A5101541166- Smart Grid Security and Resilience
- Fault Detection and Control Systems
- Adaptive Control of Nonlinear Systems
- Network Security and Intrusion Detection
- Iterative Learning Control Systems
- Graphene research and applications
- Advanced Memory and Neural Computing
- Anomaly Detection Techniques and Applications
- Distributed Control Multi-Agent Systems
- Carbon Nanotubes in Composites
- Guidance and Control Systems
- Traffic Prediction and Management Techniques
- Advanced Computational Techniques and Applications
- Adaptive Dynamic Programming Control
- Aluminum Alloys Composites Properties
- Magnesium Alloys: Properties and Applications
- Metal and Thin Film Mechanics
- Adversarial Robustness in Machine Learning
- Prosthetics and Rehabilitation Robotics
- Energy and Environmental Systems
- Human Pose and Action Recognition
- Robotic Locomotion and Control
- Human Mobility and Location-Based Analysis
- Diabetic Foot Ulcer Assessment and Management
- Gait Recognition and Analysis
University of Electronic Science and Technology of China
2022-2024
Central South University
2023-2024
State Key Laboratory of Rare Earth Materials Chemistry and Application
2019-2023
Nanjing University of Posts and Telecommunications
2021-2023
Beijing National Laboratory for Molecular Sciences
2022-2023
Peking University
2019-2023
Shanghai Polytechnic University
2023
Shanghai Institute of Ceramics
2023
Chinese Academy of Sciences
2023
Liaoning University
2021
This article is concerned with bipartite tracking for a class of nonlinear multiagent systems under signed directed graph, where the followers are unknown virtual control gains. In predictor-based neural dynamic surface (NDSC) framework, strategy proposed by introduction predictors and minimal number learning parameters (MNLPs) technology along graph theory. Different from traditional NDSC, NDSC utilizes prediction errors to update network improving system transient performance. The MNLPs...
Catalyst design plays vital roles in structurally relevant reactions. Revealing the catalyst structure and chemistry reactive environment at atomic scale is imperative for rational of catalysts as well investigation reaction mechanisms, while situ characterization high temperature still a great challenge. Here, tracking intermetallic Co7W6 nanocrystals with defined melting point by environmental aberration-corrected transmission electron microscopy combination synchrotron X-ray absorption...
This article investigates the fault detection problem of unmanned marine vehicles (UMVs) under influence caused by replay attacks. First, dynamics UMV are modeled a Takagi--Sugeno (T--S) fuzzy system with an unknown membership function, which includes nonlinear coupling internal state system, environmental multisource disturbance as well potential thruster failure on UMV. Then, possible attack from sensor to shore-based center is considered, and switching-type tolerant filter designed....
For a class of nontriangular nonlinear systems in presence unknown disturbances, we propose predictor-based neural dynamic surface control (PNDSC) strategy this paper. This system is transformed via the mean value theorem, and predictor then constructed. To avoid an algebraic loop problem, partial state vectors are employed as input signals networks (NNs) for approximating dynamics, compensation items designed to compensate approximation errors from NNs. Different traditional NDSC, PNDSC...
Neural dynamic surface control (NDSC) is an effective technique for the tracking of nonlinear systems. The objective this article to improve closed-loop transient performance and reduce number learning parameters a strict-feedback system with unknown gains. For purpose, predictor-based NDSC (PNDSC) approach presented. It introduces Nussbaum functions predictors into traditional systems Unlike that uses errors update neural networks (NNs), PNDSC employs prediction same leading improved To...
An attitude control issue is concerned for a quadrotor with external disturbances in this paper. For unknown system dynamics, predictor-based neural networks (NNs) are introduced, where prediction errors, angular velocities, constructed, instead of tracking updating NNs' weights. This replacement reduces the occurrence high-frequency oscillations approximation. With improved NNs, predictorbased NN disturbance observer then developed compensation and approximation normalization learning...
Ni-rich materials (LiNixCoyMn1-x-yO2, x ≥ 0.6) are highly desirable for use in lithium-ion batteries (LIBs) due to their high energy density. However, voltage decay caused by heavy migration of transition metals (TMs), particularly Ni, remains a major issue. While Ni2+ is the dominant form Ni into Li layer, content Ni4+ and low during late stages de-lithiation leave underlying cause redox unclear. This knowledge gap hinders design better cathode material. To address this, we investigated...
Abstract After chirality‐specified growth of single‐walled carbon nanotubes (SWCNTs) was realized by tungsten‐based intermetallic compound catalysts, here we developed a different kind compound, cobalt disilicide (CoSi 2 ), as catalysts to selective grow chemical vapor deposition (CVD). By using methane source, obtained (11, 7) tubes with the selectivity ∼24% and semiconducting SWCNTs (s‐SWCNTs) purity ∼93% simultaneously. Because sensitivity CoSi toward oxygen‐containing environment at high...
In this paper, a novel secure fault-tolerant control strategy is proposed to deal with the impact of multiple threats such as sparse sensor attacks, system faults and unknown disturbances on T-S fuzzy cyber-physical systems (CPSs). Firstly, under assumption 2s-detectability, set robust local input observers are designed. Specifically, each observer can decouple partial perform targeted suppression undecoupling simultaneously. Next, residualbased attack detection global estimation fusion...
The interval observer, recognized as a potent tool for fault detection (FD), diverges from the adoption of fixed thresholds to enhance timeliness and precision detection. This study endeavors design an FD mechanism fuzzy cyber-physical systems (CPSs) subjected adversarial influences based on improved attack tolerant observer. Specifically, proposed frequency-information-based unknown input observer (UIIO) not only enables more precise estimation range under influence signals but also...
Silicon oxycarbide (SiOC), Ca- and Mg-modified silicon (SiCaOC SiMgOC) were synthesized via sol–gel processing with subsequent pyrolysis in an inert gas atmosphere. The physicochemical structures of the materials characterized by XRD, SEM, FTIR, 29Si MAS NMR. Biocompatibility vitro bioactivity detected MTT, cell adhesion assay, simulated body fluid (SBF) immersion test. Mg Ca successfully doped into network structure SiOC, non-bridging oxygens (NBO) formed. hydroxycarbonate apatite (HCA) was...
Large language models (LLMs) have made remarkable strides in complex reasoning tasks, but their safety and robustness processes remain underexplored. Existing attacks on LLM are constrained by specific settings or lack of imperceptibility, limiting feasibility generalizability. To address these challenges, we propose the Stepwise rEasoning Error Disruption (SEED) attack, which subtly injects errors into prior steps to mislead model producing incorrect subsequent final answers. Unlike...
Most current gait recognition methods suffer from poor interpretability and high computational cost. To improve interpretability, we investigate features in the embedding space based on Koopman operator theory. The transition matrix this captures complex kinematic of cycles, namely operator. diagonal elements can represent overall motion trend, providing a physically meaningful descriptor. reduce cost our algorithm, use reversible autoencoder to model size eliminate convolutional layers...