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.

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 set of commands for each of a plurality of actuators to alter an aircraft's state responsive to one or more inputs is produced. The set of commands is provided to fewer than all actuators comprising the plurality of actuators.

A set of commands for each of a plurality of actuators to alter an aircraft's state responsive to one or more inputs is produced. The set of commands is provided to fewer than all actuators comprising the plurality of actuators.

The present disclosure provides methods and system for controlling the operation of a fly-by-wire aircraft. One or more yaw commands are received from an operator control, and one or more actual induced rolls rates are determined based on the yaw commands. A yaw signal and a roll-countering command are sent to flight control components of the aircraft, the yaw signal to cause a yaw motion in the aircraft, and the roll-countering command to counter the actual induced rolls. A standardized roll rate command is determined based on the yaw command, and the standardized roll rate command is sent to the flight control components to cause a roll motion in the aircraft.

Methods and systems for longitudinal control of aircraft during flight are disclosed. One method comprises receiving a commanded normal acceleration of the aircraft and computing a target pitch rate for the aircraft based on the commanded normal acceleration. The target pitch rate is used in a control technique for controlling one or more flight control surfaces of the aircraft to achieve the target pitch rate for the aircraft. The control technique can include (e.g., incremental) nonlinear dynamics inversion.

A vehicle and method of control comprising generating a geometric control envelope in a geometric space of operation points defined by a number of control aspects, the envelope having vertices representing maximum values of the control aspects, and determining a desired operation point in the geometric space representing a control input. Further, the method includes if the desired operation point is outside the envelope, scaling up a first one of the control aspects by a first factor, determining an effective operation point in the envelope geometrically closest to the desired operation point, scaling down all of the control aspects by a second factor inverse of the first factor, and instructing the propulsion mechanisms to propel the vehicle according to the effective operation point.

An emergency pilot assistance system may include an artificial neural network configured to calculate reward (Q) values based on state-action vectors associated with an aircraft. The state-action vectors may include state data associated with the aircraft and action data associated with the aircraft. The system may further include a user output device configured to provide an indication of an action to a user, wherein the action corresponds to an agent action that has a highest reward Q value as calculated by the artificial neural network.

A method of adjusting a directional movement ability in an aircraft having two or more rotors includes receiving a desired thrust demand for each rotor of the two or more rotors, comparing the desired thrust demands to determine a maximum thrust demand, determining whether the maximum thrust demand exceeds a maximum thrust limit of the two or more rotors, and adjusting each desired thrust demand based on whether the maximum thrust demand exceeds the maximum thrust limit to provide an adjusted thrust demand for each rotor of the two or more rotors. Each rotor can be operated based on a respective adjusted thrust demand.

Apparatus and methods for controlling unmanned systems (UMSs), such as unmanned aircraft, are provided. A UMS can be provided that includes a network, auxiliary systems, and a payload, where the network can connect the auxiliary systems and the payload. A network switch of the network can logically separate the network into at least a second tier of communications and a third tier of communications. The network can be used to control the UMS by at least: controlling the auxiliary systems using messages communicated by the second tier of communications, and communicating with the payload using messages communicated by the third tier of communications.