UAV Flight Control Software: Architecture and Safety

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Robot Control Software — Ch.11: UAV Flight Control Software [EN]

STATERA Library · Series 08 · Volume 04 · Chapter 11 · EN Source: https://github.com/Statera-Library/08_Vol_04_Robot_Control_Software/blob/main/Chapter_11_UAV_Flight_Control_Software/Chapter_11_UAV_Flight_Control_Software_EN.md Volume 04 Robot Control Software 11. UAV Flight Control Software 11.01 UAV Flight Control SW Architecture Overview A UAV flight control software architecture is the real-time computational framework that transforms pilot commands, autonomous mission objectives, and sensor measurements into safe actuator commands. It forms the control core between the aircraft hardware and higher-level autonomy software, continuously coordinating estimation, guidance, control, actuator allocation, health monitoring, and safety functions under strict timing constraints. At the lowest software boundary, the hardware abstraction and device-driver layer interfaces with inertial sensors, GNSS receivers, barometers, air-data sensors, magnetometers, motor controllers, servos, and communication buses. This layer converts device-specific measurements into standardized data structures while providing deterministic actuator interfaces, allowing the flight-control algorithms to remain largely independent of individual sensor and actuator implementations. Sensor acquisition is normally organized around multiple update rates because UAV sensors operate at significantly different frequencies. IMU measurements may arrive at hundreds or thousands of samples per second, while GNSS, barometric, airspeed, or payload measurements operate more slowly. Timestamping, synchronization, calibration, filtering, validity checking, and buffering therefore become fundamental architectural services before measurements enter estimation and control functions. The state-estimation layer converts these heterogeneous measurements into a coherent representation of aircraft motion. Typical estimated states include attitude, angular velocity, position, velocity, altitude, acceleration, sensor biases, and selected environmental variables. Attitude and heading reference algorithms and more comprehensive sensor-fusion estimators provide the feedback information required by the control loops, separating noisy physical measurements from usable control states. Flight-control functions are commonly implemented as cascaded loops with progressively different dynamic bandwidths. Fast inner loops regulate angular rates and attitude, while slower outer loops regulate altitude, velocity, and position. Each outer controller generates references for the controller beneath it, producing a hierarchical path from trajectory objectives to forces, moments, and finally actuator commands while preserving manageable control-loop complexity. The control architecture must explicitly separate guidance objectives from stabilization. Guidance determines where the aircraft should move by generating position, velocity, heading, altitude, or trajectory references. Stabilization determines how the aircraft physically follows those references despite aerodynamic disturbances, modeling uncertainty, actuator limitations, and sensor noise. This separation enables navigation algorithms to evolve without unnecessarily modifying safety-critical low-level control logic. Control allocation translates desired forces and moments into commands appropriate for the aircraft configuration. A multirotor uses a mixing relationship to distribute thrust and torque among individual propulsion units, whereas fixed-wing aircraft coordinate throttle and aerodynamic control surfaces. VTOL platforms require both mechanisms and additional transition logic because actuator effectiveness changes substantially between hovering, transitional, and wing-borne flight regimes. A flight mode and state-management layer coordinates these control functions according to operational context. Typical states include initialization, standby, arming, takeoff, manual or assisted flight, autonomous mission execution, landing, degrad...

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