CN106444809B - Unmanned aerial vehicle flight controller - Google Patents
Unmanned aerial vehicle flight controller Download PDFInfo
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- CN106444809B CN106444809B CN201610890066.1A CN201610890066A CN106444809B CN 106444809 B CN106444809 B CN 106444809B CN 201610890066 A CN201610890066 A CN 201610890066A CN 106444809 B CN106444809 B CN 106444809B
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- VYPSYNLAJGMNEJ-UHFFFAOYSA-N Silicium dioxide Chemical compound O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 claims description 3
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- 229910002027 silica gel Inorganic materials 0.000 claims description 3
- 229910000679 solder Inorganic materials 0.000 claims description 2
- 239000007787 solid Substances 0.000 claims description 2
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- 238000004519 manufacturing process Methods 0.000 description 7
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 description 4
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- 238000007499 fusion processing Methods 0.000 description 3
- 239000003292 glue Substances 0.000 description 3
- 238000009434 installation Methods 0.000 description 3
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 2
- 238000006073 displacement reaction Methods 0.000 description 2
- 238000007667 floating Methods 0.000 description 2
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
- G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
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Abstract
The invention discloses an unmanned aerial vehicle flight controller, which comprises a flight controller top cover (1), an upper layer damping sponge (2), an IMU module (3), a lower layer damping sponge (5) and a flight controller bottom plate (9); the device comprises a flight controller top cover (1), an upper shock-absorbing sponge (2), an IMU module (3), a lower shock-absorbing sponge (5) and a flight controller bottom plate (9) which are sequentially arranged and connected from top to bottom; the IMU module (3) is wrapped between the upper layer damping sponge (2) and the lower layer damping sponge (5). The unmanned aerial vehicle flight controller also comprises a built-in power supply arranged on a flight controller bottom plate (9); built-in power supply including switching regulator a regulator and a linear voltage regulator; the input end of the switching voltage stabilizer is connected with the battery through a battery connecting wire, the output end of the switching voltage stabilizer is connected with the linear voltage stabilizer, and the output end of the linear voltage stabilizer supplies power for the internal equipment of the flight controller. The unmanned aerial vehicle flight controller is small in interference, and stable in gesture resolving and controlling.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicle flight control, in particular to an unmanned aerial vehicle flight controller.
Background
Unmanned aerial vehicle flight controllers are the core control components of the unmanned aerial vehicle, whose task is to receive data from internal sensors (gyroscopes, accelerometers, magnetometers, barometers, thermometers, voltmeters) and external sensors (GNSS positioning devices, external magnetometers), and to convert, by means of specific flight control algorithms, into control signals required by the electronic speed regulator, in order to vary and control the attitude (pitch/roll/heading conditions), the geographical position and the altitude of the unmanned aerial vehicle.
At present, most unmanned aerial vehicle flight controllers are powered through an external power supply module, the noise and fluctuation of the power supply voltage of the external power supply module are large, and meanwhile, the flight controllers are easily interfered due to the fact that the distance between the ground wire and the flight controllers is long; most unmanned aerial vehicle flight controllers are hard-connected by adopting an IMU (Inertial measurement unit, an inertial measurement unit), and data acquired by the IMU are easy to interfere due to vibration generated by a propeller when the unmanned aerial vehicle flies, so that instability of gesture calculation is caused.
The output quantity of the current mainstream flight attitude calculation method is Euler angle, and the flight control method controls the attitude of the machine body by taking the Euler angle as an internal control object, wherein the Euler angle has a universal lock defect and cannot be suitable for controlling the full attitude, so that the motion amplitude of the unmanned aerial vehicle is limited, and meanwhile, the processor burden is increased and the real-time performance of the control is reduced due to the inclusion of trigonometric function operation.
Disclosure of Invention
The invention solves the technical problem of providing the unmanned aerial vehicle flight controller which is small in interference and stable in gesture calculation and control aiming at the defects of the prior art.
The technical scheme adopted for solving the technical problems is as follows:
an unmanned aerial vehicle flight controller comprises a flight controller top cover 1, an upper layer damping sponge 2, an IMU module 3, a lower layer damping sponge 5 and a flight controller bottom plate 9;
the upper layer damping sponge 2, the IMU module 3, the lower layer damping sponge 5 and the flight controller bottom plate 9 are sequentially arranged from top to bottom; the IMU module 3 is wrapped between the upper layer damping sponge 2 and the lower layer damping sponge 5.
The IMU module is integrated with a triaxial accelerometer, a triaxial magnetometer and a triaxial gyroscope; and the measurement data of the IMU module is transmitted to a CPU on the bottom plate of the flight controller for gesture calculation.
The flight controller top cover 1, the upper shock-absorbing sponge 2, the IMU module 3, the lower shock-absorbing sponge 5 and the flight controller bottom plate 9 are sequentially arranged and connected from top to bottom, and the connecting medium is double-sided non-conductive adhesive.
The areas of the upper layer damping sponge 2 and the lower layer damping sponge 5 are larger than the area of the IMU module 3; the IMU module 3 is arranged in the center between the upper layer damping sponge 2 and the lower layer damping sponge 5; the upper layer damping sponge 2 is connected with the lower layer damping sponge 5 corresponding to the part outside the IMU module 3; the connecting medium is double-sided non-conductive adhesive.
The unmanned aerial vehicle flight controller also comprises a built-in power supply arranged on a flight controller bottom plate 9;
the built-in power supply comprises a switching regulator and a linear regulator; the input end of the switching regulator is connected with the battery through a battery connecting wire, the output end of the switching regulator is connected with the linear regulator, and the output end of the linear regulator supplies power for internal equipment of the flight controller (comprising a CAN transceiver, a CPU, an auxiliary CPU, a communication buffer, a nonvolatile memory, an LED indicator, an IMU module 3 and the like on a bottom plate 9 of the flight controller).
