57 citations · 238 across the 15 of their papers we have counts for
16 papers
Data-driven Self-triggered Control via Trajectory Prediction
Wenjie Liu, Jian Sun, Gang Wang +2
Self-triggered control, a well-documented technique for reducing the communication overhead while ensuring desired system performance, is gaining increasing popularity. However, ex…
Data-Driven Resilient Predictive Control under Denial-of-Service
Wenjie Liu, Jian Sun, Gang Wang +2
The study of resilient control of linear time-invariant (LTI) systems against denial-of-service (DoS) attacks is gaining popularity in emerging cyber-physical applications. In prev…
Data-driven Control of Dynamic Event-triggered Systems with Delays
Xin Wang, Jian Sun, Julian Berberich +3
This paper studies data-driven control of unknown sampled-data systems with communication delays under an event-triggering transmission mechanism. Data-based representations for ti…
Resonant Beam Communications with Echo Interference Elimination
Mingliang Xiong, Qingwen Liu, Gang Wang +4
Resonant beam communications (RBCom) is capable of providing wide bandwidth when using light as the carrier. Besides, the RBCom system possesses the characteristics of mobility, hi…
Resilient Control under Quantization and Denial-of-Service: Co-designing a Deadbeat Controller and Transmission Protocol
Wenjie Liu, Jian Sun, Gang Wang +2
This paper is concerned with the problem of stabilizing continuous-time linear time-invariant systems subject to quantization and Denial-of-Service (DoS) attacks. In this context,…
Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data
Alireza Sadeghi, Gang Wang, Meng Ma +1
Data used to train machine learning models can be adversarial--maliciously constructed by adversaries to fool the model. Challenge also arises by privacy, confidentiality, or due t…
Reinforcement Learning for Caching with Space-Time Popularity Dynamics
Alireza Sadeghi, Georgios B. Giannakis, Gang Wang +1
With the tremendous growth of data traffic over wired and wireless networks along with the increasing number of rich-media applications, caching is envisioned to play a critical ro…
Wireless Power Transmitter Deployment for Balancing Fairness and Charging Service Quality
Mingqing Liu, Gang Wang, Georgios B. Giannakis +3
Wireless Energy Transfer (WET) has recently emerged as an appealing solution for power supplying mobile / Internet of Things (IoT) devices. As an enabling WET technology, Resonant…
Channel-Dependent Scheduling in Wireless Energy Transfer for Mobile Devices
Wen Fang, Gang Wang, Georgios B. Giannakis +3
Resonant Beam Charging (RBC) is the Wireless Power Transfer (WPT) technology, which can provide high-power, long-distance, mobile, and safe wireless charging for Internet of Things…
Resonant Beam Communications: Principles and Designs
Mingliang Xiong, Qingwen Liu, Gang Wang +2
Wireless optical communications (WOC) has carriers up to several hundred terahertz, which offers several advantages, such as ultrawide bandwidth and no electromagnetic interference…
Gauss-Newton Unrolled Neural Networks and Data-driven Priors for Regularized PSSE with Robustness
Qiuling Yang, Alireza Sadeghi, Gang Wang +2
Distributed renewable generation, elastic loads, and purposeful manipulation of meter readings challenge the monitoring and control of today's power systems (PS). In this context,…
Learning Connectivity and Higher-order Interactions in Radial Distribution Grids
Qiuling Yang, Mario Coutino, Gang Wang +2
To perform any meaningful optimization task, distribution grid operators need to know the topology of their grids. Although power grid topology identification and verification has…
Finite-Sample Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation
Jun Sun, Gang Wang, Georgios B. Giannakis +2
Motivated by the emerging use of multi-agent reinforcement learning (MARL) in engineering applications such as networked robotics, swarming drones, and sensor networks, we investig…
A Statistical Learning Approach to Reactive Power Control in Distribution Systems
Qiuling Yang, Alireza Sadeghi, Gang Wang +2
Pronounced variability due to the growth of renewable energy sources, flexible loads, and distributed generation is challenging residential distribution systems. This context, moti…
A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation
Gang Wang, Bingcong Li, Georgios B. Giannakis
Motivated by the widespread use of temporal-difference (TD-) and Q-learning algorithms in reinforcement learning, this paper studies a class of biased stochastic approximation (SA)…
Two-Timescale Voltage Control in Distribution Grids Using Deep Reinforcement Learning
Qiuling Yang, Gang Wang, Alireza Sadeghi +2
Modern distribution grids are currently being challenged by frequent and sizable voltage fluctuations, due mainly to the increasing deployment of electric vehicles and renewable ge…