A method and system to control a rotor system includes providing a controller communicably coupled to the rotor system, and automatically changing a rotor speed of the rotor system from a first rotor speed in a first flight mode to a second rotor speed in a second flight mode over a time period using the controller in accordance with an acceleration-rate profile that varies over the time period.

In one example a system for emotional adaptive driving policies for automated driving vehicles, comprising a first plurality of sensors to detect environmental information relating to at least one passenger in a vehicle and a controller communicatively coupled to the plurality of sensors and comprising processing circuitry, to receive the environmental information from the first plurality of sensors, determine, from the environmental information, an emotional state of the at least one passenger, and implement a driving policy based at least in part on the emotional state of the at least one passenger. Other examples may be described.

A method for operating a materials handling vehicle is provided and comprises: monitoring, by a controller, a first vehicle drive parameter during a manual operation of the vehicle by an operator; storing, by the controller, data related to the monitored first vehicle drive parameter. The controller is configured to use the stored data for implementing a semi-automated driving operation of the vehicle subsequent to the manual operation of the vehicle. The method further comprises: detecting, by the controller, operation of the vehicle indicative of a start of a pick operation occurring during the manual operation of the vehicle; and based on detecting the start of the pick operation, resetting, by the controller, the stored data related to the monitored first vehicle drive parameter.

Operating a materials handling vehicle includes monitoring, by a controller, a first vehicle drive parameter during a first manual operation of the vehicle by an operator; monitoring, by the controller, the first vehicle drive parameter during a second manual operation of the vehicle by the operator; receiving, by the controller after the first manual operation of the vehicle and the second manual operation of the vehicle, a request to implement a semi-automated driving operation; calculating, by the controller, a first weighted average based on the monitored first vehicle drive parameter during the first manual operation of the vehicle and the monitored first vehicle parameter during the second manual operation of the vehicle; and based at least in part on the calculated first weighted average, controlling, by the controller, implementation of the semi-automated driving operation.

A method of operating a rotorcraft includes receiving multiple first height data signals from multiple first height sensors on the rotorcraft, wherein the first height sensors measure height using a first technique, receiving multiple second height data signals from multiple second height sensors on the rotorcraft, wherein the second height sensors measure height using a second technique that is different than the first technique, determining a first height signal from the multiple first height data signals based on a selection scheme, determining a second height signal from the multiple second height data signals, selecting the first height signal or the second height signal to determine a selected height signal, and generating a flight control signal and controlling operation of the rotorcraft according to the flight control signal, the flight control signal based on the selected height signal.

A process and machine configured to predict and preempt an undesired load and/or bending moment on a part of a vehicle resulting from an exogenous or a control input. The machine may include a predictor with an algorithm for converting parameters from a state sensed upwind from the part into an estimated normal load on the part and a prediction, for a future time, of a normal load scaled for a weight of the aerospace vehicle. The machine may: produce, using a state upwind from the part on the aerospace vehicle and/or a maneuver input, a predicted state, load and bending moment on the part at a time in the future; derive a command preempting the part from experiencing the predicted load and bending moment; and actuate the command just prior to the part experiencing the predicted state, thereby alleviating the part from experiencing the predicted load and bending moment.

The present disclosure relates to a computer-implemented method for calculating a trajectory of a mobile platform. The method calculates an exact or approximate solution of an optimization problem, which minimizes the travel time from a predetermined starting state to a predetermined end state, wherein the jerk of the mobile platform is restricted in absolute value to a maximum jerk and wherein the acceleration of the mobile platform is restricted, wherein the limit of the acceleration can be dependent on the velocity of the mobile platform.

An apparatus and method for identifying potential aircraft fuel jettison and/or burn sites is provided.

A method of controlling an elevator of an aircraft includes selecting a factor for increasing or decreasing a predetermined horizontal tail load alleviation (HTLA) authority limit for an elevator based on at least one aircraft parameter. The HTLA authority limit decreases with an increase in Mach number and/or airspeed. The method also includes computing an elevator position limit as a product of the HTLA authority limit and the factor, and moving the elevator to a commanded elevator position that is no greater than the elevator position limit.

A method of operating an under-actuated actuator system including a plurality of actuators (3), preferably for operating a multiactuator aerial vehicle (1), wherein the actuators (3) are individual propulsion units of the multiactuator aerial vehicle (1), each actuator having a maximum physical capacity u.sup.max, the method including: controlling the actuators (3) by with an actual control input u∈.sup.k computed from an allocation equation u=D.sup.−1u.sub.p, wherein D.sup.−1 is an inverse allocation matrix and u.sub.p∈.sup.m is a pseudo control input defined by a system dynamics equation m(x){dot over (x)}+c(x,{dot over (x)})+g(x)+G(x)u.sub.p=f.sub.ext, wherein x∈n is an n-dimensional configuration vector of the system, m(x)∈.sup.n×n is a state dependent generalized moment of inertia, c(x,{dot over (x)})∈.sup.n are state dependent Coriolis force, g(x)∈.sup.n are gravitational forces and f.sub.ext∈.sup.n are external forces and torques, and G(x)∈.sup.n×m is a control input matrix which contains the information of under-actuation.