The switching voltage stabilizer is a Buck type DC-DC switching voltage stabilizer TPS54160; the linear voltage stabilizer is high-precision and low-precision a differential pressure SPX1117M3 linear regulator; the 5V output connecting wire of the Buck type DC-DC switching voltage stabilizer TPS54160 is connected to the linear voltage stabilizer SPX1117M3 through an internal circuit, and outputs high-precision low-ripple 3.3V direct current voltage;
the loop compensation part of the TPS54160Buck type DC-DC switching regulator adopts a 102K-1% resistor and a 2.2nF/50V low ESR ceramic capacitor which are connected in series, and then a 1.5pF/50V low ESR ceramic capacitor is connected in parallel; the output feedback resistor of the TPS54160Buck type DC-DC switching voltage stabilizer is set to be 52.6K and 10K which are connected in series, and the output is regulated to be 5V direct current;
the input of the SPX1117M3 linear regulator, namely, a 4.7uF/10V ceramic capacitor is connected in parallel on the 5V output connecting line, A100 uF/10V low ESR ceramic capacitor and a 100nF/16V ceramic capacitor are connected in parallel between the output end of the SPX1117M3 linear voltage stabilizer and the power end of the internal equipment of the flight controller.
The unmanned aerial vehicle flight controller further comprises an electronic speed regulator signal output socket board 6 and an external sensor and peripheral module signal socket board 7;
an electronic governor signal output socket board 6 and an external sensor and external module signal socket board 7; the bottoms of the two frames are vertically connected with the bottom plate 9 of the flight controller, and the connection points are respectively positioned at the edges of the two opposite sides of the bottom plate 9 of the flight controller;
the tops of the electronic speed regulator signal output socket board 6 and the external sensor and external module signal socket board 7 are vertically connected with the flight controller top cover 1, and the connection points are respectively positioned at the edges of two opposite sides of the flight controller top cover 1;
the connecting medium adopts solid solder paste.
The flight controller bottom plate 9 is connected with the electronic speed regulator signal output socket plate 6 through the golden finger welding at the joint between the two, and the flight controller bottom plate 6 is connected with the external sensor and the external signal socket plate 7 through the golden finger welding at the joint between the two.
The connectors of the electronic speed regulator signal output socket board 6 and the external sensor and external module signal socket board 7 are 2.54mm gold-plated pin bars 8, wherein the electronic speed regulator signal output socket board 6 comprises two rows of pin bars, 18 pin bars are arranged in each row, and the external sensor and external module signal socket board 7 comprises two rows of pin bars, 17 pin bars are arranged in each row.
The battery connecting wire is divided into two sections, the front section is positioned between the battery and the flight controller and is a silica gel wire, and the front section is connected with the flight controller through an external sensor and a peripheral module signal socket board 7; the second section is positioned on a printed circuit board in the flight controller, and a 500mA self-recovery fuse is connected in series on the second section of wire; the current output of the 500mA self-healing fuse is also connected to the common ground inside the flight controller via a 4.7uF/50V low ESR ceramic capacitor.
A printed circuit board and a CPU11 are arranged on the flight controller bottom plate 9; CPU and printed circuit board is connected through an electronic circuit; the IMU module 3 and the flight controller bottom plate 9 are respectively provided with an IMU module 14P connected with a flip type FPC base 4 and a main control bottom plate 14P connected with a flip type FPC base 10; the IMU module 3 is connected with the bottom plate 9 of the flight controller through an FPC base and an FPC flexible flat cable.
The unmanned aerial vehicle flight controller takes a space attitude vector as a control object, and specifically comprises the following steps:
1) Error correction and normalization are carried out on the original triaxial accelerometer data, and the corrected triaxial accelerometer data are recorded as: aXN, aZN;
2) Error correction and normalization are carried out on the original triaxial magnetometer data, and the corrected triaxial magnetometer data are recorded as: mXN is the number of the active ingredients, mYN is used for the preparation of the medicine, mZN;
3) Fusing the two groups of corrected data in the steps 1) and 2) to obtain a first posture matrix;
4) Performing error correction on the original triaxial gyroscope data to obtain corrected triaxial gyroscope data, and recording the corrected triaxial gyroscope data as gX, gY and gZ;
fusing the corrected triaxial gyroscope data with a third gesture matrix obtained in the previous control period to obtain a second gesture matrix; the initial value of the third gesture matrix is equal to the value of the first gesture matrix obtained in the first control period;
5) Fusing the first gesture matrix and the second gesture matrix, and obtaining a third gesture matrix of the control period, namely a fused direction cosine matrix.
The unmanned aerial vehicle flight controller performs attitude control through the following steps after performing attitude calculation:
extracting a balance vector B and a heading vector Y from the third gesture matrix;
wherein the balance vector is a vector formed by the elements of the third row in the third gesture matrix: (c 31, c32, c 33)
The heading vector is a vector formed by elements of a first row and a first column of the third gesture matrix and elements of a first column of a second row: (c 11, c 21).
Controlling the balance of the machine body by utilizing the difference between the expected balance vector and the actual balance vector; when the expected balance vector is not equal to the actual balance vector, calculating a balance vector difference; and then converting the balance vector difference into motor matrix control quantity, and finally decoupling the motor matrix control quantity into control quantity of each motor.
Controlling the body heading by utilizing the difference between the expected heading vector and the actual heading vector; when the expected heading vector is not equal to the actual heading vector, calculating a heading vector difference; and then converting the course vector difference into motor matrix control quantity, and finally decoupling the motor matrix control quantity into control quantity of each motor.
