The Boeing Company

Sherwin Chunshek Li

Brian Kenyon Rupnik

Kioumars Najmabadi

Brian T Whitehead

Robert Erik Freeman

Leonard J Inderhees

Ryan L Pettit

Russell Tanner Bridgewater

Rostyslav Oleksiy Svitelskyi

Melville D W Mcintyre

Rostyslav Svitelskyi

Bryan A Lopez

William Tyler Piersol

Russell T Bridgewater

Leonard John Inderhees

An aircraft includes an autopilot system including one or more processors. The one or more processors are configured to, in response to selection of an autopilot activation button during flight of the aircraft while the aircraft is operating in a first condition, apply first control laws to automatically control the flight of the aircraft. The one or more processors are further configured to, in response to selection of the autopilot activation button while the aircraft is operating in a second condition, apply second control laws to automatically control the flight of the aircraft, where the second control laws are different from the first control laws.

Autopilot-based aircraft recovery system

A system and a method include air data sensors configured to detect one more characteristics of air surrounding an aircraft. At least three of the air data sensors differ in type. The air data sensors are configured to output air data. A flight control unit is in communication with the air data sensors. The flight control unit is configured to receive the air data from the air data sensors and control at least one aspect of the aircraft based on at least a portion of the air data. In at least one example, the flight control unit is further configured to vote in relation to the air data from the air data sensors.

Systems and methods for controlling an aircraft using dissimilar air data

Methods and apparatus for automatically extending aircraft wing flaps in response to detecting an excess energy steep descent condition are described. An example control system of an aircraft includes one or more processors. The one or more processors determine whether the aircraft is experiencing an excess energy steep descent (EESD) condition. In response to determining that the aircraft is experiencing the EESD condition, the one or more processors command an actuator of the aircraft coupled to a flap of the aircraft to extend the flap from a current flap position to a subsequent flap position defined by a flap extension sequence.

Methods and apparatus for automatically extending aircraft wing flaps in response to detecting an excess energy steep descent condition

An example system includes a common mode pneumatic event detector to detect a common mode pneumatic event at pitot tubes of an aircraft, a latch, a relay switch in communication with the latch, and a latch controller to set the latch in a first state to cause the latch to output a first latch signal, the relay switch to output a first pressure signal in response to the first latch signal, the first pressure signal based on pressure data from the pitot tubes, and set the latch in a second state to cause the latch to output a second latch signal based on the detection of the common mode pneumatic event. The relay switch is to output a second pressure signal in response to the second latch signal. The second pressure signal includes estimated pressure data.

Apparatus, systems, and methods for managing common mode pneumatic events

Systems, methods, and apparatus for sensor fault detection and identification using residual failure pattern recognition are disclosed. In one or more embodiments, a method for sensor fault detection and identification for a vehicle comprises sensing, with sensors located on the vehicle, data. The method further comprises performing majority voting on the data for each of the types of data to generate a single voted value for each of the types of data. Also, the method comprises generating, for each of the types of data, estimated values by using some of the voted values. In addition, the method comprises generating residuals by comparing the estimated values to the voted values. Further, the method comprises analyzing a pattern of the residuals to determine which of the types of the data is erroneous to detect and identify a fault experienced by at least one of the sensors on the vehicle.

Sensor fault detection and identification using residual failure pattern recognition

A flight control system for an aircraft is disclosed. The flight control system includes one or more processors and a memory coupled to the processors. The memory stores data comprising a database and program code that, when executed by the one or more processors, causes the flight control system to receive as input a plurality of first operating parameters that each represent an operating condition of the aircraft. The flight control system is further caused to determine a drag coefficient and a lift coefficient based on the plurality of first operating parameters. The flight control system is also caused to determine an estimated dynamic pressure based on both the drag coefficient and the lift coefficient.

Flight control system for determining estimated dynamic pressure based on lift and drag coefficients

A flight control system for an aircraft is disclosed and includes one or more processors and a memory coupled to the processors. The memory stores data comprising a database and program code that, when executed by the one or more processors, causes the flight control system to receive as input a measured angle of attack that is based on a raw angle of attack and an estimated angle of attack based on a total pressure. The flight control system is further caused to compare the measured angle of attack with the estimated angle of attack to determine an error. In response to determining that the error between the measured angle of attack and the estimated angle of attack exceeds a threshold value, the flight control system determines the presence of a fault with an angle of attack value.

Flight control system for determining a fault based on error between a measured and an estimated angle of attack

A flight control system for an aircraft is disclosed, where the flight control system detects a first common mode pneumatic event. The flight control system includes one or more processors and a memory coupled to the processors. The memory stores data comprising a database and program code that, when executed by the one or more processors, causes the flight control system to receive as input a measured dynamic pressure and an estimated angle of attack. The flight control system is further caused to determine a rate of change of the measured dynamic pressure and compare the rate of change of the measured dynamic pressure with a dynamic pressure threshold value. The flight control system is further caused to determine a rate of change of the estimated angle of attack and compare the rate of change of the estimated angle of attack with a threshold angle of attack.

Flight control system for determining a common mode pneumatic fault

A system includes a plurality of smart outlets and a backend system in wireless communication with the smart outlets. The smart outlets are configured to provide electrical power from an electrical system to respective power loads, and configured to measure power consumption characteristics thereof the respective power loads. The power consumption characteristics may include real power, apparent power or a combination thereof consumed by the respective power loads. The backend system may be configured to wirelessly receive the power consumption characteristics from the smart outlets for analysis in accordance with a power distribution schedule of the electrical system, and wirelessly transmit a command signal to one or more of the smart outlets in various instances response to the analysis. This command signal may instruct the respective one or more smart outlets to shed or restore power to respective power loads from the electrical system.

Growing community of inventors

Edmonds, WA, United States of America

Sherwin Chunshek Li