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Articles 1 - 3 of 3
Full-Text Articles in Systems Science
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca
Publications
As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …
Data Compression In Additive Manufacturing: Recent Progress And Opportunities, Dongmin Ethan Kang, Wenmeng Tian
Data Compression In Additive Manufacturing: Recent Progress And Opportunities, Dongmin Ethan Kang, Wenmeng Tian
Publications
A crucial aspect of quality control for Additive Manufacturing (AM) processes is the acquisition of diverse data from the entire lifecycle of the product. AM data has grown significantly in terms of diversity and volumes, resulting in diverse data formats of increasing volumes, including time series, images, and point clouds. Large quantities of these data are essential for effective in-situ process monitoring and ex-situ non-destructive evaluation. However, this will result in large manufacturing and inspection datasets that are difficult to manage for users, which will delay the broader adoption of AM for mission critical applications. This motivates the urgent need …
Event-Triggered Optimal Adaptive Control Of Partially Unknown Linear Continuous-Time Systems With State Delay, Rohollah Moghadam, Vignesh Narayanan, Sarangapani Jagannathan
Event-Triggered Optimal Adaptive Control Of Partially Unknown Linear Continuous-Time Systems With State Delay, Rohollah Moghadam, Vignesh Narayanan, Sarangapani Jagannathan
Publications
This paper proposes an event-triggered optimal adaptive output feedback control design approach by utilizing integral reinforcement learning (IRL) for linear time-invariant systems with state delay and uncertain internal dynamics. In the proposed approach, the general optimal control problem is formulated into the game-theoretic framework by treating the event-triggering threshold and the optimal control policy as players. A cost function is defined and a value functional, which includes the delayed system output, is considered. First, by using the value functional and applying stationarity conditions using the Hamiltonian function, the output game delay algebraic Riccati equation (OGDARE) and optimal control policy are …