A5102952807- Distributed Control Multi-Agent Systems
- Magnetic Properties and Applications
- Neural Networks Stability and Synchronization
- UAV Applications and Optimization
- Non-Destructive Testing Techniques
- Traffic control and management
- Stochastic Gradient Optimization Techniques
- Energy Harvesting in Wireless Networks
- Autonomous Vehicle Technology and Safety
- Internet Traffic Analysis and Secure E-voting
- Control Systems and Identification
- Vehicular Ad Hoc Networks (VANETs)
- Viral Infections and Outbreaks Research
- Power Systems Fault Detection
- Advanced Control Systems Optimization
- Control and Dynamics of Mobile Robots
- Cooperative Communication and Network Coding
- Robotic Path Planning Algorithms
- Composite Material Mechanics
- Metaheuristic Optimization Algorithms Research
- Adaptive Control of Nonlinear Systems
- Privacy-Preserving Technologies in Data
- Mechanical Behavior of Composites
- COVID-19 Pandemic Impacts
- COVID-19 epidemiological studies
Georgia Institute of Technology
2000-2025
Shandong University
2018-2019
Abstract Infectious disease outbreaks with pandemic potential present challenges for mitigation and control. Policymakers make decisions to reduce disease-associated morbidity mortality while also minimizing socioeconomic costs of Despite ongoing efforts widespread recognition the challenge, there remains a paucity decision tool frameworks that integrate epidemic macroeconomic dynamics. Here, we propose analyze an econo-epidemic model identify robust planning policies limit impacts...
This letter proposes a distributed consensus controller for class of heterogeneous nonlinear multi-agent systems. The control law enacted at each agent is based on predicted outputs itself and its neighboring agents. It implements fluid-flow version the Newton-Raphson method solving equations, this, together with way predictions are used, guarantees asymptotic general systems defined by ordinary differential equations. scope analysis includes whose agent-subsystems have different state-space...
Abstract As a necessary electrical equipment for the construction of power grid, safety and reliability transformer is focus that people have always paid attention to. In recent years, DC bias has serious impact on safe operation system, which attracted wide scholars at home abroad. view this phenomenon, combined with basic principle excitation, simulation phenomenon carried out by using Simulink software in paper. According to results, distortion characteristics excitation current under are...
Recurrent neural networks (RNNs) have many advantages over more traditional system identification techniques. They may be applied to linear and nonlinear systems, they require fewer modeling assumptions. However, these network models also need larger amounts of data learn generalize. Furthermore, training is a time-consuming process. Hence, building upon long-short term memory (LSTM), this paper proposes using two types deep transfer learning, namely parameter fine-tuning freezing, reduce...
This paper investigates an application of feedforward neural networks (FNN) to a tracking-control technique in order render it model-free. The controller, proposed elsewhere by author this paper, is based on the Newton-Raphson fluid-flow dynamics for matching system's predicted output target-reference signal. Most extant results require that predictor be knowledge input-output model. In overcome limitation, we construct using FNN slated provide adequate approximations future outputs. We test...
In recent years, Unmanned Aerial Vehicles (UAVs) have been used in fields such as architecture, business delivery, military and civilian theaters, many others. With increased applications comes the demand for advanced algorithms resource allocation energy management. As is well known, game theory machine learning are two powerful tools already widely wireless communication field there numerous surveys of usage communication. Existing however focus either on or due to this fact, current...
In this article, we propose a joint access selection and bandwidth allocation method for UAV-assisted wireless communication networks. We consider an application scenario where UAVs act as flying base stations to provide services ground mobile devices. The interactions among devices are modeled Stackelberg game, the leaders followers. is noncooperative of based on evolutionary game theory. explore distributed synchronous update asynchronous update's influence convergence results. addition,...
This paper proposes a consensus controller for multi-agent systems that can guarantee the agents' safety. The controller, built with idea of output prediction and Newton-Raphson method, achieves class heterogeneous nonlinear systems. Integral Control Barrier Function is applied in conjunction such states are confined within pre-defined safety sets. Due to dynamically-defined control input, resulting optimization problem from barrier function always Quadratic Program, despite nonlinearities...
Distributed optimization plays an important role in solving engineering problems. Contrary to centralized optimization, it seeks find global optima a distributed manner, where agents within group share information only with their neighbors. Optimizing cost function without constraints or separable has already been addressed, however, appears be difficult optimal solution when both cross-terms and linear exist. To solve this problem, we propose algorithm based on alternating direction method...
Federated Learning is an algorithm suited for training models on decentralized data, but the requirement of a central "server" node bottleneck. In this document, we first introduce notion Decentralized (DFL). We then perform various experiments different setups, such as changing model aggregation frequency, switching from independent and identically distributed (IID) dataset partitioning to non-IID with partial global sharing, using optimization methods across clients, breaking into segments...