Control method of unmanned aerial vehicle automatic control system

Abstract

The invention provides a control method of an unmanned aerial vehicle automatic control system. The unmanned aerial vehicle automatic control system comprises a flight control unit which comprises a first flight control module, a second flight control module,..., and an nth flight control module; the flight control arbitration master control equipment is connected with each flight control module; the CAN bus is connected with the flight control arbitration general control equipment; the CAN to PWM / SPI / IIC / UART module is connected with the CAN bus; the electric adjusting module is connected with a PWM interface on the CAN to PWM / SPI / IIC / UART module; the control method comprises the steps that S1, each flight control module calculates corresponding electronic speed controller and steering engine data, the electronic speed controller and steering engine data are sent to the flight control arbitration general control equipment through the CAN bus, and the flight control arbitration general control equipment selects one piece of data in the flight control module through an arbitration algorithm to carry out actual output.

Description

Technical Field

[0001] The present invention belongs to the field of electronic information technology, and in particular relates to a control method for an unmanned aerial vehicle automatic control system. Background Art

[0002] Unmanned aircraft, also known as "drones", are unmanned aircraft that are controlled by radio remote control equipment and self-contained program control devices, or are operated completely or intermittently autonomously by onboard computers. At present, with the development of science and technology, drone technology is becoming more and more mature, and drones are widely used for their fast speed and flexible operation.

[0003] The flight control system of a drone is the core control brain of the drone, responsible for the control of the entire drone flight process. Once a failure occurs, it will cause a crash or very serious consequences. Therefore, it is very necessary to perform redundant backup of the drone's flight control system. Conventional backup is divided into dual redundant hot backup, which has the defects of slow speed and poor stability. Summary of the invention

[0004] The present invention provides a control method for an unmanned aerial vehicle automatic control system, which can effectively solve the above problems.

[0005] The present invention is achieved in that: The present invention provides a control method for an unmanned aerial vehicle automatic control system, the unmanned aerial vehicle automatic control system comprising: a flight control unit, comprising a first flight control module, a second flight control module ... and an nth flight control module; a flight control arbitration master control device, which is respectively connected to each flight control module; a CAN bus connected to the flight control arbitration master control device; a CAN to PWM / SPI / IIC / UART module connected to the CAN bus; an electric control module, connected to a PWM interface on the CAN to PWM / SPI / IIC / UART module; a steering gear module connected to the electric control module; The control method comprises: S1, each flight control module respectively calculates the corresponding electric speed controller and servo data, and sends them to the flight control arbitration master control device through the CAN bus. The flight control arbitration master control device selects one data in the flight control module for actual output through the arbitration algorithm.

[0006] As a further improvement, in step S1, each flight control module respectively calculates the corresponding electric speed controller and servo data, and sends them to the flight control arbitration master control device through the CAN bus. The flight control arbitration master control device selects one data in the flight control module for actual output through the arbitration algorithm, which specifically includes: S11, define the ESC of each flight control module as E1f1, E1f2...E1f n, n is the number of ESCs, and then the first summation is performed ΣE1f1+E1f2+.....+E1f n And the average value of the first summation △E A =ΣE1f1+E1f2+.....+E1f n / n; S12, determine the actual error value In= 100*(E1f1-△E A ) / △E A , when In falls within the error threshold of ±Ith(%), it is qualified data, and Ith is the set error threshold; S13, taking out qualified data to perform secondary summation and secondary average calculation; S14, then perform a second round of error calculation, and output the flight control data with the smallest absolute value of In in the second round as the final data of the drone.

[0007] As a further improvement, each flight control module includes a barometer, a gyroscope, an accelerometer, and a magnetometer; and the control method further includes: S31, during the flight, obtaining flight control data in each flight control module through the CAN bus, wherein the flight control data includes barometer data, gyroscope data, accelerometer data, and magnetometer data; S32, voting and screening the flight control data in each flight control module at regular intervals, and if there is unqualified flight control data in the voting result, marking the flight control module as a fault state; S33, determine whether the flight control module corresponding to the fault state is in the operating state. If so, quickly switch the fault-free flight control module to the operating state, take over the control of the drone, trigger the intelligent landing mode, terminate the flight mission and return to the home point for maintenance.

