UAV flight control refers to the flight control system of UAV, which is mainly used to maintain the normal flight attitude of UAV. The main function of this system is to stabilize the flight attitude of the drone and control the autonomous or semi-autonomous flight of the drone. With the development of intelligence, the current UAV is not limited to the traditional fixed-wing form, but has emerged in various forms such as four-axis, six-axis, single-axis, and vector control. The flight control system is the core system of the UAV to complete the entire flight process such as take-off, air flight, mission execution and return**, which is equivalent to the brain of the UAV.
The flight control generally includes three parts: sensors, airborne computers and servo actuation equipment, and the functions realized are mainly three categories: UAV attitude stabilization and control, UAV mission equipment management and emergency control. Specifically, the flight controller perceives the attitude and position information of the drone through various sensors (such as gyroscope, accelerometer, magnetometer, etc.), and then calculates and adjusts the attitude and position of the drone through control algorithms and software programs, so that the drone can fly stably. At the same time, the flight controller can also control the mission equipment (such as cameras, communication equipment, etc.) of the UAV through the mission equipment management function to complete various tasks.
Common drone flight control sensors
Gyroscope (angular velocity meter):
Based on the theory of conservation of angular momentum, the angular motion detection device is used to detect the momentum of the high-speed rotating body about one or two axes of the rotation axis around the relative inertial space. The common areas of use of gyroscopes are as follows:
Accelerometer:
Accelerometer is a sensor that can measure acceleration, and the sensor uses Newton's second law to obtain the acceleration value by measuring the inertial force on the mass during acceleration. The basic principles of accelerometers are as follows:
Inertial Measurement Unit (IMU):
An inertial measurement unit is a device that measures the three-axis attitude angle (or angular rate) and acceleration of an object. Generally, an IMU contains three single-axis accelerometers and three single-axis gyroscopes, the accelerometer detects the acceleration signal of the object in the carrier coordinate system, and the gyroscope detects the angular velocity signal of the carrier relative to the navigation coordinate system, measures the angular velocity and acceleration of the object in three-dimensional space, and calculates the attitude of the object.
Barometer:
This is a device that detects the current altitude according to the atmospheric pressure detection.
Magnetometer (electronic compass):
Magnetometer (magnetic, M-sensor) is also called geomagnetism, magnetic inductor, can be used to test the strength and direction of the magnetic field, locate the orientation of the device, the principle of the magnetometer is similar to the principle of the compass, can measure the current equipment and the four directions of the southeast, northwest and the angle.
Satellite Positioning System:
GPS is the abbreviation of Global Positioning System in English. GPS started as a project in the United States in 1958 and was put into use in 1964. In the 70s of the 20th century, the US Army, Navy and Air Force jointly developed a new generation of satellite positioning system GPS. The main purpose is to provide real-time, all-weather and global navigation services for the three major fields of land, sea and air, and for some military purposes such as intelligence gathering, nuclear explosion monitoring and emergency communications, after more than 20 years of research and experiments, costing 30 billion US dollars, by 1994, the global coverage of up to 98 percent of the 24 GPS satellite constellation has been deployed.
RTK (Carrier Phase Difference Technique):
The differential method of processing the carrier phase observations of the two measuring stations in real time, and the carrier phase collected by the base station is sent to the user receiver for differential coordinates.
Ultrasonic Sensors:
Ultrasonic sensors are sensors that convert ultrasonic signals into other energy signals, usually electrical signals. Ultrasonic wave is a mechanical wave with a vibration frequency higher than 20kHz, which has the characteristics of high frequency, short wavelength, small diffraction phenomenon, good directionality, and can become a ray and propagate directionally. Ultrasonic waves have a great ability to penetrate liquids and solids, especially in solids where sunlight is opaque. Ultrasonic waves will produce significant reflections when they encounter impurities or interfaces, forming reflected echoes, and Doppler effects can occur when they hit active objects.
Optical Flow Sensor:
Optical flow sensor is a kind of sensor that measures the flow change of light reflected by the surface of an object, which is widely used in aviation, aerospace, robotics and other fields. Optical flow sensors use the optical flow method to measure the motion state of an object, that is, to infer the motion state of an object by measuring the change in the optical flow field between successive frames. Specifically, optical flow sensors use the optical flow method to calculate the velocity of the pixels by measuring the displacement of pixels between successive frames, thereby inferring the speed and direction of movement of the surface of an object.
MEMS system:
Micro-electro-mechanical system (MEMS), also known as micro-electro-mechanical system, microsystem, micro-machine, etc., refers to high-tech devices with a size of a few millimeters or even smaller.
Stance:
Describes the angular position relationship between a rigid body coordinate system and a reference coordinate system. That is, pitch, yaw, roll.
Algorithm:
That is, the attitude conversion method, the controller, how to collect the attitude sensor data, and fuse it, and judge its own motion state according to the fused data.
PID Control:
After the flight controller decodes the data of the attitude sensor, it immediately adjusts the attitude accordingly based on the result of the fusion of the two, and controls the ESC through the signal, which is called PID control. p (proportional) i (integral) d (differential).
Filtering algorithm:
Kalman filtering is an algorithm that uses the linear system equation of state to make an optimal estimation of the system state through the system input and output observation data.