The beneficial effects are that:
the invention adopts a built-in DC-DC and linear voltage stabilizer power supply mode, a power supply system adopts a built-in high-efficiency small package, a Buck type DC-DC switching step-down voltage stabilizer converts external voltage of 7.2V to 30V into 5V, and then an ultralow noise linear voltage stabilizer with 1% precision is used for further converting 5V into 3.3V to supply power for a CPU and an IMU module. The mode not only improves the power supply quality and the power supply stability, has small ripple voltage and no ground wire interference problem, but also simplifies the installation of the flight controller. The problems of poor power supply quality and large ripple voltage of the existing flight controller can be effectively solved.
The IMU adopts an independent installation mode, and an IMU module is coated by adopting an sexual damping sponge. The upper layer damping sponge and the lower layer damping sponge are both high-elasticity damping sponge. The method solves the problem that the hard connection of the existing IMU of the flight controller is easy to be interfered by vibration, weakens the vibration suffered by the IMU module, reduces fluctuation of original output data of the IMU, greatly improves the stability of the IMU, reduces the influence of the vibration suffered by the IMU, and improves the flight control stability.
The invention designs a gesture resolving method based on a gesture space vector as a control object, which overcomes the defects of a conventional flight controller that a euler angle is used as a control object to cause a universal lock, has no universal lock problem, can realize resolving of full gesture movement, completely releases the maneuverability of an unmanned aerial vehicle, enables the full gesture movement to be possible, removes the operation process of a trigonometric function, and greatly reduces the load of a CPU.
Drawings
The invention will be further described with reference to the drawings and examples.
FIG. 1 is an assembled block diagram of a flight controller of the present invention.
Fig. 2 is a schematic diagram of the built-in power connection of the present invention.
Fig. 3 is a circuit configuration diagram of the switching regulator of the present invention.
Fig. 4 is a schematic diagram of the gesture resolving method of the present invention.
Fig. 5 is a flowchart of the attitude control method of the present invention.
Reference numerals illustrate:
1. the aircraft controller is characterized by comprising a top cover, an upper layer damping sponge, a 3.IMU module, a 4.IMU module 14P, a flip type FPC base, a lower layer damping sponge, an electronic speed regulator signal output socket board, a 7.external sensor and peripheral module signal socket board, 8.2.54mm interval gold-plated pins, a 9.aircraft controller bottom plate, a 10.main control bottom plate 14P, and a 11.CPU.
Detailed Description
The invention is further described in detail below with reference to the drawings and detailed description.
As shown in fig. 1, a preferred unmanned aircraft flight controller internal architecture is illustrated.
As shown in fig. 1, the unmanned aerial vehicle flight controller disclosed by the invention comprises a flight controller top cover 1, an upper layer damping sponge 2, an imu module 3, a lower layer damping sponge 5, a flight controller bottom plate 9, an electronic speed regulator signal output socket plate 6, an external sensor and an external module signal socket plate 7.
As shown in fig. 1, the stacking installation sequence from top to bottom is that the top cover 1 of the flight controller is connected with the upper layer damping sponge 2, the connecting medium adopts double-sided nonconductive glue, the upper layer damping sponge 2 is connected with the IMU module 3, the connecting medium adopts double-sided nonconductive glue, the IMU module 3 and the lower layer damping sponge 5 are connected, meanwhile, the upper layer damping sponge 2 is also connected with the lower layer damping sponge 5, the lower layer damping sponge 5 is connected with the bottom plate 9 of the flight controller, the connecting medium adopts double-sided nonconductive glue, the signal output socket plate 6 of the electronic governor is vertically connected with the bottom plate 9 of the flight controller, the connecting point is positioned at the leftmost edge of the signal output socket plate 6 of the electronic governor, the signal socket plate 7 of the external sensor and the peripheral module is vertically connected with the bottom plate 9 of the flight controller, and the connecting point is positioned at the rightmost edge of the signal socket plate 7 of the external sensor and peripheral module.
As shown in FIG. 1, the volume of the top cover of the flight controller was 52mm×42mm×1.2mm, the volume of the upper layer damping sponge before assembly was 48mm×40mm×6mm, the volume of the upper layer damping sponge after assembly was 48mm×40mm×5mm, the volume of the IMU module was 25mm×22mm×1mm, the volume of the lower layer damping sponge before assembly was 48mm×40mm×6mm, the volume of the lower layer damping sponge after assembly was 48mm×40mm×5mm, the volume of the flight controller base plate before mounting components was 52mm×42mm×1.2mm, the volume of the flight controller base plate after mounting components was 52mm×42mm×3.5 mm, the volume of the electronic governor signal output socket was 42mm×15mm×1mm, and the volumes of the external sensor and peripheral module signal socket were 42mm×15mm×1mm.
As shown in fig. 1, the connectors employed by the electronic governor signal output socket and the external sensor and peripheral module signal socket are 2.54mm gold plated pins 8, wherein the electronic governor signal output socket contains 18 x 2 pins and the external sensor and peripheral module signal socket contains 17 x 2 pins.
The unmanned aerial vehicle flight controller further comprises a built-in power supply. As shown in fig. 2 and 3, the lithium battery special for the unmanned aerial vehicle is connected with a flight controller through a section of silica gel wire and a connector, the lithium battery is input into a Buck type DC-DC switching voltage stabilizer in the flight controller, the switching voltage stabilizer adopts an integrated Buck type DC-DC controller TPS54160, the input section of the controller is connected with a 500mA self-recovery fuse in series, a 4.7uF/50V low ESR ceramic capacitor is connected in parallel, the output end of the controller is connected with a 100uF/10V low ESR ceramic capacitor and a 100nF/10V low ESR ceramic capacitor in parallel, a loop compensation part (i.e. COMP pin) is connected in series by adopting a 102K-1% resistor and a 2.2nF/50V low ESR ceramic capacitor in parallel. The output feedback part is: the output end is grounded through the resistances of 52.6K and 10K of the serially connected output feedback resistances (R4 and R9), and the VSENSE pin is connected with the connection point of the two resistances. The DC-DC switching regulator output can be regulated to 5 vdc by setting the output feedback resistor to 52.6K and 10K in series.
