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.

The present disclosure describes an actuator system comprising an actuator unit that is configured to be positioned next to a structure; and an adaptive controller unit that is configured to receive a command input for the actuator unit and output an actuator command based on a reference model of a physical system that includes the actuator unit and the structure, wherein the actuator command does not alter trajectories of the reference model. In various embodiments, the uncertain dynamical system of the physical system is augmented with the actuator dynamics to provide improved stability.

A method of protecting a margin for controlling the yaw attitude of a hybrid helicopter that includes a lift rotor as well as at least one first propeller and at least one second propeller. A thrust control is configured to generate at least a first order issued to increase a first pitch of first blades of the first propeller and a second pitch of second blades of the second propeller. After a first order has been issued, the method includes an inhibition step for having a control computer inhibit the first order when a yaw attitude control margin, with regard to an envelope delimiting a flight control domain, is and/or will be less than or equal to a threshold.

Systems and vehicle are provided. A vehicle system for a vehicle includes: a trajectory selection module configured to select a potential vehicle path relative to a current vehicle movement condition; a trajectory movement condition module configured to estimate a modeled movement condition of the vehicle along the potential vehicle path; a limit comparison module configured to determine whether the modeled movement condition violates vehicle limits; and a violation indicator module configured to generate an indication of impending violation.

Provided is a stable flight control method for a multi-rotor unmanned aerial vehicle based on finite-time neurodynamics, comprising the following implementation process: 1) acquiring real-time flight orientation and attitude data through airborne sensors, and analyzing and processing kinematic problems of the aerial vehicle through an airborne processor to establish a dynamics model of the aerial vehicle; 2) designing a finite-time varying-parameter convergence differential neural network solver according to a finite-time varying-parameter convergence differential neurodynamics design method; 3) solving output control parameters of motors of the aerial vehicle through the finite-time varying-parameter convergence differential neural network solver using the acquired real-time orientation and attitude data; and 4) transmitting results to speed regulators of the motors of the aerial vehicle to control the motion of the unmanned aerial vehicle. Based on the finite-time varying-parameter convergence differential neurodynamics method, the invention can approximate the correct solution of the problem in a quick, accurate and real-time way, and can well solve a variety of time-varying problems such as matrix, vector, algebra and optimization.

An autopilot nonlinear compensation method includes providing an autopilot command for executing an aircraft maneuver, determining a desired aerodynamic moment of the aircraft based on the autopilot command, providing a measured pilot interface position, determining a total aerodynamic moment of the aircraft based on the measured pilot interface position and the autopilot command in combination with the desired aerodynamic moment, determining a ratio of the desired aerodynamic moment to the total aerodynamic moment, and adjusting the autopilot command with a corrective command based on the ratio. The method may be used to stabilize autopilot control of an aircraft following nonlinear deployment of a control surface.

An aircraft may include a tail having a rudder and a pair of wings. The pair of wings may include at least one flap and at least one roll control device. The aircraft may also include at least two thrust-producing devices. The aircraft may also include a differential thrust control system including a computing device having at least one processor. The at least one processer may be configured to control an attitude of the aircraft by selectively operating the at least two thrust-producing devices, the rudder, and the at least one roll control device based at least in part on a plurality of conditions provided by a plurality of sensors on the aircraft and a selected mode setting of a mode control panel. The computing device may be communicatively coupled to the at least two thrust-producing devices, the rudder, and the at least one roll control device.

A method for monitoring an oscillatory signal from an oscillating device includes filtering the oscillatory signal to within a desired frequency band to provide a filtered signal and extracting an amplitude from the filtered signal. The method further includes switching control of the oscillating device when the amplitude exceeds a predetermined amplitude requirement for a predetermined duration. An oscillatory signal monitor includes a first controller and a second controller each configured to independently control an oscillating device. An oscillatory signal based on a position of the oscillating device is filtered to a desired frequency band, and an amplitude is extracted from the filtered signal. A switch is provided for switching control of the oscillatory device from the first controller to the second controller when the amplitude exceeds a predetermined amplitude requirement for a predetermined duration.

An aircraft control system includes a target instruction value calculation unit acquires a target instruction value to set an aircraft in a target state, a reference velocity calculation unit inputs, to a reference model in which reference velocity corresponding to a reference value of aircraft velocity is set uniquely as an output value according to an input value, a value based on the target instruction value as the input value. A relative velocity calculation unit calculates relative velocity of the aircraft to a target position, the relative velocity being used in control of the aircraft. An estimated disturbance quantity calculation unit calculates an estimated disturbance quantity acting on the aircraft, based on a difference between the relative velocity and the reference velocity, and a correction target instruction value calculation unit corrects the target instruction value, based on the estimated disturbance quantity calculated at a previous timing.

Systems and vehicle are provided. A vehicle system for a vehicle includes: a trajectory selection module configured to select a potential vehicle path relative to a current vehicle movement condition; a trajectory movement condition module configured to estimate a modeled movement condition of the vehicle along the potential vehicle path; a limit comparison module configured to determine whether the modeled movement condition violates vehicle limits; and a violation indicator module configured to generate an indication of impending violation.