Data-Assisted Control -- A Framework Development by Exploiting NASA GTM Platform
Mostafa Eslami, Afshin Banazadeh

TL;DR
This paper introduces a Data-Assisted Control framework for aerospace vehicles that combines model-based control with real-time data to improve performance, especially in damage scenarios, demonstrated on NASA GTM platform.
Contribution
The paper proposes a novel Data-Assisted Control framework integrating data support with model-based control for aerospace vehicles, enhancing robustness during damage events.
Findings
Data assistance improves control performance during damage.
The framework maintains stability during transition phases.
Simulations validate the effectiveness of the combined approach.
Abstract
Today's focus on expanding the capabilities of control systems, resulting from the abundance of data and computational resources, requires data-based alternatives over model-based ones. These alternatives may become the sole tool for analysis and synthesis. Nevertheless, mathematical models are available to some extent, especially for air and space vehicles. Hypothetically, data assistance would be the approach to meet the requirements in collaboration with the model. In this paper, a framework of Data-Assisted Control (DAC) for aerospace vehicles is proposed. NASA Generic Transport Model (GTM) is the platform for the study and the data supports the model-based controller in extending performance over a damage event. The framework requires real-time decisions to override the control law with the information obtained from the data, while the model-based controller does not show regular…
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Taxonomy
TopicsTarget Tracking and Data Fusion in Sensor Networks · Fault Detection and Control Systems · Gaussian Processes and Bayesian Inference