[0008] As a further improvement, after step S33, the following is further included: S34, when at least one flight control module is in standby mode, the flight mission continues; otherwise, the intelligent landing mode is triggered, the flight mission is terminated and the flight mission is returned to the home point for maintenance.

[0009] As a further improvement, in step S32, voting and screening the flight control data in each flight control module at a regular interval, if there is unqualified flight control data in the voting result, marking the flight control module as a fault state specifically includes: S321, define the flight control data in each flight control module as follows: , where D1, D2, and D3 are the flight control data of the first flight control module, the second flight control module, and the third flight control module, respectively, and d j1 , d j2 , d j3 , dj4 Represent barometer data, gyroscope data, accelerometer data, and magnetometer data respectively; S322, calculate the difference of flight control data by formula: ; S323, when the difference Δd j When the preset first threshold is exceeded, the system determines that the sensor data is abnormal and triggers the voting screening mechanism, otherwise it ends; S324, the voting screening mechanism is as follows: , when δ ij If it is greater than the second threshold, it is determined that the j sensor data d of the i flight control module ij Exception; otherwise terminate.

[0010] As a further improvement, each flight control module includes a barometer; and the control method further includes: S41, obtain the real-time wind speed V during flight through the barometer w ; S42, the mathematical model of the UAV speed is established as follows: , where u is the motor speed, v is the instantaneous speed of the drone, and k1, k2 and k3 are model parameters; S43, introduce PID control law to make the instantaneous speed v of the UAV track the expected value v d : , where K p is the proportional gain, K i is the integral gain, and K d is the differential gain; S44, the above PID control law is introduced, and the control model is finally obtained as follows: .

[0011] As a further improvement, the real-time wind speed V during flight is obtained by using a barometer. w Specifically include: obtaining the pressure gradient of the drone through three barometers set at intervals and through the pressure gradient Estimated real-time wind speed V w .

[0012] As a further improvement, the pressure gradient of the drone is obtained by three barometers arranged at intervals. and through the pressure gradient Estimated real-time wind speed V w Specifically include: According to the fluid mechanics model, the wind speed V 风 satisfy: , where K 风 is the proportionality constant; Obtain the air pressure p1, p2, p3 of three different barometers in real time; The pressure gradient is obtained according to the formula : , where Δp is the air pressure between the two barometers and Δx is the distance between the two barometers.

[0013] The beneficial effects of the present invention are: The control method of the automatic control detection system of the unmanned aerial vehicle provided by the present invention proposes a multi-flight control redundancy technology, and manages n flight control modules through the flight control arbitration master control device. Each flight control module can operate independently, and the arbitration master control device determines the electric adjustment servo of the unmanned aerial vehicle, which can effectively avoid or reduce the occurrence of the unmanned aerial vehicle out of control phenomenon caused by the failure of the flight control system, effectively ensure the flight safety of the unmanned aerial vehicle, change the defects of the conventional flight control such as poor stability, and solve the emergency backup problem of the unmanned aerial vehicle flight control system. Furthermore, the present invention can also solve the problem that the fixed-wing unmanned aerial vehicle has extremely large vibration when using an oil engine, and the sensors of individual flight control modules will have inaccurate data due to factors such as resonance, and a single flight control needs to spend a lot of costs on shock absorption. The multi-flight control solution can solve this problem. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0015] Figure 1 It is an architecture diagram of the automatic control system of the unmanned aerial vehicle provided by an embodiment of the present invention.

