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DTSTART;TZID=America/Los_Angeles:20250811T140000
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DTSTAMP:20260428T072509
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UID:10000095-1754920800-1754920800@events.ucsc.edu
SUMMARY:Montenegro\, C. (ECE) - Control of Uncertain Hybrid Systems
DESCRIPTION:Machine learning endows autonomous systems to uncover underlying structures and physical laws from measured data and to leverage these models for prediction and decision-making. As the costs of data acquisition\, processing\, and storage decline—and sensors become increasingly widespread alongside ever-improving algorithms—artificial intelligence has attracted significant attention in research and industry. \n Machine-learning methods are particularly attractive when an analytical model is too difficult—or even impossible—to derive because the underlying principles are poorly understood. As control engineering enters such domains—for example\, physical human-robot interaction and self-driving vehicles—data-driven models offer a practical alternative to classical system-identification techniques for model-based control. In addition\, we know that robotic or control systems seldom work in ideal conditions. Sensor noise\, incomplete state information\, and uncertain parameters are everyday realities\, and controllers must be robust—able to attenuate these disturbances—and be backed by formal guarantees of stability and safety. \n Coupling physical dynamics with embedded computation and communication introduces new challenges. Hardware elements such as analog-to-digital converters\, sample-and-hold circuits\, and quantizers\, together with events like timers\, resets\, and impacts\, yield an even more complex class of control systems in which designing controllers that remain robust to unmodeled dynamics and disturbances—and providing formal certificates of stability and safety—becomes harder. Cyber-physical systems that have continuous dynamics with event-driven behavior\, therefore\, require control strategies that explicitly account for these events and stay robust to adversarial uncertainties. \n Therefore\, the focus of this proposal is to design learning-based certificates and control techniques for hybrid systems with uncertainties in the form of unmodeled dynamics and unknown disturbances. We propose four research thrusts in this proposal. The first one addresses the problem of learning a surrogate model of the unmodeled using learning-based models that are both statistically sound and directly usable for feedback design. In the second thrust\, we develop a safety control framework for systems whose dynamics are learned with high probability using a set-valued and variational analysis. In our third thrust\, we consider the problem of learning certificates—in particular\, Lyapunov functions and cost upper-bound surrogates—for hybrid systems. Finally\, we tackle the optimal control problem for hybrid systems under unknown disturbances in our fourth thrust. \nEvent Host: Carlos Montenegro\, PhD Student\, Electrical & Computer Engineering \nAdvisor: Ricardo Sanfelice
URL:https://events.ucsc.edu/event/montenegro-c-ece-control-of-uncertain-hybrid-systems/
LOCATION:CA
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DTSTART;TZID=America/Los_Angeles:20250811T183000
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DTSTAMP:20260428T072509
CREATED:20250924T212216Z
LAST-MODIFIED:20250924T212216Z
UID:10000080-1754937000-1754937000@events.ucsc.edu
SUMMARY:August Slugs & Steins with Professor Nancy N. Chen
DESCRIPTION:Breathing in the Anthropocene: Reflections on Breath\, Air\, and Vitality \nThis presentation examines breathing in the present moment when humans vastly transform Earth ecosystems that impact health and well-being. Atmospheric transformations via worsened air highlight connections of breath with health. How might breath be shaped by cultural and individual experiences? Ethnographic research at the intersections of medical and environmental anthropology have renewed attention on energetic relations between bodies\, landscapes\, air\, and health\, especially the role of vital energy in qi\, prana\, or ha. In addition to these breath centered approaches\, we examine recent biomedical research on breath management across a broad range of complementary medicine and health interventions.
URL:https://events.ucsc.edu/event/august-slugs-steins-with-professor-nancy-n-chen/
LOCATION:CA
CATEGORIES:Lectures & Presentations
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