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Unscented Kalman Filter for State of Charge Estimation of Lithium Titanate Battery 20

Unscented Kalman Filter for State of Charge Estimation of Li...

20th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2023

作者： Dardchuntuk, Joshua Chun-Ken Banjerdpongchai, David Faculty of Engineering Chulalongkorn University Center of Excellence in Intelligent Control Automation of Process Systems Department of Electrical Engineering Pathumwan 254 Phayathai Road Bangkok10330 Thailand

ISBN: (纸本)9798350310467

An accurate estimation of the state of charge (SoC) of lithium titanate (LTO) batteries is required for their effective operation and management. In this study, we propose an unscented Kalman filter (UKF) approach for estimating the SoC of LTO batteries, which are challenging to assess due to the nonlinear voltage-SoC relationship and aging impact. Our approach uses a state and measurement model based on LTO's electrochemical characteristics and employs sigma points and weights to address nonlinearities. According to the findings of our research, the UKF-based methodology has high accuracy, rapid convergence, and resilience to discharge rate, outperforming or matching the capabilities of existing state-of-the-art approaches. This work provides a novel and effective solution for LTO battery SoC estimation, useful for applications in electric vehicles, energy storage, and smart grid energy systems. © 2023 IEEE.

关键词： Battery management systems

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Performance Comparison of Lightweight CNN Models for Drone Collision Avoidance Dataset 20

Performance Comparison of Lightweight CNN Models for Drone C...

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20th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2023

作者： Zufar, Rifqi Nabila Banjerdpongchai, David Chulalongkorn University Center of Excellence in Intelligent Control Automation of Process Systems Department of Electrical Engineering Faculty of Engineering 254 Phayathai Road Bangkok Pathumwan10330 Thailand

ISBN: (纸本)9798350310467

Collision Avoidance System (CAS) is important for drone safety. CAS consists of three steps e.g., obstacle sensing, collision prediction, and collision avoidance. Collision prediction enables drones to gain information, process information, and estimate whether the object has a risk of collision. Convolution Neural Network (CNN) is one of the methods that can be employed for collision prediction. However, CNN is a method that needs a large data in the training. Dario Pedro et al. provided a dataset called the CoLANet dataset that consists of VDOs of collision drones. Subsequently, they proposed a new algorithm called Neural Network Pipeline which has a Convolution Neural Network (CNN) part to extract the feature from a couple of images. CNN extracts images by using MobileNetV2 as a pre-trained model. They chose MobileNetV2 due to training performance from another dataset. This paper aims to assess the performance of lightweight CNN models using the CoLANet dataset. The models will be trained on the Keras library with parameters of fewer than ten million. The models will be validated by Confusion Matrix and Receiver Operating Characteristics. In conclusion, we examine which pre-trained CNN model has the best performance and suggest ongoing work. © 2023 IEEE.

关键词： Drones

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The need for neuromorphic computing in industrial robotics

The need for neuromorphic computing in industrial robotics

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2023 International Conference on Artificial Intelligence and Power engineering, AIPE 2023

作者： Bhanja, Tapanta Nusbaum, Jonathan Abuibaid, Khalil Legler, Tatjana Wagner, Achim Ruskowski, Martin University of Kaiserslautern-Landau Machine Tools and Control Systems Department of Mechanical and Process Engineering Kaiserslautern Germany German Research Centre for Artificial Intelligence Innovative Factory Systems Kaiserslautern Germany

ISBN: (纸本)9798350310788

With Moore's law coming to its limits, the rate of increase in compute power available for processing applications is similarly coming to a halt. This implies that the compute intensive tasks, such as robotics, artificial intelligence, and high-performance space computing need innovative ways to cater their ever-increasing compute needs. One innovative way to solve computational bottlenecks is to bring compute and memory together, as opposed to the Von Neumann computational model, with greater degree of parallelism in an event-based, asynchronous computation paradigm. Neuromorphic computing is one such paradigm that draws its inspiration from the brain. Energy and computational efficiency, asynchronous and event-based processing being its salient features, neuromorphic computing is an area worth exploring for compute intensive tasks. In this paper, the authors explore the possibilities and benefits of neuromorphic computing in robotics, and establish possible research directions that could benefit the robotics domain. © 2023 IEEE.