[0016] Figure 2 It is an architectural diagram of the local structure of the UAV automatic control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0018] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0019] Reference Figure 1-2 As shown, the embodiment of the present invention provides a control method for an automatic control system of an unmanned aerial vehicle, the automatic control system of the unmanned aerial vehicle comprises: a flight control unit 10, which comprises a first flight control module 101, a second flight control module 102... and an nth flight control module; a flight control arbitration master control device 20, which is respectively connected to each flight control module; a CAN bus, which is connected to the flight control arbitration master control device 20; a CAN to PWM / SPI / IIC / UART module 14 connected to the CAN bus; an electric adjustment module 15, which is connected to the PWM interface on the CAN to PWM / SPI / IIC / UART module 14; and a servo module 18 connected to the electric adjustment module 15. The system proposes a multi-flight control redundancy technology, which can effectively avoid or reduce the occurrence of unmanned aerial vehicle out-of-control phenomena caused by failures in the flight control system, effectively ensure the flight safety of the unmanned aerial vehicle, change the defects of poor stability of conventional flight control, and solve the emergency backup problem of the flight control system of the unmanned aerial vehicle.

[0020] The remote controller or the data transmission ground station sends a control command, which is parsed by the flight control arbitration master control device 20 and converted into a CAN command and distributed to each flight control module. Each flight control module adjusts the flight speed and flight attitude according to the control command, and converts it into actual values ​​of the electric adjustment module 15, the servo module 18, etc., and sends it back to the flight control arbitration master control device 20 through CAN for data fusion processing.

[0021] The UAV automatic control system also includes a current sensor 19, which is connected to the ADC interface on the CAN to PWM / SPI / IIC / UART module 14 to measure the current i output by the electric adjustment module 15 to the servo module 18; a BMS 11, an oil level gauge 12, an RTK 13, and various sensors connected to the flight control unit 10 through the CAN bus. The above structure is not limited and also includes other modules required for the UAV, such as a BMS 16 and a power module 17.

[0022] The control method comprises: S1, each flight control module respectively calculates the corresponding electric speed controller and servo data, and sends them to the flight control arbitration master control device 20 through the CAN bus. The flight control arbitration master control device 20 selects one data in the flight control module for actual output through the arbitration algorithm.

[0023] As a further improvement, in other embodiments, in step S1, each flight control module respectively calculates its corresponding electric speed controller and servo data, and sends them to the flight control arbitration master control device 20 through the CAN bus. The flight control arbitration master control device 20 selects one data in the flight control module for actual output through an arbitration algorithm, specifically including: S11, define the ESC of each flight control module as E1f1, E1f2...E1f n , n is the number of ESCs, and then the first summation is performed ΣE1f1+E1f2+.....+E1f n And the average value of the first summation △E A =ΣE1f1+E1f2+.....+E1f n / n; S12, determine the actual error value In= 100*(E1f1-△E A ) / △E A , when In falls within the error threshold of ±Ith(%), it is qualified data, and Ith is the set error threshold; S13, taking out qualified data to perform secondary summation and secondary average calculation; S14, then perform a second round of error calculation, and output the flight control data with the smallest absolute value of In in the second round as the final data of the drone. In other embodiments, further, data with large errors can be eliminated, and then averaged to output as the final control data.

[0024] As a further improvement, in other embodiments, each flight control module includes a barometer, a gyroscope, an accelerometer, and a magnetometer; and the control method further includes: S31, during the flight, obtaining flight control data in each flight control module through the CAN bus, wherein the flight control data includes barometer data, gyroscope data, accelerometer data, and magnetometer data; S32, voting and screening the flight control data in each flight control module at regular intervals, and if there is unqualified flight control data in the voting result, marking the flight control module as a fault state; S33, determine whether the flight control module corresponding to the fault state is in the operating state. If so, quickly switch the fault-free flight control module to the operating state, take over the control of the drone, trigger the intelligent landing mode, terminate the flight mission and return to the home point for maintenance.

[0025] As a further improvement, in other embodiments, after step S33, the method further includes: S34, when at least one flight control module is in standby mode, the flight mission continues; otherwise, the intelligent landing mode is triggered, the flight mission is terminated and the flight mission is returned to the home point for maintenance.

