Gas Turbine Engine Control with Real-Time Performance Seeking
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Solution Overview
Problem
Existing gas turbine engine control systems face challenges in optimizing performance across varying flight conditions and engine wear, with limitations in accurately adjusting fuel flow, compressor geometry, and propeller pitch to maximize efficiency and minimize fuel consumption.
Innovation Solution
A controller system that incorporates a piece-wise linear state-space model with an observer and optimization module, which adjusts engine parameters using measured values and sensitivity relations to generate optimized control signals, improving engine performance by updating the model in real-time and accounting for actual operating conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a baseline controller generates engine commands based on standard operating procedures, then the engine operates reliably under normal conditions, but it cannot optimize performance under varying flight conditions and engine wear
Solution Approach 1:
The controller is divided into a baseline controller that handles standard operations and a delta controller that handles performance optimization. This segmentation allows the system to maintain reliability through the baseline controller while adding optimization capabilities through the delta controller without requiring complete redesign of the entire control system.
Solution Approach 2:
The controller transitions from a static baseline design to a dynamic system that adapts to varying flight conditions and engine wear. The delta controller continuously adjusts engine commands based on real-time sensor data and optimization algorithms, enabling the system to optimize performance under different operating conditions.
2Productivity
If the controller uses fixed control parameters, then the system is simple to implement, but it cannot accurately adjust fuel flow, compressor geometry, and propeller pitch to maximize efficiency
Solution Approach 1:
The optimization controller implements feedback mechanisms that continuously monitor engine performance parameters and adjust control commands accordingly. Sensor data on fuel flow, compressor geometry, and propeller pitch are fed back to the delta controller, which uses optimization algorithms to maximize fuel efficiency while accounting for varying operating conditions.
Solution Approach 2:
The system dynamically changes control parameters such as fuel flow rate, compressor geometry angles, and propeller pitch based on optimization calculations. These parameter adjustments are made in real-time to maximize fuel efficiency under different flight conditions, replacing fixed parameters with adaptive variable parameters.
3Reliability
If the controller does not account for engine wear and changing conditions, then the control logic remains simple, but performance degrades over time and under varying operating conditions
Solution Approach 1:
The system performs preliminary actions by developing a delta engine model that anticipates performance degradation due to wear and changing conditions. The optimization controller uses this model to pre-calculate adjusted commands that compensate for expected performance variations, maintaining consistent reliability over time without requiring complex real-time adjustments.
Data Source
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AI summary
A gas turbine engine control system is disclosed having a model and an observer that together can be used to adjust a command issued to the gas turbine engine or associated equipment to improve performance. In one form the control system includes a nominal model that is adjusted to real time conditions. The adjusted model is used with a Kalman filter and is ultimately used to determine a perturbation to a control signal. In one form the perturbation can be to a legacy controller.