关键词： Robotics

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Modulated Degradation Rates of Bone Mineral-Like Calcium Phosphate Glass to Support the Proliferation and Osteogenic Differentiation of Bone Marrow-Derived Stem Cells

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Journal of Bionic engineering 2024年第4期21卷 1960-1974页

作者： Lizhe He Yuye Huang Jiafei Gu Xiaoling Liu Jun Yin Xiang Gao Department of Neurosurgery The First Affiliated Hospital of Ningbo UniversityNingbo315010China Center for Medical and Engineering Innovation The First Affiliated Hospital of Ningbo UniversityNingbo315010China The State Key Laboratory of Fluid Power Transmission and Control Systems Key Laboratory of 3D Printing Process and Equipment of Zhejiang ProvinceSchool of Mechanical EngineeringZhejiang UniversityHangzhou310028China Faculty of Science and Engineering University of Nottingham Ningbo ChinaNingbo315100China

With an elemental composition similar to bone mineral,and the ability to release phosphorus and calcium that benefit bone regeneration,Calcium Phosphate Glass(CPG)serves as a promising component of bone tissue engineering ***,the degradation of CPG composites typically results in increased acidity,and its impact on bone-forming activity is less *** this work,we prepared 3D-printed composite scaffolds comprising CPG,Poly-ε-caprolactone(PCL),and various Magnesium Oxide(MgO)*** the MgO content effectively suppressed the degradation of CPG,maintaining a physiological pH of the degradation *** the degradation of CPG/PCL scaffolds resulted in upregulated apoptosis of Rat Bone Marrow-derived Stem Cells(rBMSC),scaffolds containing MgO were free from these negative impacts,and an optimal MgO content of 1 wt%led to the most pronounced osteogenic differentiation of *** work demonstrated that the rapid degradation of CPG impaired the renewability of stem cells through the increased acidity of the surrounding media,and MgO effectively modulated the degradation rate of CPG,thus preventing the negative effects of rapid degradation and supporting the proliferation and osteogenic differentiation of the stem cells.

关键词： Phosphate glass Polymer composites 3D printing Bone tissue engineering Scaffolds

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New Hysteresis control Block for Shunt Active Power Filter for Harmonics Compensation Generated by CFLs with PQ Theory 1

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2nd International Conference on Green Energy Conversion System, ICGECS 2023

作者： Hajjej, Mohamed Sbita, Lassaad El Aroudi, Abdelali Mandal, Kuntal Research Laboratory of Process Energies Environment and Electrical Systems National Engineering School of Gabes University of Gabes Zrig Eddakhlania6029 Tunisia Department of Electronics Electrical Engineering and Automatic Control Universitat Rovira i Virgili Tarragona Spain

ISBN: (数字)9789819761487

ISBN: (纸本)9789819761470

This paper proposes a New Modulation Hysteresis control block for a three phase four wire Shunt Active Power Filter (SAPF) for currents harmonics compensation generated by Compact Fluorescents Lamps (CFLs). This study employs the PQ power control strategy. The performance of the SAPF is evaluated under both simple hysteresis controller and under the new modulation hysteresis controller conditions using the Matlab/Simulink platform. The findings simulation results demonstrate that the proposed new technique can improve the power quality of the main, and the total harmonic distortion (THD) optimization, which also confirms the effectiveness of the approach. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Harmonic analysis

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Recent Developments in Event-Triggered control of Nonlinear systems:An Overview

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无人系统（英文） 2023年第1期11卷 27-56页

作者： Pengpeng Zhang Tengfei Liu Jie Chen Zhong-Ping Jiang Department of Control Science & Engineering Frontiers Science Center for Intelligent Autonomous SystemsTongji UniversityShanghai 201804P.R.China State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819P.R.China Department of Electrical and Computer Engineering New York University370 Jay StreetBrooklynNY 11201USA

Event-triggered control is a most popular paradigm for transferring feedback information in an economical"as needed"*** study of event-triggered control can be traced back to the *** significant advances on the topic of control over networks and the topic of nonlinear control systems over the last two decades,event-triggered control has quickly emerged as a major theoretical subject in control *** of event-triggered control are wide-spread ranging from embedded control systems and industrial control processes to unmanned systems and cyber-physical transportation *** this paper,we first review developments in the synthesis of event-triggered sampling *** event triggering mechanisms,such as static event trigger,dynamic event trigger,time-regularized event trigger,and event trigger with positive threshold offsets,are systematically ***,we study how to design a stabilizing controller that is robust with respect to the sampling ***,we review some recent results in the directions of self-triggered control,event-triggered tracking control and cooperative control,and event-triggered control of stochastic systems and partial differential equation *** applications of event-triggered control are also discussed.

关键词： Event-triggered control event-triggered sampling mechanism event-triggered controller

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Model-based Estimation of Ventricular Cerebrospinal Fluid Volume

Model-based Estimation of Ventricular Cerebrospinal Fluid Vo...

