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Data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 47-63页

作者： Yongliang Yang Zihao Ding Rui Wang Hamidreza Modares Donald C.Wunsch Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education School of Automation&Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China School of Automation Beijng Institute TechnologyBeijing 100081China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Mechanical Engineering Department Michigan State UniversityEast LansingMI 48824 USA Department of Electrical&Computer Engineering Missouri University of Science&TechnologyRollaMO 65401 USA

In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the *** presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller *** task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the ***-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance *** the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity *** this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task *** simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.

关键词： Adaptive impedance control data-driven method human-robot interaction(HRI) reinforcement learning velocity-free

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Programmable photonic time circuits for highly scalable universal unitaries

arXiv

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arXiv 2023年

作者： Piao, Xianji Yu, Sunkyu Park, Namkyoo Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of

Programmable photonic circuits (PPCs) have garnered substantial interest in achieving deep learning accelerations and universal quantum computations. Although photonic computation using PPCs offers critical advantages, including ultrafast operation, energy-efficient matrix calculation and room-temperature quantum states, its poor scalability impedes the integration required for industrial applications. This challenge arises from the temporally one-shot operation using propagating light in conventional PPCs, which leads to the light-speed increase of device footprints. Here we propose a concept of programmable photonic time circuits, which employ time-cycle-based computations analogous to the gate cycling in the von Neumann architecture and quantum computation. As a building block, we develop a reconfigurable SU(2) time gate composed of two resonators, which have tunable resonances and are coupled through time-coded dual-channel gauge fields. We demonstrate universal U(N) operations with high fidelity using the systematic assembly of the SU(2) time gates, achieving improved scalability from O(N2) to O(N) in both the footprint and gate number. This result opens a pathway to industrial-level PPC implementation in very large-scale integration. © 2023, CC BY.

关键词： Scalability

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Enhancing Organic Solar Cell Performance Using Novel Conjugated Compounds

Enhancing Organic Solar Cell Performance Using Novel Conjuga...

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Innovative Research in Applied Science, engineering and Technology (IRASET),Conference on

作者： Imane EL MHAMEDI Zakaria EL MALKI Materials and Systems Control (MMSC) Computer Engineering and Intelligent Electrical Systems (2ISEI) Laboratory High School of Technology (ESTM) University Moulay Ismail Meknes Morocco

ISBN: (数字)9798350309508

ISBN: (纸本)9798350309515

This article deals with a series of six organic D-n-A molecules consisting of thiophene and carbazole. This series includes molecules with identical donor and acceptor groups, but different π-systems. We examined the effect of substituting thiophene (T) with phenylene (P), carbazole (C), fluorene (F) and anthracene (A) as π-systcms on the physical properties of these molecules. Using one-dimensional microelectronic and photonic structure analysis (AMPS-1D), we investigated and simulated the operational characteristics of orgnic heterojunction solar cells. These solar cells were constructed using the compound D1-B-Ed-B-D2-A as electron donor and [6], [6]-phenyl-C61-butyric acid methyl ester (PCBM) as electron acceptor. The performance of organic photovoltaic cells has shown significant improvements on various parameters, such as open-circuit voltage (Voc), short-circuit current density (Jsc), fill factor (FF), power conversion efficiency (PCE), as well as series resistance (Rs) and shunt resistance (Rsh). In addition, devices based on P3-B-Ed-B-T3-A/PCBM and P3-B-Ed-B-T3-A/PCBM show power conversion efficiencies (PCE) of 8% and 9%, respectively. The introduction of a PEDOT layer between the indium-tin oxide (ITO) and the aluminum oxide layer significantly improved the performance of devices based on P3-B-Ed-B-T3-A/PCBM and P3-B-Ed-B-P3-A/PCBM, with PCEs of 14% and 15%, respectively.

关键词： Performance evaluation Resistance Temperature Photovoltaic cells Short-circuit currents Voltage Software

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Adaptive Automatic Generation Control for Improved Stability of Power systems with Utility-Scale Photovoltaic Plants

Adaptive Automatic Generation Control for Improved Stability...

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Renewable Energy and Hydrogen Technologies (GlobConHT), IEEE IAS Global Conference on

作者： Rajan Ratnakumar Ganesh K. Venayagamoorthy Holcombe Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University Clemson USA

Stability problems arise when large utility-scale solar photovoltaic (PV) plants are integrated into bulk power systems. The intermittent nature of solar radiation results in PV power generation variations, which must be compensated by the conventional power plants (synchronous generators) to regulate the frequency of the power system by balancing generation-load. The compensation involves generation dispatch changes of the synchronous generators. The PV plant variations and synchronous generators' dispatch changes could give rise to electromechanical oscillations (EMOs) in the power system. Severe EMOs can lead to power system instability, and this can be avoided by intelligently modulating the rate of change of dispatch of the synchronous generators during PV plant output variations. The intelligent modulation of the rate of change of dispatch can be implemented via an adaptive automatic generation control (A-AGC). This paper presents the development of an A-AGC based on an EMO index derived from phasor measurement units to ensure the stability of the power system. Typical results are presented to illustrate the operation and performance of A-AGC during PV power variations.

