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Model predictive control of hemodynamics during intravenous general anesthesia 27

Model predictive control of hemodynamics during intravenous ...

引用

27th International Conference on System Theory, control and Computing, ICSTCC 2023

作者： Farbakhsh, Hamed Yumuk, Erhan Othman, Ghada Ben De Keyser, Robin Copot, Dana Birs, Isabela Ionescu, Clara M. Ghent University Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Tech Lane Science Park 125 Zwijnaarde9052 Belgium Istanbul Technical University Department of Control and Automation Engineering Istanbul Turkey Technical University of Cluj-Napoca Department of Automation Memorandumului no. 28 Cluj-Napoca400114 Romania

ISBN: (纸本)9798350337983

In the operating rooms and the intensive care unit, it is crucial to manage the patient's hemodynamic status, which includes factors like cardiac output and mean arterial pressure. Anesthesiologists confront a difficult task while monitoring high-risk patients. Cardiac output optimization has been found to enhance the result of high-risk patients in terms of hospital stay, mortality rate, post-operative problems, etc. The application of standard control approaches is restricted because the mean arterial pressure response of a patient using vasoactive medicines is modeled by a first-order dynamical system with time-varying parameters and a time-varying delay in the control input. In order to circumvent implementation challenges, this work develops an approximation technique that describes the system using a higher-order model. Predictive control is therefore used to comprehend the practical application of higher-order hemodynamic systems. The effectiveness of this strategy is demonstrated by the simulations and outcomes that are given. © 2023 IEEE.

关键词： Model predictive control

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XSpace: Self-learning platform for implementation of digital control algorithms 14

XSpace: Self-learning platform for implementation of digital...

引用

14th IEEE Global engineering Education Conference, EDUCON 2023

作者： Caceres, Pablo Cardenas Cieza Huane, Leslie Y. Horna Vilcahuaman, Ingrid M. Pauyac Estrada, Claudia R. Casano, Celso De-La-Cruz Tafur Sotelo, Julio C. Pontificia Universidad Catolica Del Peru Department of Engineering Electronics Section Lima Peru Degree Program Pontificia Universidad Catolica Del Peru Department of Engineering Control and Automation Master Engineering Lima Peru

ISBN: (纸本)9798350399431

In the electronic engineering undergraduate program, Peruvian universities offer different theoretical courses of Automatic control that do not present enough practical approach to the algorithms that are studied during the progress of these courses;however, the approach to implementation is very important to achieve good performance in the industry and researching. In this work is presented XSpace, an innovative and friendly platform which consists of a robust hardware that allows the student to take it home;this way, the student is given the opportunity to implement digital control algorithms learned in the theoretical classes. The effectiveness of this platform is shown using a proposed methodology which evidences greater interest, efficiency and efficacy in students at the Automatic control area. This project was implemented in the 'control Systems' course at Pontificia Universidad Catolica del Peru (PUCP) from 2020 to 2022. Results are presented through a student survey and a history of average grades during the academic periods the platform was employed. © 2023 IEEE.

关键词： Students

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An Event-Triggered Tracking control Scheme Based on Predictive control Method and its Application 42

An Event-Triggered Tracking Control Scheme Based on Predicti...

引用

42nd Chinese control Conference, CCC 2023

作者： Cao, Lei Yumuk, Erhan Ionescu, Clara-Mihaela Liu, Guo-Ping Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China Ghent University Dynamical Systems and Control Research Group Department of Electromechanical Systems and Metal Engineering Ghent9052 Belgium Center for Control Science and Technology Southern University of Science and Technology Shenzhen518055 China Istanbul Technical University Department of Control and Automation Engineering Istanbul34467 Turkey

ISBN: (纸本)9789887581543

In this paper, the tracking control problem for networked control system (NCS) under communication delays is investigated. In order to realize the tracking of the NCS, an event-triggered predictive control strategy is provided to compensate for the delays and achieve stability. Both tracking performance and input increments are considered in the proposed cost function. Based on the incremental inputs, an event-triggered mechanism is established to reduce the communication costs. The efforts of different parameters are illustrated through the results of the simulation, and the effectiveness of the proposed control scheme is also validated from the application of the networked lighting setup. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Networked control systems

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Data-Based Soft Fault Diagnosis of a Three-Phase DC/AC Converter 7

Data-Based Soft Fault Diagnosis of a Three-Phase DC/AC Conve...

引用

7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Chen, Cen Du, He Cai, Xi Wang, Haoran Zhai, Guofu Harbin Institute of Technology Department of Electrical Engineering and Automation Harbin China Engineering Corporation China Three Gorges Construction Chengdu China Three Gorges Intelligent Industrial Control Technology Company Wuhan China

ISBN: (纸本)9798350359558

With the widespread use of power electronic equipment, accurately identifying soft faults in power electronic converters is crucial for the stable and reliable operation of power electronic equipment. This paper proposed a soft fault diagnosis method for three-phase DC/AC converter using a data-based approach. Firstly, simulation analysis is conducted on the soft faults of three-phase DCI AC converter, and appropriate test signals are selected as data sources. Then, the LSTM neural network and its variants are used to obtain fault diagnosis models. Finally, the method is validated through experiments, and the results show that it has good performance in soft fault diagnosis of the three-phase DCI AC converter. © 2024 IEEE.

关键词： Failure analysis

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Language Reasoning in Vision-Language-Action Model for Robotic Grasping

Language Reasoning in Vision-Language-Action Model for Robot...

