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2019 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Junnan Chen Xiaoming Liu Shengnan Dong Pengyun Li Xiaoqing Tang Dan Liu Masaru Kojima Qiang Huang Tatsuo Arai Intelligent Robotics Institute School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing CHINA Department of Systems Innovation Graduate school of Engineering Science Osaka University Toyonaka Osaka Japan Global Alliance Lab The University of Electro-Communications Tokyo Japan

We have successfully achieved manipulation and assembly of microbeads having the size of 100μm diameter by hemispherical end-effectors with high stability and accuracy. The motivation of achieving assembly of actual cells lies in the great significance of it in tissue regeneration and cell analysis. Firstly, the most difficult problem we need to solve is the releasing problem caused by adhesion force. The viscosity on cell surface is much larger than the microbeads which makes cell releasing challenging. Secondly, the cell can generate its deformation, then contact area with end-effector will change during grasping process. This may influence the adhesion force and also bring problem to releasing. Thirdly, cell is much smaller, around 15μm in diameter, so we need to fabricate smaller end-effector to achieve successful manipulation and ensure the stability in the meantime. In this paper, we realize the manipulation by decreasing the adhesion forces and apply vibration to release a cell stably. We found the appropriate scale size for the end-effector is around 10μm diameter. It can not only grasp a 15μm cell but also bring little interference to the environment. As a demonstration of the proposed manipulation method, the repeated experiments were conducted to explore the dependence of adhesion force on the grasping distance, which can be helpful in the improvement of successful rate. Finally, we achieved automatic cell assembly using Hela cells.

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An Economic Scheduling Strategy of Photovoltaic Storage Micro-grid Considering Demand Response

An Economic Scheduling Strategy of Photovoltaic Storage Micr...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Rundong Liu Sen Zhang Yincheng Zhao Haojie Ma Luan Chen Weihao Hu Ming Tang Wei Zhan Qingjia Zhou Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China SPIC Sichuan Electric Power Co. LTD Chengdu China SPIC Southwest Energy Research Institute Chengdu China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

To realize the economic optimization dispatch of PSMG (Photovoltaic Storage Micro-grid), considering the stochastic influence of multiple uncertainties, this study formulates a day-ahead optimal dispatching strategy of PSMG with the minimum comprehensive operating cost as the objective function. Firstly, the source-load uncertainty is dealt with by scenario generation using the Monte Carlo method and k-means clustering algorithm. Then the peak shaving ability of the system is enhanced by the introduction of flexible loads, and the scheduling flexibility of the photovoltaic storage system is increased by the integrated demand response increases the scheduling flexibility of the photovoltaic storage system. Finally, simulation results show that the scheduling scheme can prompt the source-load to participate in peak shaving and valley filling at the same time, increase the new energy consumption capacity of the photovoltaic storage micro-grid, and effectively improve the economic and social benefits of the micro-grid.

关键词： Photovoltaic systems Uncertainty Fluctuations Costs Monte Carlo methods Simulation Demand response

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On the Gaussian Filtering for Nonlinear Dynamic systems Using Variational Inference

On the Gaussian Filtering for Nonlinear Dynamic Systems Usin...

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International Conference on Information Fusion

作者： Yi Liu Xi Li Le Yang Lyudmila Mihaylova Ji Li Department of Electrical and Computer Engineering University of Canterbury Christchurch NZ State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems National University of Defense Technology Changsha China Department of Automatic Control and System Engineering University of Sheffield Sheffield UK Locaris Electronic Technology Co. Ltd Zhengzhou China

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

This paper introduces a new variational Gaussian filtering approach for estimating the state of a nonlinear dynamic system. We first assume that the predictive distribution of the state is Gaussian and derive an iterative method for updating the state posterior in the natural parameter space through KullbackLeibler divergence minimization. The obtained update rule is the same as that of the conjugate-computation variational inference technique in Bayesian learning. The derivation here is simpler and more insightful. We then impose a Wishart prior on the inverse of the state prediction covariance to take into account the impact of approximating the state predictive distribution using a Gaussian density on the state posterior estimation. The prediction covariance is identified jointly with the state using variational inference and the established state posterior update rule to achieve the desired Gaussian filtering. Simulation study examines the performance of the proposed filtering framework in target tracking based on bearing and range measurements.