In fig. 2, the 5V output of the switching regulator is connected to the high-precision low-dropout linear regulator SPX1117M3 through an internal circuit, a 4.7uF/10V ceramic capacitor is added to the input end of the regulator, and a 100uF/10V low ESR ceramic capacitor and a 100nF/16V ceramic capacitor are connected in parallel to the output end, so that a 3.3V dc voltage with high precision and low ripple can be output, and the dc voltage supplies power to most of the flight controller internal devices and sensors.
As shown in fig. 4, the basic procedure of the attitude resolving method based on the attitude space vector as the control object is illustrated.
As shown in fig. 4, the original triaxial accelerometer data is first subjected to zero bias and sensitivity error correction, the original triaxial magnetometer data is subjected to zero bias, sensitivity error and elliptical error correction, the two groups of fusion data are fused to obtain a first gesture matrix, the original triaxial gyroscope data is subjected to zero bias and sensitivity error correction to obtain corrected triaxial gyroscope data, the data is fused with a third gesture matrix obtained in the last control period to obtain a second gesture matrix, the first gesture matrix and the second gesture matrix are fused to obtain a third gesture matrix, the third gesture matrix contains information of a balance vector and a heading vector, and a balance vector B and a heading vector Y are extracted from the third gesture matrix.
As shown in fig. 4, the original triaxial accelerometer data, the original triaxial magnetometer data, and the original triaxial gyroscope data are all read from the IMU module and updated at each control cycle.
As shown in fig. 4, the zero offset correction of the accelerometer raw data is implemented by subtracting an offset constant on the basis of the raw data, the offset constant being determined by the error in the accelerometer production process, and the sensitivity error correction of the accelerometer raw data is implemented by multiplying the sensitivity correction coefficient on the basis of the raw data, the correction coefficient being determined by the error in the accelerometer production process.
As shown in fig. 4, the zero bias correction of the original magnetometer data is achieved by subtracting an offset constant on the basis of the original data, the offset constant being determined by the error in the magnetometer production process, the sensitivity error correction of the original magnetometer data is achieved by multiplying the sensitivity correction coefficient on the basis of the original data, the correction coefficient is determined by the error in the magnetometer production process, and the ellipse correction of the original magnetometer data is achieved by performing a quadratic polynomial fit on the basis of the original data.
As shown in fig. 4, the zero bias correction of the original gyroscope data is achieved by subtracting an offset constant on the basis of the original data, the offset constant being determined by the error in the production process of the gyroscope, and the sensitivity error correction of the original gyroscope data is achieved by multiplying the sensitivity correction coefficient on the basis of the original data, the correction coefficient being determined by the error in the production process of the gyroscope.
As shown in figure 4 of the drawings, the corrected data of the triaxial accelerometer and the triaxial magnetometer are fused to obtain a first attitude matrix, the fusion process combines the raw triaxial accelerometer data and the raw triaxial magnetometer data into a complete pose matrix.
As shown in fig. 4, the corrected data of the tri-axis gyroscope is fused with the third gesture matrix obtained in the previous control period to obtain a second gesture matrix, and the fusion process combines the original tri-axis gyroscope data and the third gesture matrix obtained in the previous control period into a complete gesture matrix.
As shown in fig. 4, the first gesture matrix and the second gesture matrix are fused to obtain a third gesture matrix, and most of errors of the first gesture matrix and the second gesture matrix are eliminated in the fusion process, so that more accurate gesture information is obtained, and the more accurate gesture information is stored in the third gesture matrix.
The unmanned aerial vehicle flight controller takes a space attitude vector as a control object, and specifically comprises the following steps:
1) Error correction and normalization are carried out on the original triaxial accelerometer data, and the corrected triaxial accelerometer data are recorded as: aXN, aZN;
2) Error correction and normalization are carried out on the original triaxial magnetometer data, and the corrected triaxial magnetometer data are recorded as: mXN, mYN, mZN;
3) Fusing the two groups of corrected data in the steps 1) and 2) to obtain a first posture matrix;
4) Performing error correction on the original triaxial gyroscope data to obtain corrected triaxial gyroscope data, and recording the corrected triaxial gyroscope data as gX, gY and gZ;
fusing the corrected triaxial gyroscope data with a third gesture matrix obtained in the previous control period to obtain a second gesture matrix; the initial value of the third gesture matrix is equal to the value of the first gesture matrix obtained in the first control period;
5) And fusing the first gesture matrix and the second gesture matrix to obtain a third gesture matrix of the control period, namely a fused direction cosine matrix.
The step 1) specifically comprises the following steps:
the accelerometers (aX, aY, aZ) are read.
Zero offset correction and sensitivity error correction are performed on the original triaxial accelerometer data according to the following formulas:
aXZ＝aX-zoaX
aYZ＝(aY-zoaY)*saY
aZZ＝(aZ-zoaZ)*saZ
wherein, zoAX, zoAY and zoAZ are respectively triaxial accelerometer offset value constants, saY and saZ are respectively the relative values of Y-axis and Z-axis accelerometer sensitivity correction coefficients and X-axis sensitivity correction coefficients; the offset constant and the sensitivity correction coefficient are determined by errors in the production process of the instrument;
and correcting the horizontal-magnetic declination of the triaxial acceleration data:
aXH＝h11*aXZ+h12*aY+h13*aZ
aYH＝h21*aXZ+h22*aY+h23*aZ
aZH＝h31*aXZ+h32*aY+h33*aZ
wherein the horizontal-declination correction matrixObtained by calibration measurement;
normalizing triaxial accelerometer data:
the step 2) specifically comprises the following steps:
the raw triaxial magnetometer data is read (magX, magY, magZ).
