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Push Recovery methods Based on Admittance Control Strategies for a NAO-H25 Humanoid

Push Recovery Methods Based on Admittance Control Strategies...

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RSI/ISM international conference on robotics and Mechatronics (ICROM)

作者： Fatemeh Sadat Mousavi Mehdi Tale Masouleh Ahmad Kalhor Payam Ghassemi Human and Robot Interaction Laboratory School of Electrical nad Computer Engineering University of Tehran Tehran Iran Faculty of New Sciences and Technologies University of Tehran Tehran Iran

ISBN: (纸本)9781728101286;9781728101279

this paper discusses two main investigations regarding push recovery of a NAO humanoid robot. the first part indicates the simulation results of different strategies retrieved from human behaviors, namely: Ankle, Hip, and Hip-ankle strategies. these methods are separately assessed and their efficiencies are discussed. To the end of converting torque parameter to robot's movement with a reasonable approximation in the aforementioned strategies' obtained models, a new approach, the so-called Virtual leg model, is introduced. the second discussion assesses the admittance control strategy, which relies on disturbances' energy absorption. Individual control algorithms are introduced for each disturbances' categories based on NAO's real conditions. this paper proposes a new strategy, which investigates the influence of admittance control coefficients against external disturbances, by considering a virtual interaction between robot's feet and the ground, and introducing a Kalman-filter-based estimator. All proposed methods are simulated in NAO-H25's simulation environment.

关键词： Legged locomotion Hip Admittance Robot kinematics Measurement uncertainty Robot sensing systems

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A comparison of adaptive PID methodologies controlling a DC motor with a varying load

A comparison of adaptive PID methodologies controlling a DC ...

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international conference on Emerging Technologies and Factory automation (ETFA)

作者： Luís Osório Jérôme Mendes Rui Araújo Tiago Matias Institute for Systems and Robotics (ISR-UC) and Department of Electrical and Computer Engineering (DEEC-UC) University of Coimbra Coimbra Portugal

this work addresses the problem of controlling unknown and time varying plants for industrial applications. To deal with such problem several Self-Tuning Controllers with a Proportional Integral and Derivative (PID) structure have been chosen. the selected controllers are based on different methodologies, and some use implicit identification techniques (Single Neuron and Support Vector Machine) while the others use explicit identification (Dahlin, Pole placement, Deadbeat and Ziegler-Nichols) based in the Least Squares Method. the controllers were tested on a real DC motor with a varying load. the results have shown that all the tested methods were able to properly control an unknown plant with varying dynamics.

关键词： Vectors DC motors Support vector machines Heuristic algorithms Neurons Process control Adaptation models

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Gene Prediction by the Scale-limited Gabor Wavelet Transform for Identifying the Protein Coding Regions

Gene Prediction by the Scale-limited Gabor Wavelet Transform...

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international conference on Control, automation, robotics and Vision (ICARCV)

作者： Qian Zheng Wenxiang Zhou Tao Chen Lei Xie Hong Ye Su State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Inertial Technology and Integrated Navigation Laboratory Beihang University Beijing China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

the identification of protein coding regions is one of the important applications of genome sequence analysis. Many digital signal processing (DSP) based methods, which rely on 3-base periodicity of DNA sequences, have been proposed. However, for most Fourier Transform based methods, a prior time-domain window length limits their performances. Even though several wavelet-based methods get rid of the dependence of window length, an overly wide scale range results in the loss of identification accuracy of these methods. In this paper, we propose a novel method based on Scale-limited Gabor Wavelet Transform (SLGWT) for identifying protein coding regions. this method inherits the advantage of wavelet-based methods in the independence of time-domain window length, while maintaining the consistent performance under different wavelet window lengths. More importantly, compared with other wavelet-based method, SLGWT identifies coding regions under narrower and more suitable scale range, thereby improving the identification accuracy and reducing computational load. the experimentations in the sequence and dataset levels verify the superiority of our proposed method.

关键词： Proteins Hidden Markov models Bioinformatics Genomics Encoding Wavelet transforms Time-domain analysis

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Dynamically Mitigating Data Discrepancy with Balanced Focal Loss for Replay Attack Detection

Dynamically Mitigating Data Discrepancy with Balanced Focal ...

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international conference on Pattern Recognition

作者： Yongqiang Dou Haocheng Yang Maolin Yang Yanyan Xu Dengfeng Ke Engineering Research Center for Forestry-oriented Intelligent Information Processing National Forestry and Grassland Administration National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

It becomes urgent to design effective anti-spoofing algorithms for vulnerable automatic speaker verification systems due to the advancement of high-quality playback devices. Current studies mainly treat anti-spoofing as a binary classification problem between bonafide and spoofed utterances, while lack of indistinguishable samples makes it difficult to train a robust spoofing detector. In this paper, we argue that for anti-spoofing, it needs more attention for indistinguishable samples over easily-classified ones in the modeling process, to make correct discrimination a top priority. therefore, to mitigate the data discrepancy between training and inference, we propose to leverage a balanced focal loss function as the training objective to dynamically scale the loss based on the traits of the sample itself. Besides, in the experiments, we select three kinds of features that contain both magnitude-based and phase-based information to form complementary and informative features. Experimental results on the ASVspoof2019 dataset demonstrate the superiority of the proposed methods by comparison between our systems and top-performing ones. Systems trained with the balanced focal loss perform significantly better than conventional cross-entropy loss. With complementary features, our fusion system with only three kinds of features outperforms other systems containing five or more complex single models by 22.5% for min-tDCF and 7% for EER, achieving a min-tDCF and an EER of 0.0124 and 0.55% respectively. Furthermore, we present and discuss the evaluation results on real replay data apart from the simulated ASVspoof2019 data, indicating that research for anti-spoofing still has a long way to go.

