ejection initial speed and then the ejection distance can be seriously influenced, and meanwhile, if the spinning speed is too high, the horn body 2 can be damaged, the attitude of the aircraft can be effectively stabilized, and meanwhile, the time for expanding the horn body 2 of the unmanned aerial vehicle is ensured to be reasonable, so that the attitude of the aircraft can be conveniently controlled by the flight control.
2. On the premise of not adding additional equipment, the dive speed of the multi-rotor unmanned aerial vehicle is increased, so that the action speed of the unmanned aerial vehicle is improved.
In example use, as shown in fig. 1 to 3, a 35mm catapulting unmanned product was used, with a horn body 2 of 5mm width and 55mm and 45mm length.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (9)
1. The unmanned aerial vehicle control method is characterized in that: comprises a horn flick control algorithm and a high-speed dive control strategy, wherein the high-speed dive control strategy is a task next to the horn flick control algorithm, the horn flick control algorithm is used for controlling the horn flick of the catapulting unmanned aerial vehicle in a spin state, the high-speed dive control strategy is used for controlling the high-speed dive of the catapulting unmanned aerial vehicle to a target when the catapulting unmanned aerial vehicle executes the task,
the horn flick control algorithm comprises the following steps:
a3, establishing a matching relationship between the air resistance of the arm body and the centrifugal force;
a5, carrying out low-pass filtering on the acceleration of each axis by using a low-pass filtering model;
a6, filtering the angular velocity values of the shafts by using a notch filter;
a7, substituting the angular velocity filtered in the step A6 into a relation formula of centrifugal force and air resistance established in the step A3, and continuously solving the centrifugal force and the air resistance of the arm body; taking the maximum strength which can be born by the material of the arm body as a limit value, gradually releasing the opening angle of the arm body;
a8, establishing a perception model aiming at the spinning state of the unmanned aerial vehicle, judging the current unmanned aerial vehicle state, and ensuring that the unmanned aerial vehicle is in a flight control controllable state;
the high-speed dive control strategy comprises the following steps:
b3, establishing a coordinate system by using the unmanned aerial vehicle body, and solving the coordinates of the target point in the body coordinate system to obtain a target coordinate in the body coordinate system;
b4, solving course angle YAW of unmanned aerial vehicle a Unmanned aerial vehicle pitch angle PIT a Unmanned aerial vehicle ROLL angle ROLL a The method comprises the steps of carrying out a first treatment on the surface of the Unmanned plane heading angle YAW a Unmanned aerial vehicle pitch angle PIT a Unmanned aerial vehicle ROLL angle ROLL a The attitude angles of the unmanned aerial vehicle are respectively;
b5, establishing a coordinate system with the earth, and solving azimuth angle YAW of the target point relative to the geometric center of the unmanned aerial vehicle under the earth coordinate system by combining the target coordinate under the body coordinate system in the step B3 with the attitude angle of the unmanned aerial vehicle obtained in the step B4 t Pit of pitch angle t ；
B6, establishing a stress decomposition relation of the unmanned aerial vehicle, and synchronously decomposing wind resistance and gravity borne by the unmanned aerial vehicle to the speed direction of the unmanned aerial vehicle and the vertical direction of the speed direction of the unmanned aerial vehicle;
b7, establishing a trajectory equation of the unmanned aerial vehicle falling under no power according to the stress of the unmanned aerial vehicle, and calculating the acceleration direction and the final speed of the unmanned aerial vehicle;
b8, the unmanned aerial vehicle carries out acceleration and direction adjustment according to the acceleration direction and the final speed which are calculated by the track equation established in the step B7, and the unmanned aerial vehicle power is closed to enter a free falling mode after the speed and the direction are adjusted in place;
b9, obtaining actual track data in the free falling mode movement;
b10, selecting a time interval T, discretizing an ideal track according to the time interval T, and comparing the actual track data in the step B9 with a route calculated by an ideal track equation; enabling the power of the unmanned aerial vehicle to carry out track correction; until the target actual position is reached.
