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IAENG International Journal of Computer Science 2022年第3期49卷 666页

作者： Chen, Gonggui Wang, Shumin He, Yongsheng Shang, Wanfeng Long, Hongyu Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing University of Posts and Telecommunications Chongqing400065 China State Grid Chongqing Electric Power Company Chongqing400015 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Shenzhen518055 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

The short-term hydrothermal scheduling (STHS) is a complex non-linear, non-convex and high-dimensional mathematical optimization problem. Due to the fact that the original chimp optimization algorithm (ChOA) is likely to fall into local optimum and has the disadvantage of low population diversity, an improved chimp optimization algorithm (IChOA) is proposed to solve the STHS problem. Firstly, Logistic-Tent chaotic mapping is employed to initialize the population and increase the population diversity. Then a new nonlinear convergence factor is introduced to make the optimization search process more applicable to STHS problems. Next, particle swarm algorithm (PSO) and gravitational search algorithm (GSA) are combined to enhance the shortcoming and balance the global search ability and local exploration ability of ChOA. Moreover, Cauchy mutation and opposition-based learning strategy are supplemented as perturbation interference when the optimal position is not updated to improve the ability to leap out of the local optimum. Finally, a graded optimization strategy is adopted for the constraint handing of dynamic reservoir balance and thermal power balance. Three standard hydrothermal power systems are utilized to verify the practicability and validity of the proposed method. Results of simulations reveal that IChOA has significant competitive advantages in addressing the STHS problem. © 2022, IAENG International Journal of Computer Science. All Rights Reserved.

关键词： Particle swarm optimization (PSO)

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Adversarial Learning Network for Recovering Rppg Signals from Low-Resolution Images for Remote Heart Rate Measurement

SSRN

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SSRN 2024年

作者： Zhai, Dezhao Chen, Wei Li, Qinwei Yu, Ming Wu, Hang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Systems Engineering Institute Academy of Military Sciences People's Liberation Army Tianjin300161 China Tianjin Key Laboratory for Advanced Signal Processing Civil Aviation University of China Tianjin300300 China School of Artificial Intelligence Nankai University Tianjin300381 China

Remote Photoplethysmography (rPPG) is a non-contact method for measuring heart rate (HR) through facial video, which has significant research value and application potential. However, in long-distance vital sign measurement tasks, the low resolution of facial images and insufficient pixels in the facial region severely degrade the quality of the rPPG signals, leading to a sharp decline in HR accuracy. To address this issue, this paper proposes an adversarial learning network for recovering rPPG signals from low-resolution images (ALRSL-HR). First, arbitrary resolution face images are fed into multi-channel network to extract rPPG signal features capturing rich rPPG information, generating rPPG feature blocks, and temporally aggregating for richer feature representation. These features are then inputted into the backbone network to generate adversarial examples of rPPG signals of varying qualities. Finally, a two-stage adversarial loss function is employed to enable the low-quality rPPG signals to learn the periodic characteristics of high-quality rPPG signals, recover the low-quality signals, and narrow the quality gap between rPPG signals from low-resolution images. Extensive experiments were conducted in this paper to validate the effectiveness of our model on the public COHFACE, UBFC-Phys and UBFC-rPPG datasets. The results of the experiments demonstrate that the proposed ALRSL-HR model can effectively recover degraded rPPG signals from low-resolution images. © 2024, The Authors. All rights reserved.

关键词： Photoplethysmography

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Sound Field control by Using Equivalent Input Disturbance method

Sound Field Control by Using Equivalent Input Disturbance me...

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Industrial Cyber-Physical systems (ICPS)

作者： Toshiki Watanabe Jinhua She Zewen Wang Department of Sustainable Engineering Tokyo university of technology Japan School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Laboratory for Future Interdisciplinary Research of Science and Technology (FIRST) Tokyo Institute of Technology Yokohama Kanagawa Japan

Low-frequency noise, such as road noise from automobiles and interior noise from bullet train cars, is detrimental to passenger comfort. Active noise control provides us with a way of suppressing low-frequency noise. It generates a sound of the same amplitude and opposite phase as noise and uses it to cancel the noise. Conventional active noise control is complicated to apply. Thus, the objective of this study is to establish a sound field control system by using the equivalent-input-disturbance method. System identification was performed to obtain an ideal plant of a duct. The control system is constructed based on the equivalent-input-disturbance approach with a low-order controller. The experimental results showed a suppression effect of about 50% of the sound field.

