1. Introduction
In the early stage of UAV development, R&D focused mainly on aerodynamic structure and mechanical performance, pursuing stable, fast and high-altitude flight capabilities. With the rapid iteration of chips, artificial intelligence and big data technologies, UAVs have evolved toward intelligence, terminalization and cluster operation. The intervention of electronic information and microelectronics technology has greatly reduced the threshold of UAV application, enabling civilian consumers to achieve stable flight with simple operation.
Undoubtedly, the rapid upgrading of flight control technology is the core driving force for the comprehensive popularization and performance leap of UAVs in the past decade.
2. What is a Flight Control System?
The Flight Control System (FCS) is regarded as the brain of UAVs. It undertakes core functions including real-time perception of aircraft attitude, data calculation, logic judgment and instruction output.
The flight, hover, attitude transformation and trajectory adjustment of multi-rotor UAVs all follow a unified logic: various sensors collect real-time attitude and position data and transmit them to the flight controller. After high-frequency operation and analysis, the flight controller outputs control commands to the actuator, so as to adjust motor speed and complete stable flight control.
Similar to the human brain, the flight controller forms a closed-loop control loop of “perception-calculation-execution-feedback”, which is the most core hardware and software system to ensure stable and safe flight of UAVs.
3. Flight Principle and Control Logic of Quadrotor UAVs
3.1 Overall Structural Composition
A standard quadrotor UAV consists of four core modules: detection module, control module, execution module and power supply module. The fuselage adopts a lightweight and high-strength carbon fiber cross symmetrical rigid structure. Four rotor motors are installed at the four ends of the fuselage, providing all flight power for the UAV.
The flight attitude and position of the quadrotor are completely controlled by adjusting the speed of the four rotors. To offset rotational torque and avoid autorotation of the fuselage, the front and rear rotors rotate clockwise, while the left and right rotors rotate counterclockwise, realizing mutual torque cancellation under hovering state.
The quadrotor UAV is a typical under-actuated, strongly coupled nonlinear system with 6-degree-of-freedom motion output controlled by 4 groups of rotor speeds. There is a strong coupling relationship between attitude motion and translational motion, which puts forward high requirements for the real-time performance and accuracy of flight control algorithms.
3.2 Five Basic Flight States
Hovering: The four rotors run at the same speed, the total lift is balanced with the UAV’s gravity, and the overall torque is zero, realizing stable static hovering in the air.
Vertical Motion: Synchronously increase or decrease the speed of all four rotors. Increased total lift enables vertical ascent, while reduced total lift causes vertical descent.
Roll Motion: Keep the speed of front and rear rotors unchanged, adjust the speed of left and right rotors to form a lift difference, generate lateral torque, and realize left and right tilt and translation of the fuselage.
Pitch Motion: Keep the speed of left and right rotors unchanged, adjust the speed of front and rear rotors to form a front-rear lift difference, and realize forward and backward tilt and flight of the fuselage.
Yaw Motion: Adjust the speed difference between clockwise and counterclockwise rotor groups to break the torque balance, generate rotational torque around the central axis of the fuselage, and realize left and right deflection rotation.
3.3 Autonomous Flight and Stable Control Logic
Precise trajectory tracking is the basic condition for UAV autonomous flight. Affected by strong coupling dynamics, model parameter errors and external wind field interference, stable attitude control is the primary premise of accurate trajectory control.
The flight control system adopts a dual-loop nested control framework: the inner loop realizes high-frequency stable control of three attitude angles (roll, pitch, yaw), and the outer loop completes low-frequency trajectory and position tracking. The fast-response inner loop suppresses external interference and attitude jitter, while the outer loop realizes long-distance accurate route navigation.
To cope with complex environmental interference and sensor noise, the flight control system is equipped with disturbance observers and adaptive compensation algorithms to improve system robustness, ensuring continuous and stable attitude tracking and trajectory execution in complex scenarios.
4. Core Components and Sensor Functions of Flight Control System
4.1 IMU Inertial Measurement Unit (Core Attitude Perception)
IMU is the most fundamental sensing unit of the flight control system, composed of a 3-axis gyroscope, 3-axis accelerometer, 3-axis geomagnetic sensor and barometer, responsible for full-dimensional motion state perception.
3-axis Gyroscope: Based on the gyroscopic effect, it measures the angular velocity of the UAV on the X, Y, and Z axes in real time, captures attitude change trends, and provides core data for attitude stability correction.
