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- Keyword
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- Active damping; active disturbance rejection control (ADRC); grid-connected inverter; LCL filter; Pade approximation (1)
- Affine policy (1)
- Autoencoder; generalized correntropy; stacked extreme learning machine (SELM); wind speed forecasting (1)
- Cognitive radio networks (CRNs); orthogonal frequency division multiplexing (OFDM); resource allocation; Internet of Things (IoT); Jaya algorithm (1)
- Dispatchable renewables (1)
Articles 1 - 7 of 7
Full-Text Articles in Engineering
Intelligent Sensing And Decision Making In Smart Technologies, Wenbing Zhao, Jinsong Wu, Peng Shi, Hongqiao Wang
Intelligent Sensing And Decision Making In Smart Technologies, Wenbing Zhao, Jinsong Wu, Peng Shi, Hongqiao Wang
Electrical and Computer Engineering Faculty Publications
No abstract provided.
Resource Allocation In The Cognitive Radio Network-Aided Internet Of Things For The Cyber-Physical-Social System: An Efficient Jaya Algorithm, Xiong Luo, Zhijie He, Zhigang Zhao, Long Wang, Weiping Wang, Huansheng Ning, Jenq-Haur Wang, Wenbing Zhao, Jun Zhang
Resource Allocation In The Cognitive Radio Network-Aided Internet Of Things For The Cyber-Physical-Social System: An Efficient Jaya Algorithm, Xiong Luo, Zhijie He, Zhigang Zhao, Long Wang, Weiping Wang, Huansheng Ning, Jenq-Haur Wang, Wenbing Zhao, Jun Zhang
Electrical and Computer Engineering Faculty Publications
Currently, there is a growing demand for the use of communication network bandwidth for the Internet of Things (IoT) within the cyber-physical-social system (CPSS), while needing progressively more powerful technologies for using scarce spectrum resources. Then, cognitive radio networks (CRNs) as one of those important solutions mentioned above, are used to achieve IoT effectively. Generally, dynamic resource allocation plays a crucial role in the design of CRN-aided IoT systems. Aiming at this issue, orthogonal frequency division multiplexing (OFDM) has been identified as one of the successful technologies, which works with a multi-carrier parallel radio transmission strategy. In this article, through …
Short-Term Wind Speed Forecasting Via Stacked Extreme Learning Machine With Generalized Correntropy, Xiong Luo, Jiankun Sun, Long Wang, Weiping Wang, Wenbing Zhao, Jinsong Wu, Jenq-Haur Wang, Zijun Zhang
Short-Term Wind Speed Forecasting Via Stacked Extreme Learning Machine With Generalized Correntropy, Xiong Luo, Jiankun Sun, Long Wang, Weiping Wang, Wenbing Zhao, Jinsong Wu, Jenq-Haur Wang, Zijun Zhang
Electrical and Computer Engineering Faculty Publications
Recently, wind speed forecasting as an effective computing technique plays an important role in advancing industry informatics, while dealing with these issues of control and operation for renewable power systems. However, it is facing some increasing difficulties to handle the large-scale dataset generated in these forecasting applications, with the purpose of ensuring stable computing performance. In response to such limitation, this paper proposes a more practical approach through the combination of extreme-learning machine (ELM) method and deep-learning model. ELM is a novel computing paradigm that enables the neural network (NN) based learning to be achieved with fast training speed and …
Active Disturbance Rejection Control Of Lcl-Filtered Grid-Connected Inverter Using Pade Approximation, Abdeldjabar Benrabah, Dianguo Xu, Zhiqiang Gao
Active Disturbance Rejection Control Of Lcl-Filtered Grid-Connected Inverter Using Pade Approximation, Abdeldjabar Benrabah, Dianguo Xu, Zhiqiang Gao
Electrical and Computer Engineering Faculty Publications
In this paper, a simplified robust control is proposed to improve the performance of a three-phase current controlled voltage source inverter connected to the grid through an inductive-capacitive-inductive ( LCL) filter. The presence of the LCL-filter resonance complicates the dynamics of the control system and limits its overall performance, particularly when disturbances and parametric uncertainty are considered. To solve this problem, a robust active damping method based on the linear active disturbance rejection control (LADRC) is proposed. The simplification is made possible by order reduction in the plant transfer function using Padé approximation. Simulation results show that the proposed LADRC-based …
Finite-Time Anti-Synchronization Of Memristive Stochastic Bam Neural Networks With Probabilistic Time-Varying Delays, Manman Yuan, Weiping Wang, Xiong Luo, Linlin Liu, Wenbing Zhao
Finite-Time Anti-Synchronization Of Memristive Stochastic Bam Neural Networks With Probabilistic Time-Varying Delays, Manman Yuan, Weiping Wang, Xiong Luo, Linlin Liu, Wenbing Zhao
Electrical and Computer Engineering Faculty Publications
This paper investigates the drive-response finite-time anti-synchronization for memristive bidirectional associative memory neural networks (MBAMNNs). Firstly, a class of MBAMNNs with mixed probabilistic time-varying delays and stochastic perturbations is first formulated and analyzed in this paper. Secondly, an nonlinear control law is constructed and utilized to guarantee drive-response finite-time anti-synchronization of the neural networks. Thirdly, by employing some inequality technique and constructing an appropriate Lyapunov function, some anti-synchronization criteria are derived. Finally, a number simulation is provided to demonstrate the effectiveness of the proposed mechanism.
Surrogate Affine Approximation Based Co-Optimization Of Transactive Flexibility, Uncertainty, And Energy, Hongzing Ye
Surrogate Affine Approximation Based Co-Optimization Of Transactive Flexibility, Uncertainty, And Energy, Hongzing Ye
Electrical and Computer Engineering Faculty Publications
This study presents an approach to co-optimization of transactive flexibility, energy, and optimal injection-range of Variable Energy Resource (VER). Flexibility receives immense attention, as it is the essential resource to accommodate VERs in modern power systems. With a novel concept of transactive flexibility, the proposed approach proactively positions the flexible resources and optimizes the demand of flexibility. A surrogate affine approximation (SAA) method is proposed to solve the problem with variable infinite-constraint range in polynomial time. It is shown that SAA is more optimistic than the traditional affine policy in the power literature. The SAA method is also applicable to …
Correction To: Dependability Enhancing Mechanisms For Integrated Clinical Environments (Vol 73, Pg 4207, 2017), Wenbing Zhao, Mary Q. Yang
Correction To: Dependability Enhancing Mechanisms For Integrated Clinical Environments (Vol 73, Pg 4207, 2017), Wenbing Zhao, Mary Q. Yang
Electrical and Computer Engineering Faculty Publications
No abstract provided.