关键词： Target tracking Smoothing methods Filtering Estimation Filtering algorithms Prediction algorithms Minimization Nonlinear dynamical systems Bayes methods Iterative methods

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A Many-Objective Evolutionary Algorithm Assisted by Ideal Hyperplane

SSRN

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SSRN 2022年

作者： Zhang, Zhixia Wen, Jie Wang, Hui Cai, Xingjuan Cui, Zhihua Zhang, Wensheng School of Computer Science and Technology Taiyuan University of Science and Technology China School of Information Engineering Nanchang Institute of Technology Nanchang330099 China State Key Laboratory of Intelligent Control and Management of Complex System Institute of Automation Chinese Academy of Sciences China State Key Lab. for Novel Software Technology Nanjing University China

In many-objective optimization problems (MaOPs), it is a difficult task for evolutionary algorithms to balance convergence and diversity while rapidly converging to the Pareto front. As the number of objectives increases, the difficulty of evolutionary algorithms increases with individual selection pressure. To address above problems, we propose a many-objective evolution algorithm assisted by an ideal hyperplane (MaOEA-IH). Firstly, the ideal hyperplane as a reference surface to guide the individual to search the Pareto front, which is established from the extremum of each dimension of the objective space. Secondly, a parallel p -norm mating selection strategy is proposed to improve convergence. In addition, two factors are considered in this strategy: 1) different p -norm are used to measure different spatial scales;2) individual selection uncertainty is defined by incorporating a probabilistic perturbation mechanism. Thirdly, the improved shift-based density estimation strategy is used as the evaluation criterion for environmental selection to improve the convergence and diversity of solution sets and enhance selection pressure. To verify the effectiveness of the proposed algorithm, MAOEA-IH is compared with seven excellent algorithms in three benchmark sets (DTLZ, WFG and MaF). The results show that the proposed MAOEA-IH is highly competitive in solving MaOPs. © 2022, The Authors. All rights reserved.

关键词： Geometry

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Adaptation Via Proxy: Building Instance-Aware Proxy for Unsupervised Domain Adaptive 3d Object Detection

SSRN

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SSRN 2023年

作者： Li, Ziyu Yao, Yuncong Quan, Zhibin Qi, Lei Feng, Zhenhua Yang, Wankou School of Automation Southeast University Nanjing210096 China Key Lab of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China School of Computer Science and Engineering Southeast University Nanjing210096 China Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom

LiDAR-based 3D detectors perform well on particular autonomous driving benchmarks, but may poorly generalize to other domains. Existing 3D domain adaptive detection methods usually require annotation-related statistics or continuous refinement of pseudo-labels. The former is not always feasible for practical applications, while the latter lacks sufficient accurate supervision. In this work, we propose a novel unsupervised domain adaptive framework, namely Adaptation Via Proxy (AVP), that explicitly leverages cross-domain relationships to generate adequate high-quality samples without any target statistics, thus mitigating domain shifts for existing LiDAR-based 3D detectors. Specifically, we first train the detector on the source domain with curriculum example mining to enhance its generalization capability. Then, we fine-tune the pre-trained detector on the instance-aware proxy that is a data collection with stronger supervision. The instance-aware proxy utilizes the profitable instances from the source domain to provide more robust supervision for optimizing the detector to overcome domain gaps. Note that AVP is architecture-agnostic thus it can be easily injected with any LiDAR-based 3D detectors. Extensive experiments on Waymo, nuScenes, KITTI and Lyft demonstrate the superiority of the proposed method over the state-of-the-art approaches for different adaptation scenarios. © 2023, The Authors. All rights reserved.

