Adaptive Controller Using Unmeasured Engine Parameters
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Solution Overview
Problem
Conventional gas turbine engine control logic struggles to accommodate nonlinearities, uncertainties, and disturbances, leading to reduced engine performance due to the need for design margins that limit access to optimal engine states.
Innovation Solution
An adaptive control system that includes a real-time engine model module and an adaptive control module, which estimates engine parameters and adjusts power demand using control laws to improve engine performance by accommodating changes and operating conditions, thereby reducing design margins.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional control logic with design margins is used, then safety and reliability are ensured, but engine performance is reduced due to limited access to optimal engine states
Solution Approach 1:
The control logic transitions from static design margins to dynamic adaptive margins that automatically adjust based on real-time engine operating conditions, component health status, and environmental factors. This allows the system to maintain safety while accessing optimal performance states by continuously adapting control parameters rather than relying on fixed conservative margins
Solution Approach 2:
The system implements closed-loop feedback using real-time sensor data, health monitoring systems, and performance measurements to continuously update control decisions. This feedback mechanism enables the control logic to distinguish between safe and unsafe operating regions dynamically, allowing the engine to operate closer to performance limits while maintaining safety through active monitoring and adjustment
2Ease of manufacture
If linear point models are used for control design, then control logic development is simplified, but the system cannot adequately accommodate nonlinearities and uncertainties
Solution Approach 1:
The control system divides the operating envelope into multiple linear regions or operating modes, each with its own simplified control model. The system dynamically selects or blends between these segmented models based on current operating conditions, maintaining the simplicity of linear models while collectively covering the full nonlinear operating range
Solution Approach 2:
The control logic dynamically adjusts model parameters, gain schedules, and operating point selections based on real-time conditions. This allows the system to use simple linear models at each operating point while adapting parameters to account for nonlinearities and uncertainties across the full operating envelope
3Reliability
If design margins are increased to accommodate uncertainties and disturbances, then reliability is improved, but responsiveness and access to optimal engine states are reduced
Solution Approach 1:
The control margins transition from static conservative values to dynamic adaptive margins that automatically adjust their magnitude based on real-time uncertainty estimates, disturbance levels, and operating conditions. This allows the system to maintain large margins when uncertainties are high while reducing margins to minimal safe values when conditions are well-known, thereby improving responsiveness without sacrificing reliability
Data Source
AI summary
The disclosure includes a system that includes a real-time engine model module and an adaptive control module. The real-time engine model module is configured to determine an engine parameter estimate signal based on at least one feedback signal indicative of an operating parameter of an engine. The adaptive control module is configured to receive a power request signal and receive, from the real real-time engine model module, the engine parameter estimate signal. The adaptive control module is further configured to determine a power demand signal based on the power request signal and the engine parameter estimate signal, wherein the adaptive control module is configured to determine the power demand signal based on the power request signal using a set of control laws. The adaptive control module is further configured to output the power demand signal to control at least one component of the engine.