2. The unmanned aerial vehicle control method of claim 1, wherein: the method also comprises the steps B1 and B2 before the step B3;
b1, collecting azimuth angle YAW of miniature nacelle p Pit pitch angle p ；
B2, acquiring the off-target quantity of a target relative to the center of the image, wherein the transverse direction is x, and the vertical direction is y;
solving the coordinates of the target point in the machine body coordinate system by utilizing the results acquired in the step B1 and the step B2; in step B4, solving the unmanned aerial vehicle course angle YAW by using Kalman filtering a ；
In the step B9, the accelerometer and the barometer are filtered by a filtering algorithm to obtain actual track data;
in step B10, when the deviation of the height direction of the actual track data and the height direction of the route calculated by the ideal track equation exceeds 2m and the deviation of the transverse direction and the longitudinal direction exceeds 0.5m, the unmanned aerial vehicle power is started to carry out track correction.
3. The unmanned aerial vehicle control method of claim 1, wherein: step A3 is preceded by steps A1 and A2;
a1, establishing a matching relationship between the exposed area of the unmanned aerial vehicle arm body and the unfolding angle of the unmanned aerial vehicle arm body;
a2, establishing a matching relation between the rotation linear speed of the exposed area of the horn body and the unfolding angle of the horn body;
utilizing the results of the step A1 and the step A2 to establish a matching relationship between the air resistance of the arm body and the centrifugal force; step A4 is also included between the step A3 and the step A5;
a4, acquiring angular velocity values of all the shafts of the unmanned aerial vehicle body by using a gyroscope, and acquiring acceleration values of all the shafts of the unmanned aerial vehicle body by using an accelerometer.
4. The unmanned aerial vehicle control method of claim 1, wherein: in step A8, the perception model is a first-method angle algorithm and a second-method angle algorithm, and the current unmanned aerial vehicle state is determined by integrating the first-method angle algorithm and the second-method angle algorithm, wherein the first-method comprises:
a81a, setting the output angular velocity of the gyroscope to be Gi= [ g ] xi ,g yi ,g zi ]T, i=1, 2,..k, accelerometer output acceleration is a= [ a xi ,a yi ,a zi ]T,i＝1,2,...k；
Then the resultant angular velocity of the system isThe combined acceleration is
A82a, setting the current state of the unmanned aerial vehicle to be delta, wherein delta=1 indicates that the system is in spin; δ=0 represents that the system is in a static or uniform motion state, and the system motion state judgment rule is as follows:
if it isAnd->Judging that the system is in a static or uniform motion state delta=0;
if it isOr->The system is in dynamic delta=1, n is the number of samples;
in step A8, the second method includes:
establishing a machine body coordinate system, and calculating the roll angle of a transverse roller under the machine body coordinate system by using a complementary filtering algorithm, wherein the method comprises the following steps:
a81b, setting the roll angle as R and the roll angular velocity as Gyro R The roll acceleration is Acc R ；
A82b, setting the weighting coefficient of the complementary filter as lambda, the time constant as tau, and the running period as d t Then
A83b is the roll angle R k ＝λ×(R k-1 +Gyro R ×d t )+(1-λ)×Acc R ；
A84b, the roll angle change rate K is
The comprehensive judgment mode is as follows: if and only if delta=1 in method one and R in method two k When the change rate K of the unmanned aerial vehicle is smaller than 0.1, judging that the unmanned aerial vehicle is in a non-spinning state at the moment; at the moment, the flight control starts the power motor of the unmanned aerial vehicle to stabilize the attitude of the aircraft, and the next task is carried out.
5. A method of unmanned aerial vehicle control according to claim 3, wherein: in step A1, establishing a matching relationship between an exposed area of an unmanned aerial vehicle horn body and an unfolding angle of the horn body, including:
setting the width of the horn body as b, the total length of the horn body as L, the width distance between the rotating shaft and the unmanned aerial vehicle body as b1, the unfolding angle of the horn body as theta, the exposed length of the horn body as L1 and the exposed area A of the horn body;
the approximation can be obtained:
the exposed area is as follows:
6. a method of unmanned aerial vehicle control according to claim 3, wherein: in step A2, establishing a matching relationship between the rotation linear speed of the exposed area of the horn body and the deployment angle of the horn body, including:
setting the distance between the rotating shaft and the axis of the unmanned aerial vehicle body as b 2 The linear speed of the top end of the exposed area of the horn body is V, and the distance between the top end of the horn body and the axis of the unmanned aerial vehicle body is b 3 The rotation angular velocity of the unmanned plane body is omega; the approximation can be obtained:
b 3 ＝b 2 +L×sinθ；
V＝ω×b 3 ＝ω×(b 2 +L×sinθ)；
wherein: l is the total length of the arm body.
