Aircraft Trajectory Control Using Merged Lateral-Vertical Profiles
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Solution Overview
Problem
Current aerospace vehicle trajectory control and prediction methods are inefficient due to rough estimations of speed at turn points, leading to conservative lateral profiles that do not achieve desired time, distance, or fuel-efficiency, as they decouple lateral and vertical profile generations without considering real interactions and limitations between the two profiles.
Innovation Solution
A process that generates a baseline lateral profile using instantaneous course changes at each turn point, computes turn radii, and adjusts the profile to derive an adapted vertical profile, merging both to form a predicted trajectory that accounts for airspace constraints and performance elements like true airspeed, thereby inverting the traditional generation process to ensure accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If rough estimations of speed at turn points are used to generate lateral profile, then the trajectory control process is simplified and can be completed independently, but the resulting lateral profile is overly conservative and does not achieve desired time, distance, or fuel-efficiency
Solution Approach 1:
The patent merges the generation of lateral and vertical profiles into a unified iterative process. Instead of generating lateral profile first with rough speed estimates and then vertical profile separately, the system simultaneously optimizes both profiles by iterating between them, using vertical profile information to refine lateral profile speed estimates and vice versa, eliminating the overly conservative nature of sequential generation
Solution Approach 2:
The patent introduces dynamic iteration between lateral and vertical profile generation. The system dynamically adjusts speed estimates at turn points by repeatedly exchanging information between lateral and vertical profile calculations, allowing the profiles to adapt to each other's constraints and optimize overall trajectory performance rather than relying on static rough estimates
2Device complexity
If lateral and vertical profile generations are decoupled and completed independently, then the computational process is simplified and faster, but the profiles cannot account for real interactions and limitations between the two directions
Solution Approach 1:
The patent performs preliminary generation of both lateral and vertical profiles independently to establish initial solutions, then uses these preliminary profiles as starting points for iterative refinement. This preliminary action allows the system to capture the full interactions between lateral and vertical constraints while maintaining computational efficiency by avoiding complete recalculation from scratch
Solution Approach 2:
The patent implements feedback loops where the vertical profile generation provides speed estimate corrections back to the lateral profile, and the lateral profile provides constraint information back to the vertical profile. This mutual feedback ensures that both profiles account for real interactions and limitations between directions while maintaining a structured computational approach
3Reliability
If conservative speed estimations are made at turn points to ensure lateral profile feasibility, then the vehicle can reliably follow the lateral profile, but the resulting trajectory does not achieve desired time of travel, distance, or fuel-efficiency
Solution Approach 1:
The patent dynamically refines speed estimates at turn points through iterative exchange between lateral and vertical profile generation. Instead of using fixed conservative estimates, the system adjusts speed values based on vertical profile constraints and performance requirements, allowing the lateral profile to be both feasible and optimized for time and fuel efficiency
Solution Approach 2:
The patent changes the speed parameter at turn points from rough conservative estimates to refined values derived from vertical profile information. By iteratively adjusting this critical parameter based on mutual constraints between lateral and vertical movements, the system achieves trajectories that meet both feasibility and performance requirements
Data Source
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AI summary
Illustrative examples are provided of a process and machine configured to provide innovative technical solutions for: deriving a predicted trajectory for a vehicle; controlling a trajectory for a vehicle; and for reducing congestion in an Air Traffic Management system, via: a processor executing an algorithm specially programmed for: generating a baseline lateral profile for a baseline trajectory; subsequently generating a baseline vertical profile for the baseline trajectory; subsequently forming the baseline trajectory by merging the vertical profile with the baseline lateral profile; and using at least one of: a performance element, or a configuration element, from the baseline trajectory for deriving the predicted trajectory. The predicted trajectory is sent for use by a Flight Management System and/or an Air Traffic Management System.