Flight Control System for Microburst Detection and Recovery
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) face challenges in automatically detecting and recovering from microburst conditions, as existing flight control systems struggle to account for the sudden changes in wind speed and direction, leading to potential loss of lift and impaired flight performance.
Innovation Solution
A flight control system utilizing intelligent state flow technology and H∞ robust control techniques to detect microburst conditions and stabilize aircraft, employing automated mode selection and robust control laws to manage lift and pitch moment, with sensors like air data computers and weather radar providing data for real-time gust estimation and system uncertainties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard flight control laws are used in UAVs, then the system complexity is low, but the reliability of flight in microburst conditions deteriorates
Solution Approach 1:
The system performs preliminary detection of microburst conditions by monitoring wind speed and direction changes before the full microburst impact occurs. The control system proactively prepares and switches to enhanced control laws when microburst conditions are detected, rather than reacting after the damage has already occurred. This preliminary action allows the system to maintain reliability by addressing hazards before they become critical.
Solution Approach 2:
The system continuously monitors flight parameters including wind speed, wind direction, and aircraft performance metrics. This feedback loop allows the control system to detect microburst conditions in real-time and dynamically adjust control inputs. The feedback mechanism enables the system to distinguish between normal turbulence and microburst conditions, switching to appropriate control strategies based on the detected state.
2Reliability
If autonomous operation is implemented in UAVs, then the loss of human operators is reduced, but the ability to detect and respond to weather hazards deteriorates
Solution Approach 1:
The autonomous UAV is equipped with self-service capabilities including onboard weather radar, anemometers, and flight control systems that automatically detect microburst conditions and execute recovery maneuvers without human intervention. The system monitors its own flight parameters and environmental conditions, making independent decisions to adjust pitch, roll, and thrust to escape microburst hazards. This self-service approach resolves the contradiction by enabling autonomous systems to detect and respond to hazards as effectively as manned aircraft.
Solution Approach 2:
The patent introduces an intermediary control system that acts as a bridge between autonomous flight operations and hazard detection. This intermediary layer processes sensor data from weather radar and wind sensors, interprets microburst conditions, and generates appropriate control commands. The intermediary enables the autonomous UAV to perceive and respond to weather hazards by translating raw sensor data into meaningful flight control actions.
3Measurement precision
If communication link is maintained with ground station, then the measurement precision of hazard detection is improved, but the loss of information in microburst conditions worsens
Solution Approach 1:
The system uses onboard sensors including weather radar and anemometers as intermediary detection devices that operate independently of ground station communication. These onboard instruments directly measure wind speed, wind direction, and atmospheric conditions, providing hazard detection capability that does not rely on external communication links. This intermediary approach ensures measurement precision is maintained even when communication with the ground station is lost during microburst events.
Solution Approach 2:
The hazard detection system is segmented into multiple independent sensor modules including weather radar, anemometers, and flight performance sensors. Each sensor provides redundant measurement capabilities, so if one sensor or communication link fails, other sensors continue to provide hazard detection data. This segmentation ensures that measurement precision is maintained through multiple independent measurement paths, reducing reliance on any single communication channel.
Data Source
AI summary
A flight control system is configured for controlling the flight of an aircraft through windshear conditions. The system has means for measuring values of selected flight performance states of the aircraft and a control system for operating flight control devices on the aircraft. A windshear detection system located on the aircraft uses at least some of the measured values of the selected flight performance states to calculate a gust average during flight for comparison to pre-determined values in a table for determining whether windshear conditions exist. The control system then operates at least some of the flight control devices in response to an output of the windshear detection system.