7. The unmanned aerial vehicle control method of claim 1, wherein: in step A3, establishing a matching relationship between the air resistance of the horn body and the centrifugal force, including:
setting the centrifugal force at the power motor of the horn body as F, setting the air resistance received by the side surface of the horn body as F, and setting the weight of the horn body as m;
the method can obtain:
F＝m×ω 2 ×L×sinθ；
wherein: c is the air resistance coefficient, ρ is the air density, ω is the unmanned aerial vehicle body rotational angular velocity, b is the width of the horn body, b 2 For the distance between the rotating shaft and the axis of the unmanned aerial vehicle body, A is the exposed area of the horn body, L is the total length of the horn body, L1 is the exposed length of the horn body, and V is the linear speed of the top end of the exposed area of the horn body.
8. The unmanned aerial vehicle control method of claim 1, wherein: in step A6, notch filter filtering is performed on signals acquired by the gyroscope, including:
the transfer function of the continuous system quadratic notch filter is as follows:
wherein omega bw Is notch width, unit rad/s; omega c The unit rad/s is the notch center frequency, and s is the input signal frequency;
a62, discretizing the step A61 by adopting a pole-zero matching method, wherein the formula is as follows:
wherein: j is an imaginary number, ω bw Is notch width, unit rad/s; omega c For notch center frequency, units rad/s, K s Is constant, K s ＝1；p 1 、p 2 All are poles, p of notch filter 1 ＝α+β，p 2 =α - β; has the following componentsAlpha is a pole value part 1, beta is a pole value part 2, s is the input signal frequency;
a63, the zero pole in the complex frequency domain is corresponding to the z domain, and the corresponding relation of the ith zero pole is as follows:
wherein: z i T is the input frequency in the polar coordinate system s For discretizing sampling time s i Is the input frequency in a rectangular coordinate system;
a64, substituting the zero pole of the step A63 into the formula of the step A62, and obtaining an equation under the z domain by means of the Euler formula as follows:
wherein: gamma is the substitution factor for the gamma,T s is the discretized sampling time, unit s, omega c For notch center frequency, K z As a filtering constant, z is an input frequency in a polar coordinate system;
a65, when the complex frequency domain is 0, the z domain is 1, namely G(s) | s＝0 ＝G(z)| z＝1 ；
A66, combining the step A65 with the step A62 and the step A64 to obtain:
the simplification can be obtained:
wherein: k (K) z Is a filtering constant, gamma is a substitution factor, beta is a pole value part 2, omega c For notch center frequency, T s For discretized sampling time, z is the input frequency in the polar coordinate system;
a67, integrating the step A64 to obtain:
using variable substitution to make available:
wherein: a, a 0 ＝K Z ，a 1 ＝-2K z cos(ω c T s )，a 2 ＝K Z ，b 1 ＝2γcos(βT s )，b 2 ＝-γ 2 The method comprises the steps of carrying out a first treatment on the surface of the The discretization differential equation of the notch filter based on the zero pole matching method is obtained by the method:
y(k)＝a 0 γ(k)+a 1 γ(k-1)+a 2 γ(k-2)+b 1 y(k-1)+b 2 y(k-2)；
wherein: y (k) is the output quantity of the notch filter, y (k-1) is the last output quantity of the notch filter, and y (k-2) is the last two output quantities of the notch filter; gamma (k) is the input of the notch filter, gamma (k-1) is the last input of the notch filter, gamma (k-2) is the last two inputs of the notch filter, a 0 、a 1 、a 2 、b 1 、b 2 All are parameters of the digital notch filter;
and carrying out data filtering iteration by using a discretized differential equation.