Firstly, carrying out zero offset correction and sensitivity error correction on original triaxial magnetometer data according to the following formula:
mXZ＝magX-zomX
mYZ＝(magY-zomY)*smY
mZZ＝(magZ-zomZ)*smZ
wherein, zomX, zomY and zomZ are respectively triaxial magnetometer offset constants, smY and smZ are respectively the relative values of Y-axis and Z-axis magnetometer sensitivity correction coefficients and X-axis magnetometer sensitivity correction coefficients; and then carrying out ellipse correction on the triaxial magnetometer data, namely carrying out quadratic polynomial fitting on the triaxial magnetometer data; the quadratic polynomial is obtained by pre-calibrating the magnetometer to obtain actual triaxial magnetometer data, and then replacing the triaxial magnetometer data by a point closest to the quadratic polynomial on the quadratic polynomial curve; ' s of
And correcting the horizontal-magnetic declination angle of the triaxial magnetometer data:
mXH＝h11*mXZ+h12*mYZ+h13*mZZ
mYH＝h21*mXZ+h22*mYZ+h23*mZZ
mZH＝h31*mXZ+h32*mYZ+h33*mZZ
the triaxial magnetometer data is then normalized [ normalized later, which may not be needed here, but is performed here in view of the higher precision of the result of the operation between floating point numbers with magnitudes close in the floating point operation process) ]:
in the step 3), the first gesture matrix is recorded as:
wherein, the third row element is:
a31＝aXN，a32＝aYN，a33＝aZN；
the first row elements are:
wherein v is a verticality factor, v= mXN × aXN + mYN × aYN + mZN × aZN;
the second row of elements is:
a21＝a13*a32-a12*a33
a22＝a11*a33-a31*a13
a23＝a31*a12-a11*a32
the calculation principle of the first row elements and the second row elements of the first gesture matrix is as follows:
carrying out verticality treatment on the corrected triaxial magnetometer data mXN, mYN and mZN;
because the magnetometer is not perpendicular to the accelerometer, the perpendicular processing is needed, a K-x accelerometer vector needs to be added to the magnetometer, and the principle that the dot product is 0 according to the mutually perpendicular vectors is as follows:
(mX-v*aX,mY-v*aY,mZ-v*aZ)*(aX,aY,aZ)＝0
the perpendicularity factor can be obtained:
and (3) carrying out verticality treatment on magnetometer data:
mXV＝mXN-v*aXN
mYV＝mYN-v*aYN
mZV＝mZN-v*aZN
and (5) carrying out normalization treatment again:
the first row element of the first gesture matrix is obtained as follows:
a11＝mXVN
a12＝mYVN
a13＝mZVN
the second row elements of the first gesture matrix are obtained according to the orthogonal characteristic of the direction cosine matrix:
a21＝a13*a32-a12*a33
a22＝a11*a33-a31*a13
a23＝a31*a12-a11*a32。
in the step 4), the second gesture matrix is recorded as:
the third pose matrix is noted as:
the calculation process of the second gesture matrix is as follows:
firstly, the corrected triaxial gyroscope data are multiplied by an updating period T respectively to obtain triaxial angle vectors alpha X, alpha Y and alpha Z:
αX＝gX*T
αY＝gY*T
αZ＝gZ*T
calculating quaternion update factors (r 0, r1, r2, r 3):
r0＝1-sSquareSum/8
wherein squaresum=αx 2 +αY 2 +αZ 2
Converting a third gesture matrix obtained in the last control period into quaternions:
if q0+.0, then there is:
if q0=0, then there are:
normalizing the quaternion:
updating quaternion:
q0＝q0N*r0-q1N*r1-q2N*r2-q3N*r3
q1＝q1N*r0+q0N*r1-q3N*r2+q2N*r3
q2＝q2N*r0+q3N*r1+q0N*r2-q1N*r3
q3＝q3N*r0-q2N*r1+q1N*r2+q0N*r3
normalization processing is carried out on the updated quaternion [ dividing each component of the quaternion by the square sum of each component, respectively ] to obtain new q0N, q1N, q2N and q3N:
convert it into a second pose matrix [ gyro direction cosine matrix ]:
b11＝q0N 2 +q1N 2 -q2N 2 -q3N 2
b12＝2*q1N*q2N-2*q0N*q3N
b13＝2*q1N*q3N+2*q0N*q2N
b21＝2*q1N*q2N+2*q0N*q3N
b22＝q0N 2 -q1N 2 +q2N 2 -q3N 2
b23＝2*q2N*q3N-2*q0N*q1N
b31＝2*q1n*q3N-2*q0N*q2N
b32＝2*q2N*q3N+2*q0N*q1N
b33＝q0N 2 -q1N 2 -q2N 2 +q3N 2 。
in the step 5), the third gesture matrix [ the fused direction cosine matrix ] of the control period is calculated by:
calculating a deviation vector of the corrected triaxial accelerometer data and the third row element of the second posture matrix:
dX3＝aXN-b31
dY3＝aYN-b32
dZ3＝aZN-b33
multiplying by a scaling factor m3 to obtain a vector for correction:
cX3＝dX3*m3
cY3＝dY3*m3
cZ3＝dZ3*m3
calculating a vector after the corrected triaxial accelerometer data and the third row of the second posture matrix are fused:
vX3＝b31+cX3
vY3＝b32+cY3
vZ3＝b33+cZ3
for the fusion after vector normalization:
calculating a deviation vector of the corrected triaxial magnetometer data and the first row element of the second posture matrix:
dX1＝mXN-b11
dY1＝mYN-b12
dZ1＝mZN-b13
multiplying by a scaling factor m1 yields the vector for correction:
cX1＝dX1*m1
cY1＝dY1*m1
cZ1＝dZ1*m1
calculating a vector after the corrected triaxial magnetometer data and the first row of the second posture matrix are fused:
vX1＝b11+cX1
vY1＝b12+cY1
vZ1＝b13+cZ1
since the vector (vX 1, vY1, vZ 1) is not perpendicular to (vX 3N, vY3N, vZ 3N), a squaring process is required, and a k (vX 3N, vY3N, vZ 3N) needs to be added to the vector; the principle of 0 according to the vector dot product perpendicular to each other is as follows:
(vX1-k*vX3N,vY1-k*vY3N,vZ1-k*vZ3N)*(vX3N,vY3N,vZ3N)＝0
the perpendicularity factor can be obtained:
orthogonalization of magnetometer fusion vectors:
vX1V＝vX1-k*vX3N
vY1V＝vY1-k*vY3N
