Nonlinear Aircraft Simulation Balancing via Adaptive Model Correction
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Solution Overview
Problem
Current aircraft simulation balancing methods are inefficient due to reliance on linear modeling, which is sensitive to errors and lacks generality, determinism, and repetitiveness, especially when dealing with nonlinear systems, leading to inaccurate control variables and increased simulation time.
Innovation Solution
A simulation platform with a nonlinear system balancing device using a servoing loop and modeling corrector to refine the simplified model of the nonlinear system, incorporating filters for model inversion and error correction, allowing for decoupling of controls and improved convergence towards precise modeling differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If linear modeling is used for balancing, then the balancing process is simpler and faster, but the accuracy and reliability deteriorate due to sensitivity to errors and lack of generality for nonlinear systems
Solution Approach 1:
The patent transforms the static linear model into a dynamic adaptive model that automatically adjusts to nonlinear system characteristics. The model correction loop continuously updates the simplified model based on actual system responses, enabling the system to adapt to changing conditions while maintaining both speed and accuracy in balancing operations.
Solution Approach 2:
The patent implements a feedback mechanism through the model correction loop that uses actual system outputs to refine the simplified model. This feedback loop compares predicted outputs from the simplified model with actual measurements, generating corrections that improve modeling accuracy while preserving the computational efficiency of the original simplified structure.
2Device complexity
If a simplified model is used for balancing, then computational complexity is reduced and processing time decreases, but modeling errors increase leading to inaccurate control variables
Solution Approach 1:
The patent uses feedback to correct modeling errors by continuously comparing simplified model predictions with actual system behavior. The model correction loop adjusts the simplified model parameters based on measurement discrepancies, thereby improving control variable accuracy without requiring complex computations.
Solution Approach 2:
The patent dynamically changes model parameters through the correction loop, adjusting the simplified model to better fit actual system characteristics. This parameter adaptation allows the system to maintain high accuracy with simple computational structures by learning from actual operational data.
3Loss of time
If conventional balancing methods are used, then the process is faster, but determinism and repetitiveness are lost due to sensitivity to modeling errors
Solution Approach 1:
The feedback mechanism in the model correction loop ensures deterministic results by systematically eliminating modeling errors. The loop consistently applies corrections based on actual system responses, producing reproducible balancing results that are independent of initial model inaccuracies, thereby achieving both speed and determinism.
Data Source
AI summary
Balancing a simulation platform including a nonlinear aeronautical system, the balancing including servoing of an output value of the system to a recorded value, including a first filter producing an inversion of a simplified model of the system for generating a control for the system based on a model correction information item estimating a modeling error of the simplified model and an information item on difference between the output value and the recorded value, and a modeling corrector looping including a second filter using the simplified model to calculate, based on the control and the output value, the model correction item to be supplied to the first filter.