Extreme ultra-reliable and low-latency communication
Ultra-reliable and low-latency communication (URLLC) is central to fifth-generation (5G)
communication systems, but the fundamentals of URLLC remain elusive. New immersive …
communication systems, but the fundamentals of URLLC remain elusive. New immersive …
Control principles of complex systems
YY Liu, AL Barabási - Reviews of Modern Physics, 2016 - APS
A reflection of our ultimate understanding of a complex system is our ability to control its
behavior. Typically, control has multiple prerequisites: it requires an accurate map of the …
behavior. Typically, control has multiple prerequisites: it requires an accurate map of the …
Reinforcement learning for safety-critical control under model uncertainty, using control lyapunov functions and control barrier functions
In this paper, the issue of model uncertainty in safety-critical control is addressed with a data-
driven approach. For this purpose, we utilize the structure of an input-ouput linearization …
driven approach. For this purpose, we utilize the structure of an input-ouput linearization …
Learning for safety-critical control with control barrier functions
Modern nonlinear control theory seeks to endow systems with properties of stability and
safety, and have been deployed successfully in multiple domains. Despite this success …
safety, and have been deployed successfully in multiple domains. Despite this success …
[图书][B] State estimation for robotics
TD Barfoot - 2024 - books.google.com
A key aspect of robotics today is estimating the state (eg, position and orientation) of a robot,
based on noisy sensor data. This book targets students and practitioners of robotics by …
based on noisy sensor data. This book targets students and practitioners of robotics by …
Implicit bias of the step size in linear diagonal neural networks
MS Nacson, K Ravichandran… - International …, 2022 - proceedings.mlr.press
Focusing on diagonal linear networks as a model for understanding the implicit bias in
underdetermined models, we show how the gradient descent step size can have a large …
underdetermined models, we show how the gradient descent step size can have a large …
Data-driven discovery of Koopman eigenfunctions for control
Data-driven transformations that reformulate nonlinear systems in a linear framework have
the potential to enable the prediction, estimation, and control of strongly nonlinear dynamics …
the potential to enable the prediction, estimation, and control of strongly nonlinear dynamics …
A social learning particle swarm optimization algorithm for scalable optimization
Social learning plays an important role in behavior learning among social animals. In
contrast to individual (asocial) learning, social learning has the advantage of allowing …
contrast to individual (asocial) learning, social learning has the advantage of allowing …
Recent developments on the stability of systems with aperiodic sampling: An overview
This article presents basic concepts and recent research directions about the stability of
sampled-data systems with aperiodic sampling. We focus mainly on the stability problem for …
sampled-data systems with aperiodic sampling. We focus mainly on the stability problem for …
Optimal tracking control of nonlinear partially-unknown constrained-input systems using integral reinforcement learning
In this paper, a new formulation for the optimal tracking control problem (OTCP) of
continuous-time nonlinear systems is presented. This formulation extends the integral …
continuous-time nonlinear systems is presented. This formulation extends the integral …