vZ1V＝vZ1-k*vZ3N
wherein k is a squaring factor; k=vx1×vx3n+vy1×vy3n+vz1×vz3n;
normalizing the normalized magnetometer fusion vector:
obtaining a first row element and a third row element of a third gesture matrix:
c11＝vX1N，c12＝vY1N，c13＝vZ1N；
c31＝vX3N，c32＝vY3N，c33＝vZ3N；
solving a second row element of the third posture matrix according to the orthogonal characteristic of the direction cosine matrix:
c21＝c13*c32-c12*c33
c22＝c11*c33-c31*c13
c23＝c31*c12-c11*c32。
as shown in fig. 4, the third gesture matrix may directly extract the balance vector B and the heading vector Y due to the relatively precise gesture information included therein.
As shown in fig. 5, a program flow of a gesture resolving method based on a gesture space vector as a control object is illustrated.
As shown in fig. 5, the body balance is controlled by using the difference between the desired balance vector and the actual balance vector, and when the desired balance vector is not equal to the actual balance vector, the balance vector difference is calculated and normalized, the normalized vector difference is converted into a motor matrix control amount, and finally the motor matrix control amount is input to the gesture control unit for processing.
As shown in fig. 5, the body balance is controlled by using the difference between the expected heading vector and the actual heading vector, when the expected heading vector is not equal to the actual heading vector, the heading vector difference is calculated and normalized, the normalized vector difference is converted into a motor matrix control quantity, and finally the motor matrix control quantity is input into the gesture control unit for processing.
The unmanned aerial vehicle flight controller controls the gesture of the unmanned aerial vehicle according to the third gesture matrix, and specifically comprises the following steps:
(A) Calculating three-axis displacement degree-of-freedom control factors (mX, mY, mZ);
let mx=0;
mY＝0；
the input signal throttle control factor throttleController of the remote controller is directly given to the control factor of the Z-axis displacement freedom degree:
mZ＝throttleController；
(B) Calculating three-axis rotational degree of freedom control factors (sX, sY, sZ):
step B1: multiplying the desired gesture matrix E by the transpose matrix of the third gesture matrix to obtain a transformation matrix D: d=c≡e:
step B2: converting the transformation matrix D into quaternions:
p0＝0.5*(1+d11+d22+d33)^(0.5)；
p1＝0.25/p0*(d32-d23)；
p2＝0.25/p0*(d13-d31)；
p3＝0.25/p0*(d21-d12)；
step B3: calculate the current angular deviation (desired rotation angle) θ:
θ＝arccos(p0)*2，θ∈[0,π]；
step B4: the current angle deviation (expected rotation angle) theta is distributed to three rotation degrees of freedom, and the current angle deviation of the three axes is obtained:
θX＝θ*p1；
θY＝θ*p2；
θZ＝θ*p3；
step B5: calculating a triaxial predicted angular velocity, a triaxial predicted angular deviation, a triaxial expected angular velocity and a triaxial predicted angular velocity deviation
B5.1 Calculating a triaxial predicted angular velocity:
predicted angular velocity of each axis = current angular velocity of the axis (measured directly by the gyroscope, i.e. corrected triaxial gyroscope data are recorded as gX, gY, gZ) +lag time period (the value of which is preset, the value of which is in the range of 0.1-0.3;) the percentage of the acting time (obtained by integration, positive and negative direction cancellation) of the axis rotation control factor is multiplied by the angular velocity increment coefficient of the axis rotation control factor (the value of which is preset, the value of which is in the range of 5-10;): (the sign of the rotation control factor (greater than 0 to 1 and less than 0 to-1) is integrated for the lag period, dividing by the lag time to obtain the percentage of the acting time of the control factor
B5.2 Calculating a triaxial predicted angular deviation:
predicted angular deviation for each axis = current angular deviation for the axis- (current angular velocity for the axis + predicted angular velocity for the axis)/2 (2 lag time;
b5.3 Calculating the triaxial desired angular velocity):
the expected angular velocity of each axis = the predicted angular deviation of the axis the angular deviation angular velocity coefficient of the axis (its value is predetermined, the value range is 10-20) +the minimum expected angular velocity of the axis (its value is predetermined, the value range is 0-0.2.);
b5.4 Calculating a triaxial predicted angular velocity deviation:
predicted angular velocity deviation for each axis = desired angular velocity for that axis-predicted angular velocity for that axis;
step B6: calculating a triaxial overspeed control factor:
overspeed control factor of each shaft = preset value of overspeed control factor of the shaft (the value of the overspeed control factor is preset and is in the range of 0.05-0.2);
step B7: calculating a triaxial rotation control factor (sX, sY, sZ)
Spin control factor for each shaft = the shaft overspeed control factor:
(C) According to the actual model, converting the control factors of 6 degrees of freedom into control amounts of all motors;
for the X4 model, the control amounts of the 4 motors are respectively:
m1＝-sX+sY+sZ+mZ；
m2＝-sX-sY-sZ+mZ；
m3＝sX-sY+sZ+mZ；
m4＝sX+sY-sZ+mZ；
for the X6 model, the control amounts of the 6 motors are respectively: :
