Zobrazeno 1 - 10
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pro vyhledávání: '"Doyle, P C"'
This paper focuses on the need for a rigorous theory of layered control architectures (LCAs) for complex engineered and natural systems, such as power systems, communication networks, autonomous robotics, bacteria, and human sensorimotor control. All
Externí odkaz:
http://arxiv.org/abs/2401.15185
Incorporating pattern-learning for prediction (PLP) in many discrete-time or discrete-event systems allows for computation-efficient controller design by memorizing patterns to schedule control policies based on their future occurrences. In this pape
Externí odkaz:
http://arxiv.org/abs/2305.05587
Animals move smoothly and reliably in unpredictable environments. Models of sensorimotor control have assumed that sensory information from the environment leads to actions, which then act back on the environment, creating a single, unidirectional pe
Externí odkaz:
http://arxiv.org/abs/2211.05922
Autor:
Kjellqvist, Olle, Doyle, John C.
We present a new, scalable alternative to the structured singular value, which we call $\nu$, provide a convex upper bound, study their properties and compare them to $\ell_1$ robust control. The analysis relies on a novel result on the relationship
Externí odkaz:
http://arxiv.org/abs/2204.05359
Autor:
Li, Jing Shuang, Doyle, John C.
We present D-Phi iteration: an algorithm for distributed, localized, and scalable robust control of systems with structured uncertainties. This algorithm combines the System Level Synthesis (SLS) parametrization for distributed control with stability
Externí odkaz:
http://arxiv.org/abs/2204.02493
Autor:
Sarma, Anish A., Li, Jing Shuang, Stenberg, Josefin, Card, Gwyneth, Heckscher, Elizabeth S., Kasthuri, Narayanan, Sejnowski, Terrence, Doyle, John C.
Feedback is ubiquitous in both biological and engineered control systems. In biology, in addition to typical feedback between plant and controller, we observe feedback pathways within control systems, which we call internal feedback pathways (IFPs),
Externí odkaz:
http://arxiv.org/abs/2110.05029
Neural architectures in organisms support efficient and robust control that is beyond the capability of engineered architectures. Unraveling the function of such architectures is challenging; their components are highly diverse and heterogeneous in t
Externí odkaz:
http://arxiv.org/abs/2109.11752
Descending predictive feedback (DPF) is an ubiquitous yet unexplained phenomenon in the central nervous system. Motivated by recent observations on motor-related signals in the visual system, we approach this problem from a sensorimotor standpoint an
Externí odkaz:
http://arxiv.org/abs/2103.16812
Publikováno v:
Proceedings of The 24th International Conference on Artificial Intelligence and Statistics 2021, PMLR 130:3475-3483
Robust control is a core approach for controlling systems with performance guarantees that are robust to modeling error, and is widely used in real-world systems. However, current robust control approaches can only handle small system uncertainty, an
Externí odkaz:
http://arxiv.org/abs/2103.11055
The System Level Synthesis (SLS) approach facilitates distributed control of large cyberphysical networks in an easy-to-understand, computationally scalable way. We present an overview of the SLS approach and its associated extensions in nonlinear co
Externí odkaz:
http://arxiv.org/abs/2010.01292