A5081612509- Neural Networks Stability and Synchronization
- Nonlinear Dynamics and Pattern Formation
- Stability and Control of Uncertain Systems
- Distributed Control Multi-Agent Systems
- Chaos control and synchronization
- Neural Networks and Applications
- stochastic dynamics and bifurcation
- Advanced Memory and Neural Computing
- Adaptive Control of Nonlinear Systems
- Quantum chaos and dynamical systems
- Fault Detection and Control Systems
- Stability and Controllability of Differential Equations
- Control Systems and Identification
- Matrix Theory and Algorithms
- Energy Efficient Wireless Sensor Networks
- Video Surveillance and Tracking Methods
- Smart Grid Security and Resilience
- Traffic Prediction and Management Techniques
- Image Enhancement Techniques
- Gene Regulatory Network Analysis
- Traffic control and management
- Transportation Planning and Optimization
- Privacy-Preserving Technologies in Data
- Machine Learning and ELM
- Machine Fault Diagnosis Techniques
Donghua University
2016-2025
Shanghai University of Engineering Science
2021
Shanghai Institute of Microsystem and Information Technology
2010-2011
Chinese Academy of Sciences
2010
Zhejiang Normal University
2004-2006
Zhejiang University of Technology
2004-2005
Zhejiang University
2004
The problem of delay-dependent robust H∞ control for uncertain singular systems with time delay has been investigated. considered are not assumed to be necessarily regular and impulse free. In terms linear matrix inequality approach, a stability criterion is given ensure the nominal system regular, impulse-free stable. Based on criterion, solved via state feedback controller, which guarantees that, all admissible uncertainties, closed-loop only stable, but also satisfies prescribed...
In this paper, the exponential stability in mean square for Markovian jumping systems (MJSs) is discussed. A new dynamic model, which involves parameters uncertainties, nonlinearities, and Lévy noises, proposed. Moreover, an adaptive sliding mode controller built to study of such a complex model. First, integral-type surface (SMS) established obtain motion dynamics MJSs. By generalized Itô formula Lyapunov theory, some sufficient conditions are obtained make sure dynamics. Second, control...
In this paper, the problem of adaptive synchronization is investigated for stochastic neural networks neutral-type with Markovian switching parameters. Using M-matrix approach and analysis method, some sufficient conditions are obtained to ensure three kinds networks. These include almost sure asymptotical synchronization, exponential in p th moment synchronization. Some numerical examples provided illustrate effectiveness potential proposed design techniques.
Abstract This paper presents an efficient inverse kinematics (IK) approach which features fast computing performance for a PUMA560-structured robot manipulator. By properties of the orthogonal matrix and block matrix, complex IK equations are transformed into eight pure algebraic that contain six unknown joint angle variables, makes solving compact without reverses 4×4 homogeneous transformation matrices. Moreover, appropriate combination related ensures solutions free extraneous roots in...
The fixed-time synchronization and energy consumption of Kuramoto-oscillator networks with multilayer distributed control are studied in this brief. In order to achieve synchronization, designed, including the proportional layer, finite-time layer layer. Then, overcome that cannot realize at desired time, sufficient conditions for proposed guarantee synchronization. To saving controller, supremum is obtained when reach Finally, an example given illustrate effectiveness consumption.
In this brief, the analysis problem of mode and delay-dependent adaptive exponential synchronization in th moment is considered for stochastic delayed neural networks with Markovian switching. By utilizing a new nonnegative function -matrix approach, several sufficient conditions to ensure are derived. Via feedback control techniques, some suitable parameters update laws found. To illustrate effectiveness -matrix-based derived numerical example provided finally.
This brief investigates the problem of global exponential stability analysis for discrete recurrent neural networks with time-varying delays. In terms linear matrix inequality (LMI) approach, a novel delay-dependent criterion is established considered via new Lyapunov function. The obtained condition has less conservativeness and number variables than existing ones. Numerical example given to demonstrate effectiveness proposed method.
Prescribed-time consensus tracking for second-order nonlinear multiagent systems (MASs) with the unknown dynamics satisfying a time-varying Lipschitz growth rate is investigated in this article. A function introduced as part of controller gains, and it plays an important role overcoming rapid terms ensuring that can be achieved preassigned time. An integral sliding-mode control protocol, which forces system trajectory to move on defined sliding manifold at initial moment, proposed solving...
In this article, the cluster synchronization problem for a class of nonlinearly coupled delayed neural networks (NNs) in both finite- and fixed-time cases are investigated. Based on Lyapunov stability theory pinning control strategy, some criteria provided to ensure NNs finite-and aspects. Then, settling time stabilization that is dependent initial value independent estimated, respectively. Finally, we illustrate feasibility practicality results via numerical example.