m1＝-0.5*sX+sY+sZ+mZ；
m2＝-sX+sZ*-1+mZ；
m3＝-0.5*sX-sY+sZ+mZ；
m4＝0.5*sX-sY+sZ+mZ；
m5＝sX+sZ+mZ；
m6＝0.5*sX+sY-sZ+mZ。
it should be understood, however, that the description herein of specific embodiments is not intended to limit the scope of the invention, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (9)
1. The unmanned aerial vehicle flight controller is characterized by comprising a flight controller top cover (1), an upper layer of shock-absorbing sponge (2), an IMU module (3), a lower layer of shock-absorbing sponge (5) and a flight controller bottom plate (9);
a top cover (1) of the flight controller, an upper layer damping sponge (2), an IMU module (3), a lower layer damping sponge (5) and a bottom plate (9) of the flight controller are sequentially arranged from top to bottom; the IMU module (3) is wrapped between the upper layer damping sponge (2) and the lower layer damping sponge (5);
the gesture resolving method takes a space gesture vector as a control object and specifically comprises the following steps:
1) Error correction and normalization are carried out on the original triaxial accelerometer data, and the corrected triaxial accelerometer data are recorded as: aXN, aZN;
2) Error correction and normalization are carried out on the original triaxial magnetometer data, and the corrected triaxial magnetometer data are recorded as: mXN, mYN, mZN;
3) Fusing the two groups of corrected data in the steps 1) and 2) to obtain a first posture matrix;
4) Performing error correction on the original triaxial gyroscope data to obtain corrected triaxial gyroscope data, and recording the corrected triaxial gyroscope data as gX, gY and gZ;
fusing the corrected triaxial gyroscope data with a third gesture matrix obtained in the previous control period to obtain a second gesture matrix; the initial value of the third gesture matrix is equal to the value of the first gesture matrix obtained in the first control period;
5) Fusing the first gesture matrix and the second gesture matrix to obtain a third gesture matrix of the control period, namely a fused direction cosine matrix;
in the step 3), the first gesture matrix is recorded as:
wherein, the third row element is:
a31＝aXN，a32＝aYN，a33＝aZN；
the first row elements are:
wherein v is a verticality factor, v= mXN × aXN + mYN × aYN + mZN × aZN;
the second row of elements is:
a21＝a13*a32-a12*a33
a22＝a11*a33-a31*a13
a23＝a31*a12-a11*a32；
in the step 4), the second gesture matrix is recorded as:
the third pose matrix is noted as:
the calculation process of the second gesture matrix is as follows:
firstly, the corrected triaxial gyroscope data are multiplied by an updating period T respectively to obtain triaxial angle vectors alpha X, alpha Y and alpha Z:
αX＝gX*T
αY＝gY*T
αZ＝gZ*T
calculating quaternion update factors (r 0, r1, r2, r 3):
r0＝1-sSquareSum/8
wherein squaresum=αx 2 +αY 2 +αZ 2
Converting a third gesture matrix obtained in the last control period into quaternions:
if q0+.0, then there is:
if q0=0, then there are:
normalizing the quaternion:
updating quaternion:
q0＝q0N*r0-q1N*r1-q2N*r2-q3N*r3
q1＝q1N*r0+q0N*r1-q3N*r2+q2N*r3
q2＝q2N*r0+q3N*r1+q0N*r2-q1N*r3
q3=q3nr0-q2nr1+q1nr2+q0nr3 normalized the updated quaternion to obtain new q0n, q1n, q2N and q3N; convert it into a second pose matrix:
b11＝q0N 2 +q1N 2 -q2N 2 -q3N 2
b12＝2*q1N*q2N-2*q0N*q3N
b13＝2*q1N*q3N+2*q0N*q2N
b21＝2*q1N*q2N+2*q0N*q3N
b22＝q0N 2 -q1N 2 +q2N 2 -q3N 2
b23＝2*q2N*q3N-2*q0N*q1N
b31＝2*q1N*q3N-2*q0N*q2N
b32＝2*q2N*q3N+2*q0N*q1N
b33＝q0N 2 -q1N 2 -q2N 2 +q3N 2 ；
in the step 5), the third posture matrix calculation method of the control period is as follows:
calculating a deviation vector of the corrected triaxial accelerometer data and the third row element of the second posture matrix:
dX3＝aXN-b31
dY3＝aYN-b32
dZ3＝aZN-b33
multiplying by a scaling factor m3 to obtain a vector for correction:
cX3＝dX3*m3
cY3＝dY3*m3
cZ3＝dZ3*m3
calculating a vector after the corrected triaxial accelerometer data and the third row of the second posture matrix are fused:
vX3＝b31+cX3
vY3＝b32+cY3
vZ3＝b33+cZ3
normalizing the fused vector:
calculating a deviation vector of the corrected triaxial magnetometer data and the first row element of the second posture matrix:
dX1＝mXN-b11
dY1＝mYN-b12
dZ1＝mZN-b13
multiplying by a scaling factor m1 yields the vector for correction:
cX1＝dX1*m1
cY1＝dY1*m1
cZ1＝dZ1*m1
calculating a vector after the corrected triaxial magnetometer data and the first row of the second posture matrix are fused:
vX1＝b11+cX1
vY1＝b12+cY1
vZ1＝b13+cZ1
orthogonalization of magnetometer fusion vectors:
vX1V＝vX1-k*vX3N
vY1V＝vY1-k*vY3N
vZ1V＝vZ1-k*vZ3N
wherein k is a squaring factor; k=vx1×vx3n+vy1×vy3n+vz1×vz3n;
normalizing the normalized magnetometer fusion vector:
obtaining a first row element and a third row element of a third gesture matrix:
c11＝vX1N，c12＝vY1N，c13＝vZ1N；
c31＝vX3N，c32＝vY3N，c33＝vZ3N；
solving a second row element of the third posture matrix according to the orthogonal characteristic of the direction cosine matrix:
c21＝c13*c32-c12*c33
c22＝c11*c33-c31*c13
c23＝c31*c12-c11*c32。
2. the unmanned aerial vehicle flight controller according to claim 1, wherein the flight controller top cover (1), the upper shock-absorbing sponge (2), the IMU module (3), the lower shock-absorbing sponge (5) and the flight controller bottom plate (9) are sequentially arranged and connected from top to bottom, and the connecting media are double-sided non-conductive adhesive.