关键词： Training Learning systems Deep learning Bridges Time-frequency analysis Neural networks Detectors

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AI-Based Finite-Element Simulation automation Workflow Applied to Automotive Electronics Field

AI-Based Finite-Element Simulation Automation Workflow Appli...

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international conference on (ICEPT) Electronic Packaging Technology

作者： Yinlong Wang Pei Xie Engineering Technology China & Digitalization Bosch Automotive Products (Suzhou) Co. Ltd. City Suzhou China

ISBN: (数字)9798350353808

ISBN: (纸本)9798350353815

Electronic component is one of the key design elements considered during the development of automotive ECU (Electronic Control Unit). As the current state-of-the-art method, FEM (Finite-Element Method) simulation is widely used for thermal design optimization and solder joint reliability assessment of electronics at early stage of ECU development. To address the challenges of modeling fidelity and efficiency, the AI (Artificial Intelligence) integrated automated simulation workflow platform is developed. Leveraging standard and Bosch in-house developed Python libraries called “pyact”, an Ansys-based automation toolset has been developed which accelerates the simulation workflow. With the assistance of AI methodologies, more precise electronic component models could be expected during calibration process. this paper presents 3 different industrial practices and examples focusing on the board level thermal management and solder joint reliability assessment. the first industrial example presents the standardization and automatization of the reliability simulation workflow of chip-resistor components. Utilizing Ansys ACT (Application Customization Toolkit), basic APIs (Application Programming Interface) of ACT are encapsulated into the Python library as pyact, enabling a fully automated simulation workflow to predicted solder joint lifetime. To further realize the fast assessment of reliability and component virtual release, an AI metamodel is derived from automated simulation-based DoE (Design of Experiments). For pursuit of accuracy for simulation models, the second industrial example presents the combination of Bayesian Optimization with BGA (Ball Grid Array) warpage calibration process to outperform the traditional manual methods. the third industrial example outlines another application of Bayesian optimization into the Zth (Transient thermal Impedance) calibration process for component thermal models. Utilizing the multi-objective optimization algorithm, the Zth c

关键词： thermal management of electronics automation Reliability engineering Calibration Finite element analysis Bayes methods Artificial intelligence

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Underactuated Ship Heading Control in Harbor Based on Model-Free Adaptive Sliding Mode Control

Underactuated Ship Heading Control in Harbor Based on Model-...

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Industrial automation, robotics and Control Engineering (IARCE), international conference on

作者： Wei Li Junqing Han Shuai Fang Yazhen Du Yang Cao Jiujiang Branch Tianjin Navigation Instruments Research Institute Tianjin China Maritime College Tianjin University of Technology Tianjin China

ISBN: (数字)9798350380323

ISBN: (纸本)9798350380330

To address the challenges posed by restricted waters, uncertain model parameters, and strong environmental disturbances such as wind and currents during the harbor navigation of underactuated ships, this paper introduces a method for controlling ship heading using partial dynamic linearization, which operates without relying on any model information. Firstly, a partial dynamic linearization model is developed using the system's input-output data, and then the model is adjusted online with changing navigation conditions through pseudo-partial derivative estimation. Additionally, conventional model-free adaptive control methods applied directly to ship heading control in the body coordinate system can result in non-convergent control errors. To solve this problem, this paper introduces a model-free adaptive sliding mode control method. Finally, MATLAB simulation tests and a comparative analysis with the traditional model-free PID control method demonstrate the effectiveness of the proposed control method and its strong robustness against environmental disturbances.

关键词： Adaptation models PI control Navigation Service robots Mathematical models Data models PD control Marine vehicles Adaptive control Sliding mode control

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A Calibration Method based on Heteroscedastic Evolutionary Bayesian Optimization for Simulation System of HVAC

A Calibration Method based on Heteroscedastic Evolutionary B...

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robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Zhe Tan Bo Liu School of Automation Wuhan University of Technology Wuhan China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

In recent years, increasing the energy efficiency of buildings has become one of the objectives of facility managers. Advanced control methods can be used to improve the efficiency of Heating, Ventilation, and Air Conditioning (HVAC). However, advanced control methods cannot be effectively applied due to inconvenient commissioning. therefore, simulating and modeling the HVAC system becomes particularly important for verifying various control algorithms. Modeling and calibrating the HVAC simulation system becomes crucial for the application of various control strategies based on actual operational data, while current calibration methods are usually based on experience. In this research, a method for the calibration of an HVAC model based on Heteroscedastic Evolutionary Bayesian Optimization (HEBO) is presented. Firstly, the HVAC model is built using the Modelica language in the Dymola environment. Secondly, real operation and weather data are fed to the HVAC model to predict the energy consumption of various equipment. thirdly, the Root Mean Squared Error (RMSE) between predicted and real values is minimized by HEBO so that the optimal parameters of the equipment can be obtained. Finally, a case study is conducted to verify the effectiveness of the proposed method. the results show that the CV(RMSE) of calibrated models meets the guideline requirements of ASHRAE, IPMVP, and FEMP.

