Autonomous Attitude Control System for Dynamic Vehicle Reorientation
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Solution Overview
Problem
Existing solutions for reorienting vehicles, such as spacecraft, require numerous manual calculations to develop and update movement models, which can be impractical and lead to communication disruptions due to outdated models, especially in dynamic conditions.
Innovation Solution
An autonomous attitude determination and control system (ADCS) using artificial intelligence and expert systems to dynamically characterize and update movement models based on vehicle state information, allowing for real-time adjustments and reorientation without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calculations are used to develop and update movement models, then the system can maintain accuracy, but the complexity and time required for updates increases significantly
Solution Approach 1:
The system uses autonomous algorithms that automatically characterize and update movement models using sensor data from the vehicle itself, eliminating the need for manual calculations. The vehicle serves its own calibration needs by collecting operational data and automatically adjusting its movement model parameters.
Solution Approach 2:
The system implements continuous feedback loops where sensor measurements of actual vehicle movement are compared against predicted movement from the model, and discrepancies are used to automatically update and refine the movement model parameters without manual intervention.
2Adaptability or versatility
If manual calculations are used to update movement models, then the system can adapt to changing conditions, but the time required for updates causes communication disruptions
Solution Approach 1:
The system continuously collects and processes sensor data in the background during normal operations, preparing updated movement model parameters before they are needed. This preliminary processing ensures that when updates are required, they are already calculated and can be applied immediately without communication disruptions.
Solution Approach 2:
The autonomous algorithm operates continuously during vehicle operation, constantly refining the movement model based on incoming sensor data. This continuous operation ensures the model remains current without requiring periodic manual updates that would interrupt communication.
3Reliability
If pre-launch or post-launch calculations are used, then the movement model can be established, but the model becomes outdated when vehicle conditions change
Solution Approach 1:
The system transitions from static movement models established at fixed points (pre-launch or post-launch) to dynamic models that continuously adapt during operation. The autonomous algorithm adjusts model parameters in real-time based on changing vehicle conditions such as fuel depletion, mass changes, and component wear.
Data Source
AI summary
The systems and methods described herein include attitude determination and control system (ADCS) and associated methods. Systems for determining attitude may be used by various vehicle types, such as to determine the vehicle's attitude relative to an external point of reference. The ADCS may be used for passive or active stabilization of spin on multiple axes. The ADCS uses an incorporated autonomous control algorithm to characterize the effects of actuation of the system components and simultaneously trains its response to attitude actuators. This characterization generates and updates a movement model, where the movement model is used to indicate or predict the effect of one or more attitude actuators given vehicle state information.