3-axis Accelerometer: Perceives the linear acceleration of the three axes of the fuselage, judges the motion state such as acceleration, deceleration and static state, and assists in solving the attitude tilt angle.
Geomagnetic Sensor: Equivalent to an electronic compass, it calibrates the UAV’s heading angle to solve the yaw drift problem of inertial sensors.
Barometer: Measures atmospheric pressure changes to realize high-precision relative altitude positioning and fixed-height flight, making up for the low accuracy of GPS altitude measurement.
The IMU forms a 10 Hz high-frequency closed-loop control loop with the flight controller, which dynamically compensates attitude offset in real time to prevent rollover and crash caused by attitude imbalance.
4.2 Airspeed Sensor
The airspeed sensor calculates the real-time airspeed by detecting the pressure difference between static atmospheric pressure and oncoming wind pressure. Different from GPS ground speed, it reflects the relative motion speed between the UAV and the air, which is the key data to judge takeoff lift and stable flight, effectively avoiding flight failure caused by headwind or tailwind interference.
4.3 GPS/ Beidou Positioning Module
Based on satellite trilateral positioning principle, GPS/Beidou obtains the UAV’s absolute longitude, latitude, ground speed and altitude information. The open and mature positioning system can achieve meter-level or even sub-meter-level positioning accuracy in open environments, providing absolute position reference for route planning, fixed-point hovering and return-to-home flight.
GPS is susceptible to occlusion by buildings, trees and tunnels, resulting in signal loss and drift, which is one of the main causes of UAV flying away and crashing in complex scenarios.
4.4 Ground Station & Data Transmission Radio
The ground station is the human-computer interaction and command scheduling terminal of the UAV system. It completes flight route planning, parameter setting, task deployment and real-time flight status monitoring through supporting software.
The data transmission radio is the communication bridge between the ground station and the UAV. Adopting mainstream frequency bands such as 433 MHz, it features strong penetration and long transmission distance. It realizes two-way transmission of ground commands and UAV flight data (altitude, speed, attitude, voltage), supporting real-time route modification and emergency control during flight.
5. Core Functions of Modern Intelligent Flight Control System
5.1 Full-State Accurate Perception
The flight control system can monitor 15 core flight state quantities in real time, including 3D position, 3D speed, 3D acceleration, 3-axis angle and 3-axis angular velocity. Through multi-sensor data fusion, it eliminates the errors of single sensors such as IMU, GPS and barometer, and outputs high-reliability flight state data.
5.2 Multi-Sensor Integrated Navigation
Modern high-end flight control systems expand visual sensors and ultrasonic sensors on the basis of traditional inertial navigation and satellite navigation. Binocular vision realizes 3D positioning, speed measurement and obstacle avoidance; ultrasonic assists in high-precision low-altitude fixed height. The redundant IMU and geomagnetic system automatically switch working channels in case of sensor failure, greatly improving flight reliability. It realizes seamless switching of stable flight in GPS-strong open scenes and GPS-lost indoor and sheltered scenes.
5.3 High-Robustness Flight Control
With optimized control algorithms, the flight control system has high-precision control capabilities for hovering, low-speed cruise and high-speed flight. At the same time, it has strong anti-interference and fault tolerance. It can quickly recover stable attitude in extreme scenarios such as propeller damage, external impact and sudden load change, effectively improving flight safety.
5.4 Intelligent Fault Diagnosis and Early Warning
The flight control system monitors real-time parameters such as voltage, current, temperature, motor speed and vibration. Based on deep learning and pattern recognition algorithms, it realizes intelligent diagnosis of potential faults such as IMU drift, communication failure and power abnormality. It supports early warning and emergency attitude protection, greatly reducing the probability of flight accidents.
6. Summary
The UAV flight control system relies on the collaborative work of IMU, satellite positioning, airspeed measurement, communication and other multi-sensor modules. Through high-frequency closed-loop control and multi-source data fusion algorithms, it realizes basic functions such as attitude stabilization, fixed-height hovering and trajectory tracking, as well as advanced intelligent functions such as redundant navigation, anti-interference flight and fault self-diagnosis.
The iteration of flight control sensing and control algorithms is the core driving force for UAVs to move from simple manual flight to fully autonomous intelligent flight, and is the key foundation for UAVs to be widely used in aerial photography, surveying, mapping and industrial inspection scenarios.
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