关键词： Object detection

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Study on the method of restraining the ending effect of empirical mode decomposition (EMD)

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Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology 2006年第3期26卷 196-200页

作者： Xu, Bao-Jie Zhang, Jian-Min Xu, Xiaoli Li, Jian-Wei School of Mechanical and Vehicular Engineering Beijing Institute of Technology Beijing 100081 China Measurement and Control of Mechanical and Electrical System Key Lab. of Beijing Beijing Institute of Machinery Beijing 100085 China

Ending effect is produced in the decomposition process of empirical mode decomposition (EMD) based Hilbert-Huang transformation. It leads to distortion near the two end points of the signal processed. Several methods of restraint aimed at ending effect are proposed. Comparison has been made among the global average statistic method, the parallel line extending method, the polynomial curvefitting method, the mirror extending method and the neural networks extending method. As a result of simulation and experiment, it is shown that ending effect can be effectively restrained.

关键词： Signal theory

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A Fair and Effective Approach to Managing Distributed Energy Resources Through Peer-to-Peer Energy Trading with Load Prioritization Among Smart Homes

SSRN

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SSRN 2023年

作者： Ahmed, Syed Adrees Huang, Qi Amin, Waqas Afzal, Muhammad Hussain, Fazal Haider, Muhammad Husnain 1Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan China Chengdu University of Technology China National University of Sciences and Technology Pakistan Superior University Pakistan School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan China

This paper proposes a novel approach to managing distributed energy resources (DERs) through peer-to-peer (P2P) energy trading among smart homes, incentivizing peers to trade surplus energy to maximize social welfare. The proposed day-ahead demand-side management (DSM) technique considers load prioritization based on users' needs. It utilizes an energy allocation method that incentivizes peers to buy energy at a reduced price and sell energy at a higher price. This method maximizes the time of energy traded to higher-priority loads, followed by lower-priority loads while considering user choice. The proposed method results in an average reduction in energy costs from 14.8% to 2.82% for all consumers and an average increase in revenues from 17.35% to 9.07% for all prosumers compared to the grid and previously proposed studies. The simulation results show significant economic benefits for all market participants, improved community self-sufficiency, and reduced dependence on the main grid. The proposed methodology provides an effective and fair solution for managing DERs through P2P energy trading by prioritizing the load in smart homes, which describes its potential to create a sustainable and efficient energy ecosystem. © 2023, The Authors. All rights reserved.

关键词： Automation

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Nonlinear Virtual Inertia control of WTGs for Enhancing Primary Frequency Response and Suppressing Drive-Train Torsional Oscillations

arXiv

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arXiv 2020年

作者： Liu, Bi Huang, Qi Zhao, Junbo Milano, Federico Zhang, Yingchen Sichuan Provincial Key Lab of Power System Wide-area Measurement and Control University of Electronic Science and Technology of China Chengdu Sichuan611731 China Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States School of Electrical and Electronic Engineering University College Dublin Dublin Ireland National Renewable Energy Laboratory GoldenCO80401 United States

Virtual inertia controllers (VICs) for wind turbine generators (WTGs) have been recently developed to compensate the reduction of inertia in power systems. However, VICs can induce low frequency torsional oscillations of the drive train of WTGs. This paper addresses this issue and develops a new nonlinear VIC based on objective holographic feedbacks theory. This approach allows transforming the original nonlinear control into a completely controllable system of Brunovsky’s type. Simulation results under various scenarios demonstrate that the proposed method outperforms existing VICs in terms of suppression of low frequency drive-train torsional oscillations, enhancement of system frequency nadir as well as fast and smooth recovery of WTG rotor speed to the original MPP point before the disturbance. The proposed method is also able to coordinate multiple WTGs. Copyright © 2020, The Authors. All rights reserved.

