Vehicle Control

• US 20110029235A1
• Filed: 07/29/2010
• Published: 02/03/2011
• Est. Priority Date: 07/30/2009
• Status: Abandoned Application

• Current Assignee: Qinetiq Limited (QinetiQ Group PLC)
• Original Assignee: Qinetiq Limited (QinetiQ Group PLC)
• Inventors: Berry, Andrew James
• Application Number:
  US12/846,220
• Publication Number:
  US 20110029235A1
• Time in Patent Office: Days
• US Class Current: 701/207
• CPC Class Codes: G01C 21/005 with correlation of navigation data from several sources, e.g. map or contour matching G01C21/30 takes precedence
• CPC Class Codes: G05D 1/0204 to counteract a sudden perturbation, e.g. cross-wind, gust
• CPC Class Codes: G05D 1/106 Change initiated in response to external conditions, e.g. avoidance of elevated terrain or of no-fly zones
• CPC Class Codes: G08G 5/0021 located in the aircraft
• CPC Class Codes: G08G 5/0069 specially adapted for an unmanned aircraft
• CPC Class Codes: G08G 5/0078 for monitoring traffic from the aircraft radar or analogous systems specially adapted for traffic control G01S13/91
• CPC Class Codes: G08G 5/045 Navigation or guidance aids, e.g. determination of anti-collision manoeuvers radar or analogous systems specially adapted for anti-collision between aircraft G01S13/933

Abstract

A method of vehicle control, in which a global target trajectory is tracked by successively calculating an optimum local trajectory in 4D output space to approach the global trajectory and observe vehicle performance limits and surrounding obstacle clearance. A receding horizon framework is proposed which successively updates the optimum local trajectory according to the current state of the vehicle. Processing overheads can be kept to a minimum by calculating performance limits offline, and optimisation is simplified by using a cost function approach.

Claims

1. A method of control of a vehicle, said method comprising the steps of:

providing a global target trajectory,

determining the current state of said vehicle,

deriving from said current state trajectory performance limits for said vehicle,

calculating an optimum local trajectory in 4D output space to approach said global trajectory and observe said performance limits,

outputting control inputs corresponding to said selected trajectory, and

updating the current state of said vehicle, and deriving updated trajectory performance limits and an updated optimum local trajectory accordingly.

2. A method according to claim 1, comprising calculating said local trajectory over a fixed time horizon.

3. A method according to claim 1, comprising calculating said local trajectory as polynomial functions of a curve parameter.

4. A method according to claim 3, comprising calculating said local trajectory as three component polynomial functions.

5. A method according to claim 4, wherein each component polynomial function represents velocity in three orthogonal axes.

6. A method according to claim 3, wherein said polynomial functions are 6^th order.

7. A method according to claim 3, comprising enforcing initial boundary conditions on said polynomial functions.

8. A method according to claim 2, wherein said fixed time period/horizon is greater than or equal to 5 seconds.

9. A method according to claim 2, wherein said fixed time period/horizon is less than or equal to 20 seconds.

10. A method according to claim 1, comprising representing obstacles as a cost penalty function during calculation of an optimum local trajectory.

11. A method according to claim 1, comprising representing trajectory performance limits as a cost penalty function during calculation of an optimum local trajectory.

12. A method according to claim 10, wherein said cost penalty function is a potential function.

13. A vehicle adapted for control by the method of claim 1.

14. A method for evaluating position errors along a proposed local object trajectory with respect to a desired object trajectory,

performing a nearest point calculation to determine the error for the current position of an object,

performing a curve fit to provide an approximation of said desired trajectory based on said nearest point calculation and the length of the local object trajectory, and

performing a series of position error calculations between said local object trajectory and said approximation.