Aircraft Flight Command Validation in Dual-Assurance Control
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Solution Overview
Problem
Current aviation systems face challenges in certifying autonomous aircraft control due to the complexity of processing unstructured sensor inputs from advanced systems, which makes it difficult to demonstrate deterministic responses, thereby limiting the use of uncertifiable hardware and software components.
Innovation Solution
The system employs a dual-assurance architecture with a lower assurance system for generating commands using uncertified components and a higher assurance system for validation, ensuring deterministic and certifiable aircraft control through partitioning and redundant processing, allowing for autonomous agents to transform unstructured sensor inputs into validated flight commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If autonomous agents use uncertified hardware and software components to process unstructured sensor inputs, then adaptability and processing capability are improved, but certification difficulty and system reliability deteriorate
Solution Approach 1:
The system is divided into two distinct segments: a lower assurance system that handles unstructured sensor inputs using uncertified components (providing adaptability), and a higher assurance system that validates commands using certified components (providing reliability). This segmentation allows each part to optimize for its specific function without compromising the other.
Solution Approach 2:
A command validation interface acts as an intermediary between the lower assurance system (generating commands) and the higher assurance system (validating commands). This intermediary layer enables the uncertified system to communicate with the certified system, allowing advanced processing while maintaining certification integrity.
2Device complexity
If a single integrated system is used for aircraft control, then device complexity is reduced, but the ability to isolate critical functions from non-critical functions deteriorates
Solution Approach 1:
The aircraft control system is segmented into functionally isolated components: sensor suites for data collection, autonomous agents for command generation, validation interfaces for verification, and flight control systems for execution. This segmentation enables critical functions to be isolated and protected while maintaining overall system integration.
Solution Approach 2:
Different parts of the system have different assurance levels tailored to their specific functions. Non-critical components (sensor processing, autonomous agents) use uncertified components for adaptability, while critical components (validation interface, flight control) use certified components for reliability. Each component's quality level matches its functional importance.
3Productivity
If advanced processing techniques are used to transform unstructured sensor inputs into flight commands, then productivity and automation are improved, but the difficulty of demonstrating deterministic responses deteriorates
Solution Approach 1:
The command validation interface serves as an intermediary that bridges the probabilistic nature of advanced processing techniques and the deterministic requirements of flight control. It validates that autonomous agent commands are appropriate before execution, enabling automation while ensuring deterministic verification.
Solution Approach 2:
The system implements feedback loops where the higher assurance system validates commands generated by the lower assurance system. This feedback mechanism ensures that advanced processing techniques produce deterministic, verifiable outputs by checking against safety criteria before flight control execution.
Data Source
AI summary
The method can include: determining sensor information with an aircraft sensor suite; based on the sensor information, determining a flight command using a set of models; validating the flight command S130; and facilitating execution of a validated flight command. The method can optionally include generating a trained model. However, the method S100 can additionally or alternatively include any other suitable elements. The method can function to facilitate aircraft control based on autonomously generated flight commands. The method can additionally or alternatively function to achieve human-in-the-loop autonomous aircraft control, and/or can function to generate a trained neural network based on validation of autonomously generated aircraft flight commands.