关键词： Frequency response

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Learning Latent Causal Factors from the Intricate Sensor Feedback of Contact-Rich Robotic Assembly Tasks

SSRN

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SSRN 2023年

作者： Chen, Yurou Yu, Jiyang Lin, Zhenyang Shen, Liancheng Liu, Zhiyong The State Key Lab of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China Beijing Institute of Spacecraft System Engineering China Academy of Space Technology Beijing China

Achieving precise robotic assembly is paramount for safety and performance in industrial settings. Conventional assembly methods require tedious manual adjustment of many parameters, and it is challenging to meet the assembly requirements with tight clearance. Robot learning has been at the forefront of research, showing potential for automation and intelligence in robotic operations. However, intricate information such as force feedback is indispensable for high-precision robot assembly tasks, and current learning methods grapple with processing this complex observation data due to discontinuous force changes during operation and the inherent noise from the force sensor. To alleviate the low learning efficiency from the problematic observations, we propose introducing the concept of latent causal factors that cause the sensor observations and truly matter in assembly tasks. This paper analyses the impact of discontinuous and noisy observations and offers two ways to infer causal factors. Based on the implied latent factors, we propose a method that learns high-precision assembly policies from interacting with the environment. The algorithm's performance is evaluated in simulated and real-world nut assembly environments, demonstrating significant improvements over the previous methods. This research also underscores the promise of causal inference in addressing intricate industrial challenges%. © 2023, The Authors. All rights reserved.

关键词： Robotic assembly

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Analysis of drying characteristics and quality of Star Anise (Illicium verum) using microwave vacuum and hot air combined drying

Journal of Biotech Research

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Journal of Biotech Research 2023年 15卷 386-396页

作者： Liu, Yongfu Zhou, Xiaoting Pan, Xiaoli Fan, Wenyan Yang, Guimei Yu, Wangxin Hong, Weisheng School of Physical and Telecommunication Engineering Yulin Normal University Guangxi Yulin China Yulin Center for Food and Drug Control Guangxi Yulin China Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data Processing Yulin Normal University Guangxi Yulin China Center for Applied Mathematics of Guangxi Yulin Normal University Guangxi Yulin China Fangchenggang Agricultural Machinery Service Center Guangxi Fangchenggang China

Star anise, rich in effective active constituents, is extensively employed in the pharmaceutical and food industries. The drying temperature can irreversibly damage these constituents. To enhance the drying quality and efficiency, this study undertook experiments using three drying methods on star anise including microwave vacuum drying, hot air drying, and a combination of microwave vacuum and hot air drying. The research examined the impacts of varying drying conditions on the drying characteristics of star anise, the moisture diffusion coefficient, and the primary component contents (anethole and shikimic acid). Models were separately established for microwave vacuum and hot air thin-layer drying kinetics including Lewis, Weibull distribution, two-term exponential, Wang, and Singh models, and a Weibull distribution model for combined microwave vacuum-hot air drying. The results indicated that drying with microwave vacuum and hot air primarily proceeded in a falling rate drying phase, whereas combined microwave vacuum and hot air drying encompassed both falling rate and constant rate stages. The effective moisture diffusion coefficients (Deff) for microwave vacuum drying and hot air drying of star anise ranged from 3.4423E-07 to 8.8239E-07 m2/s and 2.0386E-08 to 8.8239E-07 m2/s, respectively, while the Deff for combined microwave and hot air drying ranged from 2.8683E-07 to 4.8014E-07 m2/s and 7.9516E-8 to 2.0964E-7 m2/s, respectively. Evidently, segmented combined drying facilitated more convenient moisture diffusion, and both coefficients increased with microwave power and hot air temperature. During the microwave vacuum and hot air drying processes, both the Wang and Singh models and the Weibull distribution models showed good fitting effects. The Weibull distribution model could effectively predict the drying behavior of segmented microwave vacuum and hot air drying of star anise. In comparison with hot air drying time, combined microwave vacuum and hot air dr

关键词： Drying

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