Robot learning from randomized simulations: A review
The rise of deep learning has caused a paradigm shift in robotics research, favoring
methods that require large amounts of data. Unfortunately, it is prohibitively expensive to …
methods that require large amounts of data. Unfortunately, it is prohibitively expensive to …
Secure estimation and control for cyber-physical systems under adversarial attacks
The vast majority of today's critical infrastructure is supported by numerous feedback control
loops and an attack on these control loops can have disastrous consequences. This is a …
loops and an attack on these control loops can have disastrous consequences. This is a …
Performance, precision, and payloads: Adaptive nonlinear mpc for quadrotors
Agile quadrotor flight in challenging environments has the potential to revolutionize
ship**, transportation, and search and rescue applications. Nonlinear model predictive …
ship**, transportation, and search and rescue applications. Nonlinear model predictive …
Safe learning of regions of attraction for uncertain, nonlinear systems with gaussian processes
Control theory can provide useful insights into the properties of controlled, dynamic systems.
One important property of nonlinear systems is the region of attraction (ROA), a safe subset …
One important property of nonlinear systems is the region of attraction (ROA), a safe subset …
Coordinated distributed predictive control for voltage regulation of DC microgrids with communication delays and data loss
Y Yu, GP Liu, W Hu - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
This paper is concerned with the voltage tracking problem of DC microgrids subject to
communication delays and packet losses, for which existing work commonly adopts passive …
communication delays and packet losses, for which existing work commonly adopts passive …
Safe and robust learning control with Gaussian processes
This paper introduces a learning-based robust control algorithm that provides robust stability
and performance guarantees during learning. The approach uses Gaussian process (GP) …
and performance guarantees during learning. The approach uses Gaussian process (GP) …
Runtime assurance for safety-critical systems: An introduction to safety filtering approaches for complex control systems
More than three miles above the Arizona desert, an F-16 student pilot experienced a gravity-
induced loss of consciousness, passing out while turning at nearly 9Gs (nine times the force …
induced loss of consciousness, passing out while turning at nearly 9Gs (nine times the force …
Disturbance and uncertainty attenuation for speed regulation of PMSM servo system using adaptive optimal control strategy
This article proposes an adaptive optimal control scheme to minimize the effect of
disturbances and uncertainties of permanent magnet synchronous motor (PMSM). In the …
disturbances and uncertainties of permanent magnet synchronous motor (PMSM). In the …
Secure state-estimation for dynamical systems under active adversaries
We consider the problem of state-estimation of a linear dynamical system when some of the
sensor measurements are corrupted by an adversarial attacker. The errors injected by the …
sensor measurements are corrupted by an adversarial attacker. The errors injected by the …
An analytical and numerical sensitivity and robustness analysis of wave energy control systems
Considerable effort has been expended on the design of control systems for wave energy
converters (WECs) over the past two decades. Working from the fundamental requirement of …
converters (WECs) over the past two decades. Working from the fundamental requirement of …