Observer-Based Flare Landing Control for Aircraft Elevators
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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 phases like the aircraft flare regime where precise control is necessary.
Innovation Solution
An observer-based control system that uses a transfer function of an observer model to estimate the state of an aircraft parameter, determining a gain value based on measured states, and adjusting altitude control inputs to control the aircraft's elevator, thereby facilitating automatic landing during the flare regime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If observer-based control algorithms are used to estimate vehicle state, then control accuracy is improved when state is unknown, but computational processing power requirements increase
Solution Approach 1:
The control algorithm is segmented into distinct functional blocks: observer model block, transfer function block, gain calculation block, and control command generation block. This segmentation allows each component to be optimized independently and executed efficiently on embedded processors with limited computational resources while maintaining accurate state estimation.
Solution Approach 2:
The system dynamically adjusts gain values based on measured state parameters and operates in different flight regimes (approach, flare, touchdown). By changing control parameters adaptively rather than using fixed complex algorithms, the system achieves high estimation accuracy with reduced computational burden compared to constant high-complexity observer implementations.
2Reliability
If complex control algorithms are implemented to handle unknown vehicle state, then control reliability is improved, but device complexity increases
Solution Approach 1:
The control system is divided into modular functional blocks that can be independently validated and tested. The observer model, transfer function, and gain calculation are separate executable modules, making the overall complex system more manageable and reliable through structured decomposition.
Solution Approach 2:
The observer-based control system continuously compares estimated state with measured state and adjusts control commands accordingly. This feedback mechanism ensures reliable control by constantly correcting estimation errors and adapting to changing flight conditions, maintaining high reliability without requiring overly complex open-loop algorithms.
3Manufacturing precision
If state estimation algorithms are used during flare regime, then automatic landing precision is improved, but computational burden increases
Solution Approach 1:
The control system dynamically adapts its behavior based on flight regime detection. During the flare regime, the observer model and transfer function are activated with specific parameters optimized for landing precision. The system transitions between different operational modes (approach, flare, touchdown) with adjusted computational intensity, achieving high precision during critical phases without maintaining maximum computational burden throughout the entire flight.
Solution Approach 2:
Control parameters including gain values and observer model parameters are specifically tuned for the flare regime to maximize landing precision. By changing parameters adaptively rather than using fixed high-complexity algorithms throughout all flight phases, the system achieves precise automatic landing during the critical flare regime with optimized computational requirements.
Data Source
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.