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to enhance our multidisciplinary research at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement
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chargers, or nonlinear loads Experience in hardware-in-the-loop testbeds and digital twin creation Experience with SEL RTAC 3555 or similar Experience in advanced microgrid controls such as nonlinear methods
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to guarantee user-defined error bounds of reachable sets for nonlinear and hybrid systems. This project will exactly close this research gap: We will develop essentially new methods to ensure that algorithmic
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