关键词： HVAC Atmospheric modeling Buildings Predictive models Ventilation Data models Calibration Bayes methods Optimization Robots

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Observability of Two-Time-Scale Multi-Agent Systems with Antagonistic Interactions

Observability of Two-Time-Scale Multi-Agent Systems with Ant...

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robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Mengqi Gu Qingbo Li Kaijie Zhou Jing Chen Jin Yang Huaian Key Laboratory of Millimeter-Wave Communication Technology Huaiyin Normal University Huaian China College of Automation Nanjing University of Posts and Telecommunications Nanjing China Jiangsu Provincial Key Laboratory of Intelligent Electromagnetic Sensing and Communication Huaiyin Normal University Huaian China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

this paper investigates the observability of two-time-scale multi-agent systems (MASs), with particular attention to antagonistic interactions among agents. the study begins by modeling the systems, followed by defining observability and establishing its conditions using singular perturbation theory. Numerical simulations are conducted to demonstrate the effectiveness of the proposed conditions.

关键词： Perturbation methods Reliability theory Numerical simulation Numerical models Observability Artificial intelligence Robots Multi-agent systems Intelligent control

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Energy Efficiency Evaluation and Optimization methods in Electric Transportation Systems

Energy Efficiency Evaluation and Optimization Methods in Ele...

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robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Han Wang Faculty of Electrical and Automation Engineering Nanjing Normal University Nanjing China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

this study presents a reinforcement learning-based framework for optimizing energy efficiency in electric vehicle (EV) and grid interactions. Managing grid load, especially during peak charging times, becomes critical as EV adoption increases. the framework leverages short-term load forecasting with data from the Electricity Load Forecasting dataset to dynamically balance energy distribution. Experimental results show a 131.5% reduction in Peak-to-Average Load Ratio (PALR) with a GRU model, a 97.53% improvement in Charging Efficiency Index (CEI) with a CNN-LSTM model, and a lower RMSE, demonstrating the framework’s effectiveness in enhancing grid integration and EV charging efficiency.

关键词： Adaptation models Load forecasting Electricity Stability criteria Transportation Reinforcement learning Energy efficiency Electric vehicle charging Vehicle dynamics Load modeling

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Hyperspectral Inversion Modeling of Fat and Protein Content in Milk Based on XGBoost

Hyperspectral Inversion Modeling of Fat and Protein Content ...

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international conference on robotics and automation Engineering (ICRAE)

作者： Xu Jin Zhiyun Xiao Alideertu Dong Yining Wang Qixin Nie Lifang Wang College of Electric Power Inner Mongolia University of Technology Hohhot China Key Laboratory of Electromechanical Control of Inner Mongolia Autonomous Region Inner Mongolia University of Technology Hohhot China College of Chemistry and Chemical Engineering Inner Mongolia University Hohhot China Engineering Research Center of Ministry of Education Dairy Product Quality and Safety Control Technology Inner Mongolia University Huohhot China Inner Mongolia Academy of Agriculture and Animal Husbandry Sciences Hohhot China Agricultural Product Quality and Safety Risk Assessment Laboratory of the Ministry of Agriculture and Rural Affairs Hohhot China

ISBN: (纸本)9781665406987

A hyperspectral inversion modeling method is proposed to predict the fat and protein content in milk by integrating SG, CR and XGBoost to address the drawbacks of traditional chemical methods for detecting fat and protein in milk, which require damage to the emulsion itself, complicated operation and environmental pollution. the method first combines Savitzky-Golay (SG) and Continuum-Removal (CR) to pre-process the hyperspectral data, and then uses Correlation-Analysis (CA) to screen the feature bands. Finally, the screened 10 feature bands are used as inputs to build partial least squares regression (PLSR) and XGBoost models, and the model prediction results are compared. the results show that the SG_CR algorithm is an effective hyperspectral preprocessing method to improve modeling accuracy, and the screening of feature bands can greatly reduce model complexity and improve model efficiency while ensuring model accuracy. Compared with the linear model PLSR, the machine learning integration algorithm XGBoost performed optimally. Its fat and protein models have training set coefficients of determination (R2) of 0.9449 and 0.9980, training set root mean square error (RMSE) of 0.2395 (g/100g) and 0.0409 (g/100g), training set relative analysis error (RPD) of 3.8188 and 22.2079, test set R2 of 0.8653 and 0.9273, test set RMSE were 0.4672 (g/100g), 0.2116 (g/100g), and test set RPD were 2.4625, 3.5998.

关键词： Proteins Training Dairy products Machine learning algorithms Predictive models Filtering algorithms Prediction algorithms

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