Learning optimal resource allocations in wireless systems
This paper considers the design of optimal resource allocation policies in wireless
communication systems, which are generically modeled as a functional optimization …
communication systems, which are generically modeled as a functional optimization …
Deep reinforcement learning for wireless sensor scheduling in cyber–physical systems
In many cyber–physical systems, we encounter the problem of remote state estimation of
geographically distributed and remote physical processes. This paper studies the …
geographically distributed and remote physical processes. This paper studies the …
Smart testing and selective quarantine for the control of epidemics
This paper is based on the observation that, during Covid-19 epidemic, the choice of which
individuals should be tested has an important impact on the effectiveness of selective …
individuals should be tested has an important impact on the effectiveness of selective …
A control approach to scheduling flexibly configurable jobs with dynamic structural-logical constraints
We study the problem of scheduling in manufacturing environments which are dynamically
reconfigurable for supporting highly flexible individual operation compositions of the jobs …
reconfigurable for supporting highly flexible individual operation compositions of the jobs …
Toward wireless control in industrial process automation: A case study at a paper mill
A Ahlén, J Akerberg, M Eriksson… - IEEE Control …, 2019 - ieeexplore.ieee.org
Wireless sensors and networks are used only occasionally in current control loops in the
process industry. With rapid developments in embedded and highperformance computing …
process industry. With rapid developments in embedded and highperformance computing …
Control aware radio resource allocation in low latency wireless control systems
We consider the problem of allocating radio resources over wireless communication links to
control a series of independent wireless control systems. Low-latency transmissions are …
control a series of independent wireless control systems. Low-latency transmissions are …
Deep learning for wireless networked systems: A joint estimation-control-scheduling approach
Wireless-networked control system (WNCS) connecting sensors, controllers, and actuators
via wireless communications is a key enabling technology for highly scalable and low-cost …
via wireless communications is a key enabling technology for highly scalable and low-cost …
Transmission scheduling for multi-process multi-sensor remote estimation via approximate dynamic programming
In this paper, we consider a remote estimation problem where multiple dynamical systems
are observed by smart sensors, which transmit their local estimates to a remote estimator …
are observed by smart sensors, which transmit their local estimates to a remote estimator …
Resilient control in cyber-physical systems: Countering uncertainty, constraints, and adversarial behavior
Abstract Cyber-Physical Systems (CPS), the amalgamation of sophisticated sensing,
communication, and computing technologies, applied to physical spaces, have become …
communication, and computing technologies, applied to physical spaces, have become …
Optimal sensor scheduling for remote state estimation with limited bandwidth: a deep reinforcement learning approach
This paper considers co-scheduling for multiple sensors to observe multiple dynamical
systems. The measurements obtained by the sensors need to be transmitted to the remote …
systems. The measurements obtained by the sensors need to be transmitted to the remote …