A5015351531- Distributed Control Multi-Agent Systems
- Adaptive Control of Nonlinear Systems
- Neural Networks Stability and Synchronization
- Stability and Control of Uncertain Systems
- Teleoperation and Haptic Systems
- Advanced Control Systems Optimization
- Nonlinear Dynamics and Pattern Formation
- Advanced Memory and Neural Computing
- Adaptive Dynamic Programming Control
- stochastic dynamics and bifurcation
- Iterative Learning Control Systems
- Mathematical and Theoretical Epidemiology and Ecology Models
- Machine Fault Diagnosis Techniques
- Underwater Vehicles and Communication Systems
- Complex Network Analysis Techniques
- Microgrid Control and Optimization
- Extremum Seeking Control Systems
- Smart Grid Security and Resilience
- Guidance and Control Systems
- Robotic Path Planning Algorithms
- Fault Detection and Control Systems
- Piezoelectric Actuators and Control
- Gene Regulatory Network Analysis
- Robotic Locomotion and Control
- Advanced Fiber Optic Sensors
China University of Geosciences
2017-2025
Academic Degrees & Graduate Education
2025
Central South University
2020-2023
Huazhong University of Science and Technology
2012-2022
Centre de Géosciences
2022
The diagnosis of the key components rotating machinery systems is essential for production efficiency and quality manufacturing processes. performance traditional method depends heavily on feature extraction, which relies degree individual's expertise or prior knowledge. Recently, a deep learning (DL) applied to automate extraction. However, training in DL requires massive amount sensor data, time consuming poses challenge its applications engineering. In this paper, new data-driven fault...
This paper proposes a unified framework to design sliding-mode control for stabilization of delayed memristive neural networks (DMNNs) with external disturbances. Under the presented framework, finite-time stabilization, and fixed-time controlled DMNNs can be, respectively, obtained by choosing different values specific parameter. It is proved that system responses be made reaching designed surface in finite fixed time, then stay on it. Moreover, it also illustrates inevitable disturbances...
In this paper, a unified framework is proposed to address the synchronization problem of memristor chaotic systems (MCSs) via sliding-mode control method. By employing presented framework, finite-time and fixed-time MCSs can be realized simultaneously. On one hand, based on Lyapunov stability theories, finite-/fixed-time results are obtained. It proved that trajectories error states come near get designed surface, stay it accordingly approach origin in finite/fixed time. other we develop an...
This paper proposes several hierarchical controller-estimator algorithms (HCEAs) to solve the coordination problem of networked Euler-Lagrange systems (NELSs) with sampled-data interactions and switching interaction topologies, where cases both discontinuous continuous signals are successfully addressed in a unified framework. The HCEAs comprise two main layers (i.e., control layer an estimator layer) one optional filter layer), which is tackled transient response can be optionally smoothed...
This paper investigates the bipartite tracking problem of networked robotic systems (NRSs) subject to input disturbances, discrete communications and signed directed graphs. Two new classes hierarchical hybrid control algorithms (HHCAs), which involve both continuous discontinuous signals in a uniform framework, are designed solve aforementioned model-independent manner, i.e., without using prior information system model. Besides, with help Lyapunov statement theory, we establish several...
This article investigates the predefined-time stabilization problems of Takagi–Sugeno (T–S) fuzzy systems. For addressing considered problems, a class novel integral sliding mode surface is first designed based on time-regulator function, which system states are forced to converge origin in predefined time after reached. Further, proposed employed construct controller for delayed and disturbed T–S system. The settling appears as sum two parameters design, which, respectively, adjusts...
Energy management in the smart home can help reduce residential energy costs by scheduling various consumption activities. However, accurately modeling factors, such as user behavior, renewable power generation, weather conditions, and real-time electricity prices be challenging, making design of an efficient strategy difficult. This article proposes a algorithm based on deep reinforcement learning (DRL) for homes equipped with rooftop photovoltaics, storage systems, appliances. The aims to...
In this article, the consensus of networked underactuated robotic systems subject to fixed and switched communication networks is discussed by developing some novel event-triggered control algorithms, which can synchronously guarantee convergence active states, boundedness velocities passive actuators, exclusion Zeno behaviors. cases networks, sufficient criteria are established for presented distributed mechanisms with without using neighbors' velocities, in order achieve a better tradeoff...