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Articles 1 - 12 of 12
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.
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 …
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 …
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.
Human Activity Tracking And Recognition Using Kinect Sensor, Roanna Lun
Human Activity Tracking And Recognition Using Kinect Sensor, Roanna Lun
ETD Archive
The objective of this dissertation research is to use Kinect sensor, a motion sensing input device, to develop an integrated software system that can be used for tracking non-compliant activity postures of consented health-care workers for assisting the workers' compliance to best practices, allowing individualized gestures for privacy-aware user registration, movement recognition using rule-based algorithm, real-time feedback, and exercises data collection. The research work also includes developing a graphical user interface and data visualization program for illustrating statistical information for administrator, as well as utilizing cloud based database system used for data resource.
A Transformative Process Control Solution, Simone Castanho Nobrega De Almedia Soares
A Transformative Process Control Solution, Simone Castanho Nobrega De Almedia Soares
ETD Archive
Knowing that a technology invented almost hundred years ago (PID controller) is still dominating industrial process control, a historical review was done to understand how the control field evolved. Model dependency and high level of mathematics appear as the main reasons that prevent other technologies from penetrating the engineering practice. A relatively novel methodology introduced by J. Han in 1998 called Active Disturbance Rejection Control (ADRC) came with characteristics that matches process control needs and restrictions on model dependency. This study will present a transformative solution for process control based on that. The control algorithm is designed and discretized for …
School Logo Cleveland State University Logo Title Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
School Logo Cleveland State University Logo Title Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
ETD Archive
We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to …
Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
Evolutionary Optimization For Safe Navigation Of An Autonomous Robot In Cluttered Dynamic Unknown Environments, Arash Roshanineshat
ETD Archive
We present a path planning approach based on probabilistic methods for a robot to navigate in a cluttered, dynamic, unknown environment. There are dynamic obstacles moving around and static obstacles located in the map. The robot does not have any prior information about them but should be able to navigate through the map beginning from a known starting point and safely ending at a known target point. The only information the robot has is the location of the starting point and the target point and it uses sensory information to collect information about its surroundings. Our method is compared to …
Virtual Reality Based Serious Games For Stna Training, Ryan Thomas Kall
Virtual Reality Based Serious Games For Stna Training, Ryan Thomas Kall
Undergraduate Research Posters 2018
In this project, exploratory steps have been taken towards the development of a set of serious games for state tested nursing assistants (STNAs) education and training, which promises to make the training more engaging and effective. Tasks include getting familiar with developing 3D scenes with Unity, human activity recognition with Microsoft Kinect, creating holograms with Microsoft HoloLens, and help implement a gaze-based mechanism for performance assessment in patient transfer skills.