41 citations · 115 across the 18 of their papers we have counts for
8 papers · 1 filter
Scalable Forward Reachability Analysis of Multi-Agent Systems with Neural Network Controllers
Oliver Gates, Matthew Newton, Konstantinos Gatsis
Neural networks (NNs) have been shown to learn complex control laws successfully, often with performance advantages or decreased computational cost compared to alternative methods.…
Stable and Safe Reinforcement Learning via a Barrier-Lyapunov Actor-Critic Approach
Liqun Zhao, Konstantinos Gatsis, Antonis Papachristodoulou
Reinforcement learning (RL) has demonstrated impressive performance in various areas such as video games and robotics. However, ensuring safety and stability, which are two critica…
Learning Robust State Observers using Neural ODEs (longer version)
Keyan Miao, Konstantinos Gatsis
Relying on recent research results on Neural ODEs, this paper presents a methodology for the design of state observers for nonlinear systems based on Neural ODEs, learning Luenberg…
Statistical Learning for Analysis of Networked Control Systems over Unknown Channels
Konstantinos Gatsis, George J. Pappas
Recent control trends are increasingly relying on communication networks and wireless channels to close the loop for Internet-of-Things applications. Traditionally these approaches…
Optimal Resource Allocation in Wireless Control Systems via Deep Policy Gradient
Vinicius Lima Silva, Mark Eisen, Konstantinos Gatsis +1
In wireless control systems, remote control of plants is achieved through closing of the control loop over a wireless channel. As wireless communication is noisy and subject to pac…
An Information Matrix Approach for State Secrecy
Anastasios Tsiamis, Konstantinos Gatsis, George Pappas
This paper studies the problem of remote state estimation in the presence of a passive eavesdropper. A sensor measures a linear plant's state and transmits it to an authorized user…
State-Secrecy Codes for Networked Linear Systems
Anastasios Tsiamis, Konstantinos Gatsis, George J. Pappas
In this paper, we study the problem of remote state estimation, in the presence of a passive eavesdropper. An authorized user estimates the state of an unstable linear plant, based…
State Estimation with Secrecy against Eavesdroppers
Anastasios Tsiamis, Konstantinos Gatsis, George J. Pappas
We study the problem of remote state estimation, in the presence of an eavesdropper. An authorized user estimates the state of a linear plant, based on the data received from a sen…