9. The unmanned aerial vehicle control method of claim 1, wherein: in step B9, the filtering algorithm includes:
b91, establishing a mapping relation between pressure and height:
wherein: h represents altitude, the unit is m, P is the atmospheric pressure value of the current position acquired by the atmospheric pressure sensor, and P 0 Is a standard atmospheric pressure value;
and B92, correcting the altitude value converted in the step B91, wherein the correction formula is as follows:
summing formula of altitude value H for the first N times in static state under initialization, N is number of altitude values, H sum Is the sum of the N altitude values:
formula for averaging N times of initial data, H average Is averaged toValue:
H average ＝H sum /N；
corrected relative altitude value formula, where H relative The relative height value of the carrier with respect to the initial position is:
H relative ＝Height-H average ；
and B93, acquiring X, Y, Z triaxial acceleration values by an acceleration sensor, extracting motion characteristics by adopting a triaxial acceleration vector sum value, and calculating the triaxial acceleration vector sum as follows:
wherein: a is that XYZ Representing the value of the triaxial acceleration vector sum, A X Representing acceleration value in X-axis direction, A Y Representing the acceleration value in the Y-axis direction, A Z Representing the acceleration value in the Z-axis direction;
b94, data H relative And A XYZ Respectively carrying out low-pass filtering to remove data acquisition noise;
b95 value A of the triaxial acceleration vector sum XYZ Calculating the slope D A ；
B96, pair D A Setting a threshold value when D A If the height is greater than the threshold value, the barometer is considered to collect the height reliably when the height is changed, otherwise D is removed A Values.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105867400A (en) * | 2016-04-20 | 2016-08-17 | 北京博瑞爱飞科技发展有限公司 | Flying control method and device for unmanned aerial vehicle |
| CN108829124A (en) * | 2018-04-24 | 2018-11-16 | 骁越科技（青岛）有限公司 | A kind of unmanned plane automatic capture technology and equipment |
| CN110081878A (en) * | 2019-05-17 | 2019-08-02 | 东北大学 | A kind of posture and location determining method of multi-rotor unmanned aerial vehicle |
| CN112733421A (en) * | 2020-12-01 | 2021-04-30 | 南京航空航天大学 | Task planning method for cooperative fight against earth by unmanned aerial vehicle |
| CN113325865A (en) * | 2021-05-10 | 2021-08-31 | 哈尔滨理工大学 | Unmanned aerial vehicle control method, control device and control system |
| CN216375002U (en) * | 2021-04-09 | 2022-04-26 | 深圳微希科技有限公司 | Unmanned aerial vehicle turnover control system and unmanned aerial vehicle |
| CN115031730A (en) * | 2022-05-27 | 2022-09-09 | 南京航空航天大学 | Method for estimating horizontal attitude of falling body motion of fixed-wing unmanned aerial vehicle |
| CN115963858A (en) * | 2023-01-09 | 2023-04-14 | 歌尔股份有限公司 | Unmanned aerial vehicle flight control method, device, equipment and storage medium |
-
2023
- 2023-12-08 CN CN202311675704.4A patent/CN117389322B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105867400A (en) * | 2016-04-20 | 2016-08-17 | 北京博瑞爱飞科技发展有限公司 | Flying control method and device for unmanned aerial vehicle |
| CN108829124A (en) * | 2018-04-24 | 2018-11-16 | 骁越科技（青岛）有限公司 | A kind of unmanned plane automatic capture technology and equipment |
| CN110081878A (en) * | 2019-05-17 | 2019-08-02 | 东北大学 | A kind of posture and location determining method of multi-rotor unmanned aerial vehicle |
| CN112733421A (en) * | 2020-12-01 | 2021-04-30 | 南京航空航天大学 | Task planning method for cooperative fight against earth by unmanned aerial vehicle |
| CN216375002U (en) * | 2021-04-09 | 2022-04-26 | 深圳微希科技有限公司 | Unmanned aerial vehicle turnover control system and unmanned aerial vehicle |
| CN113325865A (en) * | 2021-05-10 | 2021-08-31 | 哈尔滨理工大学 | Unmanned aerial vehicle control method, control device and control system |
| CN115031730A (en) * | 2022-05-27 | 2022-09-09 | 南京航空航天大学 | Method for estimating horizontal attitude of falling body motion of fixed-wing unmanned aerial vehicle |
| CN115963858A (en) * | 2023-01-09 | 2023-04-14 | 歌尔股份有限公司 | Unmanned aerial vehicle flight control method, device, equipment and storage medium |
Non-Patent Citations (2)
| Title |
|---|
| 一种可在高空投放的低成本小型无人机技术研究;周前进 等;《兵器装备工程学报》;全文 * |
| 无人机投放分离特性仿真与优化;曾丽芳 等;《气体物理》;全文 * |
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