3. The unmanned aerial vehicle flight controller according to claim 2, wherein the areas of the upper layer damping sponge (2) and the lower layer damping sponge (5) are both larger than the area of the IMU module (3); the IMU module (3) is arranged at the center position between the upper layer damping sponge (2) and the lower layer damping sponge (5); the upper layer damping sponge (2) is connected with the lower layer damping sponge (5) at the part corresponding to the outside of the IMU module (3); the connecting medium is double-sided non-conductive adhesive.
4. The unmanned aerial vehicle flight controller according to claim 1, further comprising a built-in power supply provided on the flight controller floor (9);
the built-in power supply comprises a switching regulator and a linear regulator; the input end of the switching voltage stabilizer is connected with the battery through a battery connecting wire, the output end of the switching voltage stabilizer is connected with the linear voltage stabilizer, and the output end of the linear voltage stabilizer supplies power for the internal equipment of the flight controller.
5. The unmanned aerial vehicle flight controller of claim 4, wherein the switching regulator is a Buck DC-DC switching regulator TPS54160; the linear voltage stabilizer is an SPX1117M3 linear voltage stabilizer; the 5V output connection of Buck DC-DC switching regulator TPS54160 is connected to linear regulator SPX1117M3 by an internal line, outputting 3.3V direct current voltage;
the input end of the SPX1117M3 linear voltage stabilizer, namely a 5V output connecting line is connected with a 4.7uF/10V ceramic capacitor in parallel, and a 100uF/10V low ESR ceramic capacitor and a 100nF/16V ceramic capacitor are connected between the output end of the SPX1117M3 linear voltage stabilizer and the power supply end of the internal equipment of the flight controller in parallel.
6. The unmanned aerial vehicle flight controller of claim 5, further comprising an electronic governor signal output socket board (6) and an external sensor and peripheral module signal socket board (7);
an electronic speed regulator signal output socket board (6) and an external sensor and external module signal socket board (7); the bottoms of the two parts are vertically connected with the bottom plate (9) of the flight controller, and the connection points are respectively positioned at the edges of two opposite sides of the bottom plate (9) of the flight controller;
the tops of the electronic speed regulator signal output socket board (6) and the external sensor and external module signal socket board (7) are vertically connected with the top cover (1) of the flight controller, and the connection points are respectively positioned at the edges of two opposite sides of the top cover (1) of the flight controller;
the connecting medium adopts solid solder paste.
7. The unmanned aerial vehicle flight controller of claim 6, wherein the battery connection line is divided into two segments, the front section is positioned between the battery and the flight controller and is a silica gel wire, and is connected with the flight controller through an external sensor and a peripheral module signal socket board (7); the second section is positioned on a printed circuit board in the flight controller, and a 500mA self-recovery fuse is connected in series on the second section of wire; the current output of the 500mA self-healing fuse is also connected to the common ground inside the flight controller via a 4.7uF/50V low ESR ceramic capacitor.
8. The unmanned aerial vehicle flight controller according to any one of claims 1 to 7, wherein a printed circuit board and a CPU (11) are provided on the flight controller base plate (9); the CPU is connected with the printed circuit board through an electronic circuit; the IMU module (3) and the flight controller bottom plate (9) are respectively provided with an IMU module 14P connected with a flip type FPC base (4) and a main control bottom plate 14P connected with a flip type FPC base (10); the IMU module (3) is connected with the bottom plate (9) of the flight controller through an FPC base and an FPC flexible flat cable.
9. The unmanned aerial vehicle flight controller of claim 1, after performing the attitude resolution, performing the attitude control by:
extracting a balance vector B and a heading vector Y from the third gesture matrix;
wherein the balance vector is a vector formed by the elements of the third row in the third gesture matrix: (c 31, c32, c 33)
The heading vector is a vector formed by elements of a first row and a first column of the third gesture matrix and elements of a first column of a second row: (c 11, c 21);
controlling the balance of the machine body by utilizing the difference between the expected balance vector and the actual balance vector; when the expected balance vector is not equal to the actual balance vector, calculating a balance vector difference; converting the balance vector difference into a motor matrix control quantity, and finally decoupling the motor matrix control quantity into control quantity of each motor;
controlling the body heading by utilizing the difference between the expected heading vector and the actual heading vector; when the expected heading vector is not equal to the actual heading vector, calculating a heading vector difference; and then converting the course vector difference into motor matrix control quantity, and finally decoupling the motor matrix control quantity into control quantity of each motor.
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