[0026] As a further improvement, in step S32, voting and screening the flight control data in each flight control module at a regular interval, if there is unqualified flight control data in the voting result, marking the flight control module as a fault state specifically includes: S321, define the flight control data in each flight control module as follows: , where D1, D2, and D3 are flight control data of the first flight control module 101, the second flight control module 102, and the third flight control module 103, respectively, and d j1 , d j2 , d j3 , d j4 Represent barometer data, gyroscope data, accelerometer data, and magnetometer data respectively; S322, calculate the difference of flight control data by formula: ; S323, when the difference Δd j When the preset first threshold is exceeded, the system determines that the sensor data is abnormal and triggers the voting screening mechanism, otherwise it ends; S324, the voting screening mechanism is as follows: , when δ ij If it is greater than the second threshold, it is determined that the j sensor data d of the i flight control module ij Through the above voting method, the data of all sub-control modules can be integrated to improve the accuracy of fault identification.

[0027] As a further improvement, in other embodiments, each flight control module includes a barometer; and the control method further includes: S41, obtain the real-time wind speed V during flight through the barometer w ; S42, the mathematical model of the UAV speed is established as follows: , where u is the motor speed, v is the instantaneous speed of the drone, and k1, k2 and k3 are model parameters; S43, introduce PID control law to make the instantaneous speed v of the UAV track the expected value v d : , where K p is the proportional gain, K i is the integral gain, and K d is the differential gain; S44, the above PID control law is introduced, and the control model is finally obtained as follows: The above control can solve the problem of the impact of wind force on flight accuracy during flight and improve the accuracy of flight control.

[0028] As a further improvement, in other embodiments, preferably, the real-time wind speed V during flight is obtained by a barometer. w Specifically include: obtaining the pressure gradient of the drone through three barometers set at intervals and through the pressure gradient Estimated real-time wind speed V w .

[0029] As a further improvement, the pressure gradient of the drone is obtained by three barometers arranged at intervals. and through the pressure gradient Estimated real-time wind speed V w Specifically include: According to the fluid mechanics model, the wind speed V 风 satisfy: , where K 风 is the proportionality constant; Obtain the air pressure p1, p2, p3 of three different barometers in real time; The pressure gradient is obtained according to the formula : , where Δp is the air pressure between the two barometers and Δx is the distance between the two barometers.

[0030] An exemplary calculation with two barometers is as follows: Assume that two of the barometers on the drone are located at the two ends of the wing, with a distance of Δx = 2 meters. The measured air pressures are p1 = 1012 hPa and p2 = 1010 hPa respectively. Then the pressure gradient is: .

[0031] Assuming the proportional constant k = 0.5 m / s / hPa / m, the wind speed is: The negative sign indicates that the direction of the wind speed is opposite to the direction of the pressure gradient. The above method of the present invention can obtain the wind speed of the drone in real time without the need for an additional wind speed sensor or without obtaining the wind speed from the ground.

[0032] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A control method for an unmanned aerial vehicle automatic control system, characterized in that: The unmanned aerial vehicle automatic control system includes: a flight control unit, which includes a first flight control module, a second flight control module... and an nth flight control module; a flight control arbitration master control device, which is respectively connected to each flight control module; a CAN bus connected to the flight control arbitration master control device; a CAN to PWM / SPI / IIC / UART module connected to the CAN bus; an electric control module, which is connected to the PWM interface on the CAN to PWM / SPI / IIC / UART module; and a servo module connected to the electric control module; The control method comprises: S1, each flight control module respectively calculates the corresponding electric speed controller and servo data, and sends them to the flight control arbitration master control device through the CAN bus. The flight control arbitration master control device selects one data in the flight control module for actual output through the arbitration algorithm.

