A method and device for assisting initiation of a flare maneuver of an aircraft during a landing. The device includes an acquisition unit for acquiring current values of flight parameters of the aircraft, including the current height of the aircraft with respect to the ground, a computation unit for computing a first reference height and a second reference height, corresponding to a height starting from which the aircraft attains a current start of flare height while maintaining its current descent conditions over a predetermined first duration and over a predetermined second duration respectively, and an acoustic emission unit for emitting at least two sound signals in the cockpit of the aircraft, namely a first sound signal when the current height of the aircraft attains the first reference height during the descent and a second sound signal when the current height of the aircraft attains the second reference height during descent.

Two methods of combining multiple response types into a single flexible command model are provided and include receiving a pilot stick input, generating an aircraft response to the pilot stick input that is a continuous blend of response types by including calculable time-varying coefficients set as a function of a magnitude of the pilot stick input and other aircraft states such as airspeed, imposing at least an angular acceleration command limit and using other non-linear elements to optimize the aircraft response to the pilot stick input.

A method and apparatus for processing aerodynamic angles for an aircraft. A first rate of change in an inertial aerodynamic angle is calculated using data received from an inertial measurement system for the aircraft. Further, a second rate of change in an externally measured aerodynamic angle is calculated. Yet further, a filtered aerodynamic angle is generated during a flight of the aircraft using the first rate of change in the inertial aerodynamic angle and the second rate of change in the externally measured aerodynamic angle. Still further, a contribution of the first rate of change in the inertial aerodynamic angle used in generated the filtered aerodynamic angle is changed based on a difference between the first rate of change in the inertial aerodynamic angle and the second rate of change in the externally measured aerodynamic angle, enabling controlling the flight of the aircraft using the filtered aerodynamic angle.

A method for collecting information required for Bode plot creation of a UAV (Unmanned Aerial Vehicle) autopilot system is provided. The method comprises: creating a Bode plot generation input signal: adding the Bode plot generation input signal to control inputs; collecting data from multiple points within the control system; calculating magnitude and phase at the multiple points using the data collected; recording the magnitude and phase for the multiple points in a datalog; comparing the magnitude and phase for the multiple points to calculate the gain and phase margins for open loop responses in the control system; creating a Bode plot for at least one of the following: i) a closed loop response of the attitude and/or rate loops, ii) an open loop response of the attitude and/or rate loops and iii) a response of the UAV; and outputting the Bode plot.

Closed loop control of control surfaces is described herein. One disclosed example method includes measuring a flight metric of an aircraft during flight and calculating, using a processor, a deflection of a control surface of the aircraft based on the flight metric. The disclosed example method also includes adjusting the deflection to an effective deflection level based on the calculated deflection to reduce a drag coefficient of the aircraft.

A method and a device for controlling an unmanned aerial vehicle (UAV) to follow face rotation are provided. The UAV is provided with a camera, the method includes: detecting a face in an image based on the Viola-Jones face detection framework; tracking the face and determining two-dimensional position of the facial feature on the face in pixel coordinates; obtaining three-dimensional position of the facial feature in world coordinates by looking up a standard three-dimensional face database; obtaining the three-dimensional position, in camera-centered coordinates, of the face on the UAV based on the two-dimensional position of the facial feature in the pixel coordinates and the three-dimensional position of the facial feature in world coordinates; and controlling, based on the three-dimensional position, in camera-centered coordinates, of the face on the UAV, the UAV to adjust its position to make the camera is aligned to the face.

Physical and logical components of a long line loiter control system address control of a long line loiter maneuver conducted beneath a carrier, such as a fixed-wing aircraft. Control may comprise identifying, predicting, and reacting to estimated states and predicted states of the carrier, a suspended load control system, and a long line. Identifying, predicting, and reacting to estimated states and predicted states may comprise determining characteristics of state conditions over time as well as response time between state conditions. Reacting may comprise controlling a hoist of the carrier, controlling thrusters of the suspended load control system, and or controlling or issuing flight control instructions to the carrier so as not to increase the response time and or to avoid a hazard.

A method of operating a multicopter comprising a body and n thrusters, each thruster independently actuated to vector thrust angularly relative to the body about at least a first axis, the method comprising modelling dynamics of the multicoptor with a mathematical model comprising coupled, non-linear combinations of thruster variables, decoupling the mathematical model into linear combinations of thruster control variables, sensing at least one characteristic of multicopter dynamics, comparing the sensed data with corresponding target characteristic(s), computing adjustments in thruster control variables for reducing the difference between the sensed data and the target characteristic(s) according to a control algorithm, and actuating each thruster according to the computed thruster control variables to converge the multicopter towards the target characteristic(s), wherein the control algorithm is based on the decoupled mathematical model such that each thruster control variable can be adjusted independently.

A nonlinear dynamic control system is defined by a set of equations that include a state vector and one or more control inputs. Via a machine learning method, a sub-optimal controller is derived that stabilizes the nonlinear dynamic control system at an equilibrium point. The sub-optimal controller is retrained to be used as a stabilizing controller for the nonlinear dynamic control system under general operating conditions.

A method and system for controlling movement of a vehicle. Movement, orientation, and position data of the vehicle is collected. A model of kinematics of the vehicle and its environment is created and a Theory of World model is produced and updated. The model includes geometric algebra multivectors. Errors and noise are stored as geometrically meaningful first-class objects within the multivectors. Geometric algebra operations are used to manipulate the model during operation. Error and noise data are propagated and manipulated using geometric algebra operations to reflect measurement and processing errors or noise. The models are used in generation of control data with a primary intent of ensuring stability. Operations such as intersections are used to compare position, orientation, and movement of the vehicle against position, orientation, and movement of objects in its environment. System tasks include, but are not limited to, kinematics, inverse kinematics, collision avoidance, and dynamics.