引用

2024 China automation Congress, CAC 2024

作者： Fan, Lingling Chen, Kang Xu, Zhezhuang Yuan, Meng Huang, Ping Huang, Weibing College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China Evomotion Co. Ltd. Guangdong Shenzhen518000 China

ISBN: (纸本)9798350368604

Grasping tasks are crucial for the interaction between the robot and environment, requiring the robot to make autonomous decisions based on environmental conditions and instructions. Recently, multimodal Vision Language Models (VLMs) have demonstrated significant potential for robotic grasping. However, previous work has often been confined to high-level planning due to the gap between the text output of VLMs and the numerical predictions of robot actions, as well as the challenges of transferring rich semantic information from large models to the prediction of grasping actions. In this paper, we co-fine-tune a pre-trained VLM using the mix of large-scale visual language data and robotic grasping trajectory data, integrating model into an end-to-end robot control system to construct a Vision Language Action Model (VLA) capable of generating the robot’s underlying actions. Simultaneously, to fully leverage the prior knowledge and reasoning capabilities of the pre-trained model, we insert a language reasoning structure to bridge the mapping from high-level tasks to low-level actions. This method first deduces the relevant information regarding the target object and the end-effector motions, followed by predicting the grasping actions value with finer granularity based on the language reasoning, thereby enhancing the accuracy of action predictions. A series of grasping experiments demonstrate that our method achieves a high grasping success rate under flexible language instructions and exhibits strong generalization capabilities for unseen objects and scenes. © 2024 IEEE.

关键词： Visual languages

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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...

引用

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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Transformer-Based Sequence Modeling with Action Discretization for Robotic Grasping

Transformer-Based Sequence Modeling with Action Discretizati...

引用

2024 China automation Congress, CAC 2024

作者： Hou, Yaokun Zheng, Song Xu, Zhezhuang Yuan, Meng Huang, Ping Huang, Weibing College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China Evomotion Co. Ltd. Guangdong Shenzhen518000 China

ISBN: (纸本)9798350368604

The powerful representational and sequential modeling capabilities of Transformer have been validated in various fields such as natural language processing. However, how to better address sequential decision-making problems like robotic grasping through the Transformer architecture and achieve autonomous control of robotic grasping remains a longstanding challenge. Models that directly output continuous decision actions for robotic arms often rely on mean squared error (MSE) loss for training, which is unable to effectively handle the randomness and diversity of actions. This limitation leads to the generation of relatively singular actions in certain grasping scenarios, reducing the success rate of grasping. To address this issue, this paper proposes a Transformer-based method for discretizing robotic arm actions, where actions are discretized by dimension to enable autoregressive modeling. Experimental results demonstrate that this method effectively improves the grasping performance of robotic arms in simulation environments. © 2024 IEEE.

关键词： Mean square error

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Compensation of the Temperature Impact on the Characteristics of a Titania-Silica Thin Film Humidity Sensor Element

Compensation of the Temperature Impact on the Characteristic...

引用

2023 International Conference Automatics and Informatics, ICAI 2023

作者： Ivanov, Stefan Nedev, Nedyu Nenova, Zvezditza Technical University of Gabrovo Department of Automation Information and Control Systems Gabrovo Bulgaria Technical University of Gabrovo Department of Fundamentals of Electrical and Power Engineering Gabrovo Bulgaria

ISBN: (纸本)9798350312911

In the present work is investigated the impact of ambient temperature in the range of 20°C to 50°C under a change in relative humidity RH of 20% up to 92 % on the characteristics of a highly sensitive TiO2-SiO2-based thin-film impedance humidity sensor element doped with Ce and prepared by a sol-gel method. The variation of sensor impedance changes in a very wide range - about 4 orders of magnitude. The sensor element is connected in a measurement circuit based on an AC bridge, a variable gain amplifier, a precision rectifier, and a microcontroller with a built-in analog-to-digital converter. The use of artificial neural networks monitoring the ambient temperature and measured voltage is proposed for the realization of the temperature compensation of the characteristics. The proposed approach allows compensating the impact of temperature and performing measurements when connecting humidity sensing elements with a very wide range of impedance change. © 2023 IEEE.

关键词： Silica

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Multi-Trajectory Prediction of Pedestrian Based on Deep Neural Network Architecture 6

Multi-Trajectory Prediction of Pedestrian Based on Deep Neur...

引用

6th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2023

作者： Astuti, Lia Lin, Yu-Chen Chen, Wen-Hui Feng Chia University Department of Automatic Control Engineering Taichung Taiwan National Taipei University of Technology Department of Graduate Institute of Automation Technology Taipei Taiwan

ISBN: (纸本)9798350323535

Multimodal learning input has been used to predict the single trajectory of pedestrians. However, the single-trajectory is not efficient in making the vehicle avoid the sudden direction changes of the pedestrian in the drivable area. Therefore, we proposed a multi-trajectory prediction model with a Deep Neural Network (DNN) using an egocentric perspective. First, we input unimodal learning i.e., the historical trajectory sequences into the temporal encoder module. Second, the vision DNN-based network module was used to process the trajectory predictions through the temporal attention mechanism. Third, the linear projection was used for the decoder module to generate single- and multi-trajectory predictions for collision avoidance of vehicles and pedestrians. Finally, the proposed model outperformed previous state-of-the-art models in the experiments on publicly available Pedestrian Intention Estimation (PIE) and Joint Attention in Autonomous Driving (JAAD) datasets. © 2023 IEEE.

关键词： Trajectories

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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...

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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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