Gas Turbine MPC Weight Adjustment for Changing Flight Conditions
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Solution Overview
Problem
Existing model predictive controls in gas turbine engines have fixed weights for multiple goals, which do not adapt to changing conditions such as flight route, environmental concerns, or component health, limiting optimization flexibility.
Innovation Solution
A model predictive controller adjusts goal weights based on conditions like flight route, environmental factors, or component health, allowing dynamic optimization of thrust performance, fuel efficiency, and component lifing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed weights are assigned to multiple goals in model predictive control, then the control system is simple to implement, but it cannot adapt to changing conditions such as flight route, environmental concerns, or component health
Solution Approach 1:
The patent applies the dynamics principle by transforming the static, fixed weights into dynamic, adjustable weights that can change in real-time based on operating conditions. The model predictive controller now receives updated weight values from external devices or operators, allowing the control system to adapt to varying priorities (thrust performance, fuel efficiency, component lifing) without requiring complex structural changes to the controller architecture.
Solution Approach 2:
The patent implements parameter changes by modifying the weight parameters assigned to different control goals. Instead of changing the controller structure, the system adjusts the numerical weight values associated with each goal (thrust performance, fuel efficiency, component lifing) based on current operating conditions, flight route, environmental factors, and component health status, enabling flexible adaptation through simple parameter adjustment.
2Productivity
If goal weights are dynamically adjusted based on multiple conditions, then optimization flexibility is improved, but the complexity of weight management increases
Solution Approach 1:
The patent applies self-service by enabling operators or external devices to directly input and adjust the weight values without requiring complex automated decision-making algorithms within the controller itself. The system provides the capability for users to manage weights based on their knowledge of operational priorities, simplifying the controller's internal complexity while maintaining high optimization flexibility.
Solution Approach 2:
The patent implements universality by designing a weight management system that can handle multiple goals (thrust performance, fuel efficiency, component lifing) through a single, unified interface. The same mechanism accommodates different operating scenarios and priority combinations, allowing the system to serve multiple optimization objectives without requiring separate complex management systems for each goal.
3Reliability
If weighting priorities are changed in response to real-time conditions, then control performance is enhanced, but the time required for weight adjustment and implementation increases
Solution Approach 1:
The patent applies preliminary action by allowing weight adjustments to be prepared and input before critical operational changes occur. Operators can pre-set appropriate weight values based on anticipated conditions (such as upcoming flight phases or known environmental factors), and these weights are ready for immediate implementation when needed, reducing the time lag between condition change and optimal control response.
Data Source
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AI summary
A method of operating a gas turbine engine (20; 91; 152) includes the steps of 1) providing a model predictive controller (100) programmed to control end effectors (106) on the gas turbine engine (20; 91; 152) with a weighting assigned to a plurality of goals and 2) changing the weighting for at least one of the plurality of goals based upon conditions of at least one of the gas turbine engine (20; 91; 152), or an associated aircraft (90), flight route, or environmental concerns. An embedded processing system and a gas turbine engine (20; 91; 152) are also disclosed.