IP Library Granted Patent US 11,628,950
Granted Patent B2
US 11,628,950 · App. 17/028,773 · Granted Apr 18, 2023

Actuator monitoring system using inertial sensors

Inventor: Mark Johnson Cutler (Sunnyvale, CA)
Assignee: Kitty Hawk Corporation
B64D45/00B64C13/16B64F5/60G01C21/166B64D2045/0085
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Quick Facts
Patent No.
US 11,628,950
App. No.
17/028,773
Granted
Apr 18, 2023
Kind
B2
Abstract

Sensor data is received from an inertial measurement unit on a vehicle. An observed attitude and an observed attitude rate of the vehicle are determined based on the sensor data. Using a model associated with a vehicle failure mode, an expected attitude and an expected attitude rate of the vehicle are determined. A malfunctioning rotor is determined based on the observed attitude, the observed attitude rate, the expected attitude, and the expected attitude rate. In response to identifying the malfunctioning rotor, a responsive action is performed, including by updating a geometry matrix so that at least one non-malfunctioning rotor in the plurality of rotors compensates for the malfunctioning rotor.

Claims (55)

1. A system, comprising:

a processor; and

a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to:

receive vehicle state information and at least one actuator command from a vehicle;

determine a model associated with a vehicle failure mode, wherein the model includes an output state vector representing a vehicle state in the vehicle failure mode, the output state vector being determined based at least in part on at least one function that: receives the vehicle state information and the at least one actuator command, models each failure mode independently, and outputs the output state vector;

determine an observed flight characteristic and an observed flight characteristic rate of the vehicle based at least in part on sensor data from an inertial measurement unit on the vehicle;

determine an expected flight characteristic and an expected flight characteristic rate of the vehicle based at least in part on the model associated with a vehicle failure mode;

identify, from a plurality of rotors associated with the vehicle, a malfunctioning rotor based at least in part on the observed flight characteristic, the observed flight characteristic rate, the expected flight characteristic, and the expected flight characteristic rate; and

in response to identifying the malfunctioning rotor, perform a responsive action.

2. The system of claim 1 , wherein:

the observed flight characteristic includes an observed attitude;

the observed flight characteristic rate includes an observed attitude rate;

the expected flight characteristic includes an expected attitude; and

the expected flight characteristic rate includes an expected attitude rate.

3. The system of claim 1 , wherein the output state vector includes an expected attitude associated with the vehicle failure mode.

4. The system of claim 1 , wherein the output state vector includes an expected attitude rate associated with the vehicle failure mode.

5. The system of claim 1 , wherein modeling each failure mode independently includes applying a respective function for each failure mode to determine a respective output value based on a same set of inputs provided to all functions.

6. The system of claim 1 , wherein:

the vehicle state information includes historical vehicle state information; and

the at least one actuator command includes at least one historical actuator command.

7. The system of claim 6 , wherein the vehicle state information includes at least one of: an attitude, an attitude rate, a position, a velocity, a wind velocity, or a geometry of the vehicle.

8. The system of claim 6 , wherein the vehicle state information identifies the vehicle failure mode associated with a set of data.

9. The system of claim 8 , wherein determining the model includes at least one of grouping or sorting data to generate the model.

10. The system of claim 1 , wherein:

the vehicle includes at least one tilt wing; and

determining the model is based at least in part on at least one of a direction or a mode of the at least one tilt wing.

11. The system of claim 10 , wherein determining the model includes selecting a model to use during flight based at least in part on at least one of a direction or a mode of the at least one tilt wing.

12. The system of claim 1 , wherein the processor is further configured to update the model in real time as the vehicle is flying.

13. The system of claim 12 , wherein updating the model in real time as the vehicle is flying includes collecting flight data during flight to update the model which the vehicle is airborne.

14. The system recited in claim 1 , wherein the responsive action includes updating a geometry matrix, which is used to generate a plurality of actuator commands for the plurality of rotors, including by updating a previous geometry matrix with a precomputed geometry matrix.

15. The system recited in claim 14 , wherein:

the malfunctioning rotor is associated with a first region of the vehicle; and

updating the geometry matrix includes increasing an authority of a second region of the vehicle in response to detection of the malfunctioning rotor in the first region.

16. A method, comprising:

receiving, by a processor, vehicle state information and at least one actuator command from a vehicle;

determining, by a processor, a model associated with a vehicle failure mode, wherein the model includes an output state vector representing a vehicle state in the vehicle failure mode, the output state vector being determined based at least in part on at least one function that: receives the vehicle state information and the at least one actuator command, models each failure mode independently, and outputs the output state vector;

determining, by a processor, an observed flight characteristic and an observed flight characteristic rate of the vehicle based at least in part on sensor data from an inertial measurement unit on the vehicle;

determining, by a processor, an expected flight characteristic and an expected flight characteristic rate of the vehicle based at least in part on the model associated with a vehicle failure mode;

identifying, by the processor, from a plurality of rotors associated with the vehicle, a malfunctioning rotor based at least in part on the observed flight characteristic, the observed flight characteristic rate, the expected flight characteristic, and the expected flight characteristic rate; and

in response to identifying the malfunctioning rotor, performing, by a processor, a responsive action.

17. The method of claim 16 , wherein:

the vehicle includes at least one tilt wing; and

determining the model is based at least in part on at least one of a direction or a mode of the at least one tilt wing.

18. The method of claim 17 , wherein determining the model includes selecting a model to use during flight based at least in part on at least one of a direction or a mode of the at least one tilt wing.

19. The method of claim 16 , further comprising updating the model in real time as the vehicle is flying.

20. A computer program product embodied in a non-transitory computer readable storage medium and comprising computer instructions which when executed by a processor cause the processor to be configured for:

receiving vehicle state information and at least one actuator command from a vehicle;

determining a model associated with a vehicle failure mode, wherein the model includes an output state vector representing a vehicle state in the vehicle failure mode, the output state vector being determined based at least in part on at least one function that: receives the vehicle state information and the at least one actuator command, models each failure mode independently, and outputs the output state vector;

determining an observed flight characteristic and an observed flight characteristic rate of the vehicle based at least in part on sensor data from an inertial measurement unit on the vehicle;

determining an expected flight characteristic and an expected flight characteristic rate of the vehicle based at least in part on the model associated with a vehicle failure mode;

identifying, from a plurality of rotors associated with the vehicle, a malfunctioning rotor based at least in part on the observed flight characteristic, the observed flight characteristic rate, the expected flight characteristic, and the expected flight characteristic rate; and

in response to identifying the malfunctioning rotor, performing a responsive action.

21. The computer program product of claim 20 , wherein:

the vehicle includes at least one tilt wing; and

determining the model is based at least in part on at least one of a direction or a mode of the at least one tilt wing.

Assignments (4)
RELEASE OF SECURITY INTEREST Recorded May 22, 2023
From: ONE AERO, LLC
To: KITTY HAWK CORPORATION
Reel/Frame 063713/0367 →
SECURITY INTEREST Recorded Mar 25, 2022
From: KITTY HAWK CORPORATION
To: ONE AERO, LLC
Reel/Frame 059503/0382 →
SECURITY INTEREST Recorded Nov 4, 2021
From: KITTY HAWK CORPORATION
To: ONE AERO, LLC
Reel/Frame 058029/0610 →
SECURITY INTEREST Recorded Oct 22, 2020
From: KITTY HAWK CORPORATION
To: ONE AERO, LLC
Reel/Frame 054206/0714 →
Continuity (3)
Continuation 16126950 · Sep 10, 2018
Continuation 15689892 · Aug 29, 2017
Related Publication 20210016893A1 · Jan 21, 2021