A5029897785- Chaos control and synchronization
- Solar Radiation and Photovoltaics
- Neural Networks Stability and Synchronization
- Photovoltaic System Optimization Techniques
- Energy Load and Power Forecasting
- Neural Networks and Applications
- Advanced Combustion Engine Technologies
- Electrohydrodynamics and Fluid Dynamics
- Advanced Algorithms and Applications
- Vehicle Dynamics and Control Systems
- Simulation and Modeling Applications
- Power Systems and Renewable Energy
- Combustion and flame dynamics
China Three Gorges University
2021-2023
Hebei University of Science and Technology
2010
Shijiazhuang Tiedao University
2010
There are some problems in the photovoltaic microgrid system due to solar irradiance-change environment, such as power fluctuation, which leads larger imbalance and affects stable operation of microgrid. Aiming at mismatch loss under partial shading systems, this paper proposed a distributed maximum point tracking (DMPPT) approach based on an improved sparrow search algorithm (ISSA). First, used center gravity reverse learning mechanism initialize population, so that population has better...
Aiming at the problem of high fluctuation and instability photovoltaic power, a power prediction method combining two techniques has been proposed in this study. In method, fast correlation filtering algorithm used to extract meteorological features having strong with generation. The complete ensemble empirical mode decomposition an adaptive noise model decompose data into low-frequency components reduce volatility. Then, long short-term neural network deep confidence were combined new...
A sliding mode synchronization controller by neural network is presented for two chaotic systems. The compound disturbance of the error system consists nonlinear uncertainties and exterior disturbances Based on networks, a observer proposed update law parameters given to monitor disturbance. based output observer. designed can make convergent zero overcome disruption uncertainty system. Finally, an example demonstrate availability control method.
Online identification of nonlinear systems is still an important while difficult task in practice. A general and simple online method, by delayed cellular neural networks, proposed for multi-input-multi-output (MIMO) systems. The framework first formulated the weights network are updated error adaptive method. Based on Lyapunov stability theory, resulting closed-loop system uniform ultimate bounded stable. Then, indirect controller designed based networks.