关键词： Roads Noise reduction Ducts Channel estimation Auditory system Cyber-physical systems control systems

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A Reinforcement-Learning-Based Evolutionary Algorithm Using Solution Space Clustering For Multimodal Optimization Problems

A Reinforcement-Learning-Based Evolutionary Algorithm Using ...

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Congress on Evolutionary Computation

作者： Hai Xia Changhe Li Sanyou Zeng Qingshan Tan Junchen Wang Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

In evolutionary algorithms, how to effectively select interactive solutions for generating offspring is a challenging problem. Though many operators are proposed, most of them select interactive solutions (parents) randomly, having no specificity for the features of landscapes in various problems. To address this issue, this paper proposes a reinforcement-learning-based evolutionary algorithm to select solutions within the approximated basin of attraction. In the algorithm, the solution space is partitioned by the k-dimensional tree, and features of subspaces are approximated with respect to two aspects: objective values and uncertainties. Accordingly, two reinforcement learning (RL) systems are constructed to determine where to search: the objective-based RL exploits basins of attraction (clustered subspaces) and the uncertainty-based RL explores subspaces that have been searched comparatively less. Experiments are conducted on widely used benchmark functions, demonstrating that the algorithm outperforms three other popular multimodal optimization algorithms.

关键词： Uncertainty Clustering algorithms Evolutionary computation Reinforcement learning Benchmark testing Search problems Feature extraction

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A Novel Scalable Framework For Constructing Dynamic Multi-objective Optimization Problems

A Novel Scalable Framework For Constructing Dynamic Multi-ob...

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Congress on Evolutionary Computation

作者： Qingshan Tan Changhe Li Hai Xia Sanyou Zeng Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

Modeling dynamic multi-objective optimization problems (DMOPs) has been one of the most challenging tasks in the field of dynamic evolutionary optimization. Based on the analysis of the existing DMOPs, several features widely existed in real-world applications are not taken into account: different objectives may have different function models and variables to be optimized; and the number of conflicting variables should be independent from the number of objectives; the time-linkage property is not considered. In order to overcome the above issues, a novel framework for constructing DMOPs is proposed, where all objectives can be designed independently, and the number of the conflicting variables can be tuned by users. Moreover, it is easy to add new dynamic features to this framework. Several classical dynamic multi-objective optimization algorithms are tested on four scenarios, results show that these characteristics are challenging for the existing algorithms.

关键词： Schedules Analytical models Heuristic algorithms Object oriented modeling Evolutionary computation Benchmark testing Dynamic scheduling

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A registration-aided domain adaptation network for 3D Point cloud based place recognition

arXiv

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arXiv 2020年

作者： Qiao, Zhijian Hu, Hanjiang Shi, Weiang Chen, Siyuan Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Mechanical Engineering Carnegie Mellon University United States Department of Computer Science and Technology University of Cambridge United Kingdom

In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance. However, it is time-consuming and effort-costly to obtain high-quality point cloud data for place recognition model training and ground truth for registration in the real world. To this end, a novel registration-aided 3D domain adaptation network for point cloud based place recognition is proposed. A structure-aware registration network is introduced to help to learn features with geometric information and a 6-DoFs pose between two point clouds with partial overlap can be estimated. The model is trained through a synthetic virtual LiDAR dataset through GTA-V with diverse weather and daytime conditions and domain adaptation is implemented to the real-world domain by aligning the global features. Our results outperform state-of-the-art 3D place recognition baselines or achieve comparable on the real-world Oxford RobotCar dataset with the visualization of registration on the virtual dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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Dynamic power systems line outage detection using particle filter and partially observed states

arXiv

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arXiv 2021年

作者： Yang, Xiaozhou Chen, Nan Zhai, Chao The Department of Industrial Systems Engineering and Management National University of Singapore Singapore117576 Singapore ETH Zurich Future Resilient Systems Singapore-ETH Centre 1 CREATE Way CREATE Tower Singapore138602 Singapore The School of Automation China University of Geosciences Wuhan430074 China The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Real-time transmission line outage detection is difficult because of partial phasor measurement unit (PMU) deployment and varying outage signal strength. Existing detection approaches focus on monitoring PMU-measured nodal algebraic states, i.e., voltage phase angle and magnitude. The success of such approaches, however, is largely predicated on strong outage signals and the presence of PMUs in the outage location's vicinity. To overcome these limitations, a unified framework is proposed in this work by utilizing both nodal voltage information and generator dynamic states, e.g., rotor angular position. The proposed scheme is shown to be faster and more robust to unknown outage locations through the incorporation of generator dynamics. Using the IEEE 39-bus system simulation data, the proposed scheme's properties and performances compared to existing approaches are presented. The new approach could help improve operators' real-time situational awareness by detecting outages faster and providing a breakdown of outage signals for diagnostic purposes, making future power systems more resilient. Copyright © 2021, The Authors. All rights reserved.

