COE Faculty Works
Permanent URI for this collectionhttps://hdl.handle.net/1969.6/94847
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Browsing COE Faculty Works by Subject "aerospace electronics"
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Item A scalable sampling method to high-dimensional uncertainties for optimal and reinforcement learning-based controls(IEEE, 2017-05-26) Xie, Junfei; Wan, Yan; Mills, Kevin; Filliben, James; Lewis, FrankModern dynamical systems often operate in environments of high-dimensional uncertainties that modulate system dynamics in a complicated fashion. These high-dimensional uncertainties, non-Gaussian in many realistic scenarios, complicate real-time system analysis, design, and control tasks. In this letter, we address the scalability of computation for systems of high-dimensional uncertainties by introducing new sampling methods, the multivariate probabilistic collocation method (M-PCM), and its extension called M-PCM-orthogonal fractional factorial design (OFFD) which integrates M-PCM with the OFFDs to break the curse of dimensionality. We explore the capabilities of M-PCM and M-PCM-OFFD-based optimal control and adaptive control using the reinforcement learning approach. The analyses and simulation studies illustrate the efficiency and effectiveness of these two approaches.