Aircraft Control System for Redundant Effector Management
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Solution Overview
Problem
Current control systems for modular and morphable aircraft lack the ability to autonomously select optimal flight paths and control effector settings to accommodate damage, system failures, and changing conditions while prioritizing mission criteria such as priority, urgency, risk tolerance, and cost tolerance.
Innovation Solution
A control system that monitors and controls redundant control effectors, selects among multiple combinations of settings to achieve a desired flight condition, and adjusts in real-time to maintain optimal performance, using sensors for environmental and vehicle condition data to optimize flight paths and control settings based on mission criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the aircraft uses redundant control effectors to accommodate damage and system failures, then the reliability is improved, but the device complexity increases
Solution Approach 1:
The control system pre-configures multiple combinations of control effector settings before flight operations begin. When damage or system failures occur, the system can immediately switch to pre-calculated alternative configurations without requiring complex real-time optimization, thus maintaining reliability while managing complexity.
Solution Approach 2:
The control system dynamically selects from multiple pre-configured control effector combinations based on real-time sensor data about vehicle condition and flight parameters. This dynamic adaptation allows the system to maintain optimal performance across varying operational states while using a manageable set of pre-planned configurations.
2Productivity
If the control system optimizes control effector settings in real-time, then the productivity is improved, but the use of energy increases
Solution Approach 1:
Multiple control effector combinations are pre-calculated and stored in the control system before flight. During operation, the system selects from these pre-configured options based on current flight conditions, avoiding the need for continuous complex optimization calculations and reducing real-time computational energy consumption while maintaining mission efficiency.
Solution Approach 2:
The system changes operational parameters by selecting from discrete pre-configured control effector combinations rather than continuously optimizing all parameters in real-time. This approach reduces computational burden and energy consumption while still adapting to changing flight conditions through parameter selection from the pre-configured set.
3Ease of operation
If the aircraft autonomously selects flight paths and control settings, then the ease of operation is improved, but the device complexity increases
Solution Approach 1:
The control system pre-configures multiple flight paths and corresponding control effector settings based on mission parameters and vehicle characteristics. This preliminary preparation enables autonomous operation by providing the system with a ready set of options to select from, reducing the complexity of real-time decision-making while maintaining ease of operation.
Solution Approach 2:
The control system autonomously monitors vehicle condition, selects appropriate pre-configured flight paths and control settings, and adjusts operations without external intervention. This self-service capability improves ease of operation by eliminating the need for constant pilot input while managing complexity through the use of pre-configured options rather than requiring complex real-time optimization algorithms.
Data Source
AI summary
An automated control system for an aircraft having redundant control effectors is configured to select among multiple combinations of redundant control effector settings to achieve a selected flight condition. The control system is configured to optimize the selected control effector settings for the selected flight condition and is configured to accommodate damage or system failure.