A distributed control system with supplemental attitude adjustment including an aircraft control having an engaged state and a disengaged state. The system also including a plurality of flight components and a plurality of aircraft components communicatively connected to the plurality of flight components, wherein each aircraft component is configured to receive an aircraft command and generate a response command directing the flight components as a function of supplemental attitude. The supplemental attitude based at least in part on the engagement datum and generating a supplemental attitude includes choosing a position supplemental attitude if the aircraft control is disengaged and choosing a velocity supplemental attitude if the aircraft control is engaged. In generating the response command, the aircraft attitude is combined with the supplemental attitude to obtain an aggregate attitude, and the aircraft component is configured to generate the response command based on the aggregate attitude.

A dual agent reinforcement learning autonomous system (DARLAS) for the autonomous operation of aircraft and/or provide pilot assistance. DARLAS includes an artificial neural network, safe agent, and cost agent. The safe agent is configured to calculate safe reward Q values associated with landing the aircraft at a predetermined destination or calculated emergency destination. The cost agent is configured to calculate cost reward Q values associated with maximum fuel efficiency and aircraft performance. The safe and cost reward Q values are based on state-action vectors associated with an aircraft, which may include state data and action data. The system may include a user output device that provides an indication of an action to a user. The action corresponds to an agent action having the highest safe reward Q value and the highest cost require Q value. DARLAS prioritizes the highest safe reward Q value in the event of conflict.

A control method includes obtaining one or more attitude parameters of a gimbal of a UAV and adjusting one or more attitude parameters of the UAV according to the one or more attitude parameters of the gimbal. The UAV includes a vehicle body, and a power system and the gimbal that are provided at the vehicle body. The power system includes a motor and a propeller and is configured to provide flight power for the UAV. The gimbal is configured to connect a photographing device to the vehicle body. Adjusting the one or more attitude parameters of the UAV includes adjusting a yaw parameter of the UAV according to the yaw parameter of the gimbal. Adjusting the yaw parameter of the UAV includes controlling the UAV to rotate in a yaw direction according to the yaw parameter of the gimbal, to cause the UAV to rotate along with the gimbal.

Provided in this disclosure is a system and methods for wind compensation of an electric aircraft. More specifically, provided in this disclosure is a controller of an aircraft configured to use a plant model for compensating for wind forces. The processor is configured to receive, from the sensor, at least a geographical datum of the electric aircraft.

An aircraft includes first units each including a first sensor, a rotary wing, a driver, and a first drive controller. The first drive controller is configured to generate a drive signal of the rotary wing on the basis of a flying route of the aircraft and a control law based on a flying state detected by the first sensor, and output the drive signal to the driver configured to drive the rotary wing. The control laws of the respective first drive controllers are equal to each other between the first units. The first drive controllers are each configured to generate the drive signals that correspond to all of the first units. The drivers are each configured to drive the corresponding rotary wing on the basis of corresponding one of the drive signals that correspond to all of the first units and that are generated by the first drive controllers.

Aerial vehicle sensor calibration systems and methods are provided herein. An example method includes determining a jarring event, determining when a drone is level relative to an aerial vehicle platform of a vehicle, the vehicle having a calibration controller, determining when the vehicle is level relative to a subordinate surface, and transmitting a signal to a drone controller by the calibration controller to calibrate a gyroscope or an accelerometer of the drone.

Disclosed are a system for drone calibration related to calibration that is required prior to flying a drone, and a method therefor. According to the present invention, there is an effect of improving the convenience of a calibration operation required for flying a drone, and in addition, when multiple drones have to be flying at the same time, there is an effect of allowing the drown to be easily calibrated without manually calibrating each of the multiple drones.

Embodiments herein describe UAVs that utilize tail boom assemblies from pre-existing aircraft designs as lift generating elements. In one embodiment, a UAV includes a fuselage having a first end and a second end opposite the first end, a first tail boom coupler disposed at the first end, and a second tail boom coupler disposed at the second end. Each of the first tail boom coupler and the second tail boom coupler are configured to mechanically couple with a plurality of tail boom assemblies procured from a pre-existing aircraft design.

A system including a system controller configured to transmit a first amount of commands in order to produce a desired effect by a group of actuators acting in combination. A system controller configured to control a group of at least two actuators in order to produce at least one combined effect, wherein the number of actuators is greater than or equal to the number of effects. A system controller configures to independent and variable bandwidths or responses of the desired effects produced by the actuators acting in combination.

A control system of an air vehicle for urban air mobility (UAM) is provided. A human-machine interface (HMI) system enables people to more easily control the air vehicle for UAM with a familiar method. The control system includes a steeling wheel operated for steering of the air vehicle, an accelerator pedal operated for acceleration of the air vehicle, and a decelerator pedal operated for deceleration and braking of the air vehicle. An altitude designating device selects and designates a target altitude and a controller generates a control command for adjusting altitude, acceleration, deceleration and braking, and steering of the air vehicle, based on air vehicle driving information. A drive device is then operated according to the control command generated from the controller.