关键词： Monte Carlo methods

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A Model-Predictive-Enabled Equivalent-Input-Disturbance Approach for Disturbance Rejection

A Model-Predictive-Enabled Equivalent-Input-Disturbance Appr...

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Industrial Cyber-Physical systems (ICPS)

作者： Yujian Zhou Jinhua She Feng Wang Makoto Iwasaki School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Tokyo Japan Department of Electrical and Mechanical Engineering Nagoya Institute of Technology Nagoya Japan

This paper presents a model-predictive-enabled equivalent-input-disturbance (MPEID) method for disturbance rejection. An EID estimator with a state observer estimates the effect of disturbances in a system. The disturbance estimation will not be directly added to the input channel for disturbance rejection. A cost function that considers the disturbance estimation is designed. An MPC controller calculates an optimal control input by minimizing the cost function. The stability condition of the closed-loop system is analyzed based on the Lyapunov stability theory. Simulation results show that our method has better disturbance-rejection performance than an MPC method when the control input is similar.

关键词： Simulation Estimation Optimal control Predictive models Observers Cyber-physical systems Cost function

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A historical review and bibliometric analysis of research on weak measurement research over the past decades based on biblioshiny

arXiv

引用

arXiv 2021年

作者： Huang, Jing-Hui Duan, Xue-Ying He, Fei-Fan Wang, Guang-Jun Hu, Xiang-Yun School of Institute of Geophysics and Geomatics China University of Geosciences Lumo Road 388 Wuhan430074 China School of Automation China University of Geosciences Lumo Road 388 Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

Weak measurement has enabled fundamental studies in both experiment and theory of quantum measurement. Numerous researches have indicated that weak measurements have a wide range of application and scientific research value. In our work, we used bibliometric methods to evaluate the global scientific output of research on Weak measurement and explore the current status and trends in this field from 2000 to 2020. The R bibliometric package was used for quantitative and qualitative analyses of publication outputs and author contributions. In total, 636 related articles and reviews were included in the final analysis. The main results were as follows: The number of publications has increased substantially with time. Physical Review A was the most active journal. The country and institution contributing the most to this field were The United States and University Rochester respectively. The analysis of the conceptual structure of keywords indicated that weak measurements were involved a variety of metrology, quantum communication, and nonclassical features of quantum mechanics. Our bibliometric analysis shows that weak measurement research continues to be a hot-spot. The focus has evolved to study quantum information and amplify weak signals. © 2021, CC BY.

关键词： Quantum optics

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Improving the precision of weak-value-amplification with two cascaded Michelson interferometers based on Vernier-effect

arXiv

引用

arXiv 2021年

作者： Huang, Jing-Hui He, Fei-Fan Duan, Xue-Ying Wang, Guang-Jun Hu, Xiang-Yun School of Institute of Geophysics and Geomatics China University of Geosciences Lumo Road 388 Wuhan430074 China School of Automation China University of Geosciences Lumo Road 388 Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

A modified-weak-value-amplification(MWVA) technique of measuring the mirror's velocity based on the Vernier-effect has been proposed. We have demonstrated with sensitivity-enhanced and the higher signal-to-noise ratio(SNR) by using two cascaded Michelson interferometers. These two interferometers are composed of similar optical structures. One interferometer with a fixed mirror acts as a fixed part of the Vernier-scale, while the other with a moving mirror acts as a sliding part of the Vernier-scale for velocity sensing. The envelope of the cascaded interferometers shifts much more than a single one with a certain enhancement factor, which is related to the free space range difference between these two interferometers. In addition, we calculate the SNR based on the Fisher information with both the MWVA technique and the traditional-weak-value-amplification(TMVA) technique. The results show that the SNR with our MWVA technique is larger than the the SNR with the TWVA technique within the range of our time measurement window. Our numerical analysis proved that our MWVA technique is more efficient than the TWVA technique. And by using the principles of the Vernier-effect, it is applicative and convenient to ulteriorly improving the sensitivity and SNR in measuring other quantities with the MWVA technique. © 2021, CC BY.

关键词： Signal to noise ratio

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