Aircraft Flare Landing Control Using Observer-Based State Estimation
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Solution Overview
Problem
Vehicle control systems face challenges in generating control commands when the state of a vehicle is unknown, requiring additional processing power for complex algorithmic calculations based on advanced control theory techniques, especially during maneuvers like landing where precise control is crucial.
Innovation Solution
The implementation of an observer-based control method using a transfer function to estimate the state of an aircraft parameter, determining a gain value, and adjusting the estimate based on differences between altitude commands and outputs, allowing for precise control of the aircraft's elevator during the flare regime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If observer-based control is implemented to handle unknown vehicle states, then control capability is improved, but processing power requirements increase
Solution Approach 1:
The control system is divided into multiple independent modules: an observer module that estimates vehicle states, a control law module that generates control commands, and an execution module that applies controls. This segmentation allows each module to perform specialized functions with optimized computational requirements, reducing overall processing power needs while maintaining control capability.
Solution Approach 2:
The observer module pre-calculates and estimates vehicle states before the control law module generates control commands. By performing state estimation in advance, the system avoids computationally intensive real-time calculations during critical control moments, thereby reducing processing power requirements while ensuring reliable control capability.
2Measurement precision
If complex algorithmic calculations are performed to estimate vehicle state, then measurement precision is improved, but device complexity increases
Solution Approach 1:
An observer module acts as an intermediary between sensor measurements and control commands. This intermediary performs state estimation using a mathematical model that relates measurable quantities to unmeasured vehicle states, providing accurate state information without requiring direct complex measurements, thus improving measurement precision while managing algorithm complexity.
Solution Approach 2:
The system replaces direct physical measurement of difficult-to-measure vehicle states with computational estimation using sensor data and mathematical models. This substitution of mechanical/physical measurement with computational methods achieves high measurement precision while avoiding the complexity of direct sensing for all vehicle parameters.
Data Source
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AI summary
Methods, apparatus, and articles of manufacture for observer-based landing control of a vehicle are disclosed. An example apparatus includes at least one memory, and at least one processor to execute instructions to at least in response to determining an aircraft is in a flight plan flare regime, determine an estimate state of an aircraft parameter based on an execution of a transfer function of an observer model, the execution of the transfer function based on an altitude command corresponding to the flare regime, determine a gain value based on the aircraft parameter, determine an altitude control input based on the estimate state and the gain value, determine an altitude command output based on the altitude control input and longitudinal dynamics of the aircraft, the longitudinal dynamics generated in response to the aircraft executing the altitude command output, and control an elevator of the aircraft based on the altitude command output.