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control Technology and Applications (CCTA),

作者： Fabian Flürenbrock Simon Muntwiler Leonie Korn Marianne Schmid Daners Melanie N. Zeilinger Department of Mechanical and Process Engineering ETH Zurich Institute for Dynamic Systems and Control Zurich Switzerland

ISBN: (数字)9798350370942

ISBN: (纸本)9798350370959

This paper introduces a model-based estimator for ventricular cerebrospinal fluid (CSF) volume as a step toward improved hydrocephalus patient monitoring and therapy. For the development of this estimator, we propose a three-step pipeline: First, optimal experiment design is used to plan a safe medical intervention that maximizes the information observed about the patient’s CSF dynamics. Second, the unknown parameters of a state-space model describing the CSF dynamics are identified through maximum likelihood estimation employing either expectation maximization or nonlinear programming. Third, a Kalman filter that uses intracranial pressure and bioimpedance measurements for online CSF volume estimation is constructed based on the identified CSF dynamics model. A custom-built measurement system and mechatronic test bench are used for in-vitro validation of the introduced methods. The model-based estimator achieves a 5.56 % normalized root-mean-square estimation error during experimental testing. Smart shunt systems for hydrocephalus therapy could be augmented by the proposed estimator to allow for direct CSF volume regulation instead of pressure-driven CSF drainage control.

关键词： Solid modeling Patient monitoring Mechatronics Volume measurement Biological system modeling Pipelines Medical treatment

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A Semisupervised Soft-Sensor of Just-in-Time Learning With Structure Entropy Clustering and Applications for Industrial processes Monitoring

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 722-733页

作者： Li, Dong Liu, Yiqi Huang, Daoping Xu, Chong South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science and Engineering Guangzhou510640 China Technical University of Denmark Process and Systems Engineering Center Department of Chemical and Biochemical Engineering Lyngby2800 Denmark South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Gannan Normal University School of Physics and Electronic Information Ganzhou341000 China

To monitor industrial processes properly, soft-sensors are widely used to predict significant but difficult-to-measure quality variables. However, the prediction performances of traditional data-driven soft-sensors are usually unacceptable once suffering from high-nonlinear, high-dimension, and imblance data issues. Therefore, a semisupervised soft-sensor, which is learned by a just-in-time method with structure entropy clustering (SS-JITL-SEC), is proposed aiming to improve prediction performance with a simpler way. Inspired by a divide and conquer strategy, a novel SEC method is proposed to achieve several clusters and then to translate the highly complex and nonlinear modeling problems into simple and linear ones. Moreover, the training dataset is extended through a mixed SS labeling approach. Finally, dissimilarity-based JITL works together with the resulting clustering subdatasets to formulate a local adaptive prediction model. Two datasets from different types of wastewater treatment plants are used to verify the effectiveness of the proposed soft-sensor. The results show that the SS-JITL-SEC soft-sensor can achieve better prediction performance than other standard counterparts, and even for effective process monitoring with the resulted residuals. © 2020 IEEE.

关键词： Entropy

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Data-Driven EMPC with Design of Terminal Ingredients

Data-Driven EMPC with Design of Terminal Ingredients

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International Conference on control, Instrumentation, and Automation

作者： Fatemeh Ostovar Ali Akbar Safavi Leonhard Urbas Department of Power & Control Engineering Shiraz University Shiraz Iran Department of Process Control Systems Technische Universität Dresden Dresden Germany

ISBN: (数字)9798331509972

ISBN: (纸本)9798331509989

This paper introduces a novel data-driven economic model predictive control (EMPC) framework for linear time-invariant (LTI) systems, using Willems’ Fundamental Lemma to describe system behavior with persistently exciting data. Our method incorporates terminal ingredients, including a terminal cost and terminal constraint, to ensure recursive feasibility and asymptotic stability. We detail the design procedure for these terminal ingredients within the data-driven EMPC context. The paper concludes by confirming the strong duality property, feasibility and stability of the economically optimal equilibrium in the closed-loop system. The proposed EMPC framework is validated through its application to an isothermal stirred-tank reactor (CSTR), demonstrating its effectiveness.

关键词： Linear systems Asymptotic stability Costs Instruments Chemical reactions Stability analysis Nonlinear systems Isothermal processes Optimization Predictive control

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A Markov Chain Monte Carlo approach for Pseudo-Input selection in Sparse Gaussian processes

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IFAC-PapersOnLine 2023年第2期56卷 10515-10520页

作者： Anna Scampicchio Sanjay Chandrasekaran Melanie N. Zeilinger Institute for Dynamic Systems & Control Department of Mechanical & Process Engineering ETH Zürich Department of Information Technology & Electrical Engineering ETH Zürich

The effectiveness of non-parametric methods for regression comes at the price of high computational complexity. In fact, these methods scale as O(N 3 ), where N is the number of available data points. One possible option to address this issue consists in introducing a set of fictitious (pseudo-) inputs of size M ≪ N such that the computational effort is reduced to O(M 2 N). To estimate hyper-parameters and pseudo-inputs, a non-convex optimization problem needs to be solved. As opposed to the conventional gradient-based approach used in the literature, this paper proposes a stochastic scheme leveraging Markov Chain Monte Carlo methods. Numerical comparisons show that the latter returns a more efficient set of pseudo-inputs, leading to a superior performance in terms of mean squared error.

关键词： Non-parametric Methods Bayesian Statistics stochastic simulation Monte Carlo Methods

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