关键词： Photovoltaic systems Renewable energy sources Stability criteria Automatic generation control Power system stability Synchronous generators Table lookup

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Retinal disorder diagnosis based on hybrid deep learning models

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Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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An Artificial Intelligence Approach for Virtual Prototyping of Functional Situational Awareness systems for Hybrid Military Vehicles

An Artificial Intelligence Approach for Virtual Prototyping ...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Deborah George Ganesh K. Venayagamoorthy Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University Clemson SC USA

Situational awareness in complex systems is important for their reliable and efficient operations. Complex systems consist of components/nodes and subsystems. Functional situational awareness (FSA) is focused on providing qualitative and quantitative functional capabilities of components, subsystems, and the system over time. Safe-/mission-critical systems require FSA in real-time. The development of an artificial intelligence (AI)-based FSA system inferencing tool, herein, referred to as an FSA inference system development engine (FIDE), tailored to hybrid military ground vehicles (HMGVs) is presented. FIDE can be utilized to generate preliminary designs, virtual prototyping of FSA and its evaluation on actual HMGVs as well virtual vehicle testbeds. FIDE consists of four modules, namely, i) intelligent knowledge acquisition, ii) FSA topology model, iii) FSA engine and iv) human-computer interface (HCI). The development and operation of these modules is presented. FIDE generated FSA systems can ensure reliable and efficient operation of Vehicle Power systems (VPSs). Case studies are presented for virtual prototypes of an FSA engines and HCIs using FIDE.

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Data-Driven Digital Twins for Power Estimations of a Solar Photovoltaic Plant

Data-Driven Digital Twins for Power Estimations of a Solar P...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Michael Walters John Yonce Ganesh K. Venayagamoorthy Holcombe Department of Electrical and Computer Engineering Realtime Power and Intelligent Systems Laboratory Clemson University Clemson United States

Renewable energy generation sources (RESs) are gaining increased popularity due to global efforts to reduce carbon emissions and mitigate effects of climate change. Planning and managing increasing levels of RESs, specifically solar photovoltaic (PV) generation sources is becoming increasingly challenging. Estimations of solar PV power generations provide situational awareness in distribution system operations. A digital twin (DT) can replicate PV plant behaviors and characteristics in a virtual platform, providing realistic solar PV estimations. Furthermore, neural networks, a popular paradigm of artificial intelligence may be used to adequately learn and replicate the relationship between input and output variables for data-driven DTs (DD-DTs). In this paper, DD-DTs are developed for Clemson University's 1 MW solar PV plant located in South Carolina, USA to perform realistic solar PV power estimations. The DD-DTs are implemented utilizing multilayer perceptron (MLP) and Elman neural networks. Typical practical results for two DD-DT architectures are presented and validated.

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Digital Twins for Creating Virtual Models of Solar Photovoltaic Plants

Digital Twins for Creating Virtual Models of Solar Photovolt...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Deborah George Ganesh K. Venayagamoorthy Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University Clemson SC USA

Amidst the challenges posed by the high penetration of distributed energy resources (DERs), particularly a number of distributed photovoltaic plants (DPVs), in modern electric power distribution systems (MEPDS), the integration of new technologies and frameworks become crucial for addressing operation, management, and planning challenges. Situational awareness (SA) and situational intelligence (SI) over multi-time scales is essential for enhanced and reliable PV power generation in MEPDS. In this paper, data-driven digital twins (DTs) are developed using AI paradigms to develop actual and/or virtual models of DPV s, These DTs are then applied for estimating and forecasting the power outputs of physical and virtual PV plants. Virtual weather stations are used to estimate solar irradiance and temperature at user-selected locations in a localized region, using inferences from physical weather stations. Three case studies are examined based on data availability: physical PV plant, hybrid PV plants, and virtual PV plants, generating real-time estimations and short-term forecasts of PV power production that can support distribution system studies and decision-making.

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Consensus Control of Leader-Following Multi-Agent systems in Directed Topology With Heterogeneous Disturbances

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 423-431页

作者： Qinglai Wei Xin Wang Xiangnan Zhong Naiqi Wu the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049and also with Qingdao Academy of Intelligent IndustriesQingdao 266109China the Department of Computer and Electrical Engineering and Computer Science Florida Atlantic UniversityBoca Raton FL33431 USA the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and SystemsMacao University of Science and TechnologyMacao 999078China

This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown *** main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic *** traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent *** introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local *** the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is *** simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.

关键词： Consensus control directed topology external disturbance multi-agent(MA)systems

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Fractional Order Linear Active Disturbance Rejection Control for Linear Flexible Joint System

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computers, Materials & Continua 2022年第3期70卷 5133-5142页

作者： Ibrahim M.Mehedi Rachid Mansouri Ubaid M.Al-Saggaf Ahmed I.M.Iskanderani Maamar Bettayeb Abdulah Jeza Aljohani Thangam Palaniswamy Shaikh Abdul Latif Abdul Latif Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah21589Saudi Arabia L2CSP Laboratory Mouloud Mammeri UniversityTizi OuzouAlgeria Electrical&Computer Engineering Department University of SharjahUnited Arab Emirates Department of Nuclear Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics King Abdulaziz UniversityJeddah21589Saudi Arabia

A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this *** this control scheme,the performance against disturbances,uncertainties,and attenuation is *** active disturbance rejection control(LADRC)is mainly based on an extended state observer(ESO)technology.A fractional integral(FOI)action is combined with the LADRC technique which proposes a hybrid control scheme like *** this FOI action improves the robustness of the standard *** set-point tracking of the proposed FO-LADRC scheme is designed by Bode’s ideal transfer function(BITF)based robust closed-loop concept,an appropriate pole placement *** effectiveness of the proposed FO-LADRC scheme is illustrated through experimental results on the linear flexible joint system(LFJS).The results show the enhancement of the robustness with disturbance ***,a comparative analysis is presented with the results obtained using the integer-order LADRC and FO-LADRC scheme.

关键词： Active disturbance rejection fractional calculus ADRC pole placement linear flexible joint system robust control

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