2. The control method of the unmanned aerial vehicle automatic control system according to claim 1, characterized in that: In step S1, each flight control module respectively calculates the corresponding electric speed controller and servo data, and sends the data to the flight control arbitration master control device through the CAN bus. The flight control arbitration master control device selects a data in the flight control module for actual output through the arbitration algorithm, which specifically includes: S11, define the ESC of each flight control module as E1f1, E1f2...E1f n , n is the number of ESCs, and then the first summation is performed ΣE1f1+E1f2+.....+E1f n And the average value of the first summation △E A =ΣE1f1+E1f2+.....+E1f n / n; S12, determine the actual error value In= 100*(E1f1-△E A ) / △E A , when In falls within the error threshold of ±Ith(%), it is qualified data, and Ith is the set error threshold; S13, taking out qualified data to perform secondary summation and secondary average calculation; S14, then perform a second round of error calculation, and output the flight control data with the smallest absolute value of In in the second round as the final data of the drone.

3. The control method of the unmanned aerial vehicle automatic control system according to claim 2, characterized in that: Each flight control module includes a barometer, a gyroscope, an accelerometer, and a magnetometer; and the control method further includes: S31, during the flight, obtaining flight control data in each flight control module through the CAN bus, wherein the flight control data includes barometer data, gyroscope data, accelerometer data, and magnetometer data; S32, voting and screening the flight control data in each flight control module at regular intervals, and if there is unqualified flight control data in the voting result, marking the flight control module as a fault state; S33, determine whether the flight control module corresponding to the fault state is in the operating state. If so, quickly switch the fault-free flight control module to the operating state, take over the control of the drone, trigger the intelligent landing mode, terminate the flight mission and return to the home point for maintenance.

4. The control method of the automatic control system of the unmanned aerial vehicle according to claim 3, characterized in that: After step S33, the method further includes: S34, when at least one flight control module is in standby mode, the flight mission continues; otherwise, the intelligent landing mode is triggered, the flight mission is terminated and the flight mission is returned to the home point for maintenance.

5. The control method of the automatic control system of the unmanned aerial vehicle according to claim 3, characterized in that: In step S32, voting and screening the flight control data in each flight control module at a regular interval, if there is unqualified flight control data in the voting result, marking the flight control module as a fault state specifically includes: S321, define the flight control data in each flight control module as follows: , where D1, D2, and D3 are the flight control data of the first flight control module, the second flight control module, and the third flight control module, respectively, and d j1 , d j2 , d j3 , d j4 Represent barometer data, gyroscope data, accelerometer data, and magnetometer data respectively; S322, calculate the difference of flight control data by formula: ； S323, when the difference Δd j When the preset first threshold is exceeded, the system determines that the sensor data is abnormal and triggers the voting screening mechanism, otherwise it ends; S324, the voting screening mechanism is as follows: , when δ ij If it is greater than the second threshold, it is determined that the j sensor data d of the i flight control module ij Exception; otherwise terminate.

6. The control method of the unmanned aerial vehicle automatic control system according to claim 1, characterized in that: Each flight control module includes a barometer; and the control method further includes: S41, obtain the real-time wind speed V during flight through the barometer w ; S42, the mathematical model of the UAV speed is established as follows: , where u is the motor speed, v is the instantaneous speed of the drone, and k1, k2 and k3 are model parameters; S43, introduce PID control law to make the instantaneous speed v of the UAV track the expected value v d : , where K p is the proportional gain, K i is the integral gain, and K d is the differential gain; S44, the above PID control law is introduced, and the control model is finally obtained as follows: 。 7. The control method of the automatic control system of the unmanned aerial vehicle according to claim 6, characterized in that: The real-time wind speed V during the flight is obtained by using a barometer w Specifically include: obtaining the pressure gradient of the drone through three barometers set at intervals and through the pressure gradient Estimated real-time wind speed V w .

8. The control method of the automatic control system of the unmanned aerial vehicle according to claim 7, characterized in that: The pressure gradient of the drone is obtained by three barometers arranged at intervals. and through the pressure gradient Estimated real-time wind speed V w Specifically include: Wind speed V 风 satisfy: , where K 风 is the proportionality constant; Obtain the air pressure p1, p2, p3 of three different barometers in real time; The pressure gradient is obtained according to the formula : , where Δp is the air pressure between the two barometers and Δx is the distance between the two barometers.

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