Deep reinforcement learning control approach to mitigating actuator attacks

This paper investigates the deep reinforcement learning based secure control problem for cyber–physical systems (CPS) under false data injection attacks. We describe the CPS under attacks as a Markov decision process (MDP), based on which the secure controller design for CPS under attacks is formulated as an action policy learning using data....

Decentralized periodic event-triggered control with quantization and asynchronous communication

Asynchronous decentralized event-triggered control (ADETC) Mazo Jr. and Cao (2014) is an implementation of controllers characterized by decentralized event generation, asynchronous sampling updates, and dynamic quantization. Combining those elements in ADETC results in a parsimonious transmission of information which makes it suitable for...