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检索条件"任意字段=3rd International Symposium on Control Engineering and Robotics, ISCER 2024"

共 600 条记录，以下是201-210 订阅

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Neural Network Approaches for Magnetization Surface Prediction in Switched Reluctance Motors: Classical, Radial Basis Function, and Physics-Informed Models 3

Neural Network Approaches for Magnetization Surface Predicti...

引用

3rd IEEE international Conference on Problems of Informatics, Electronics and Radio engineering, PIERE 2024

作者： Demidova, Galina Bogdanov, Andrey Iaremenko, Andrei Xirong, Zhu Chen, Hao Anuchin, Alecksey Moscow Power Engineering Institute Electric Drive Department Moscow Russia Itmo University Faculty of Control System and Robotics Saint-Petersburg Russia School of Electrical and Power Engineering China University of Mining and Technology Xuzhou China

ISBN: (纸本)9798331516321

This paper investigates the prediction of magnetization surfaces in Switched Reluctance Motors using three distinct methods: classical Neural Networks, Radial Basis Function networks, and Physics-Informed Neural Networks. The study utilizes experimental data from a 7.5 kW SRM to assess the performance of these approaches, with all methods implemented in Python. Among the methods analyzed, PINN demonstrates the highest accuracy in predicting the magnetization surfaces, effectively capturing the underlying physical behavior of the motor. The computational costs of each method are evaluated, providing insights into training times, inference speeds, and floating-point operations per sample. The findings reveal that while NN offers a reasonable balance between performance and efficiency, the RBF method excels in training speed but shows limitations in capturing the physical dynamics of the system. In contrast, the PINN not only delivers superior predictive performance but also emphasizes the significance of incorporating physical principles into machine learning frameworks. The results highlight the applicability of these methods across various types of SRMs, suggesting their potential for enhancing control strategies in electrical and power engineering applications. © 2024 IEEE.

关键词： Radial basis function networks

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A Gradient Descent Method for Optimal Batch-to-Batch control of Unknown Linear Systems 3

A Gradient Descent Method for Optimal Batch-to-Batch Control...

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3rd international symposium on Instrumentation, control, Artificial Intelligence, and robotics, ICA-SYMP 2023

作者： Zhou, Yuanqiang Tang, Xiaopeng Gao, Furong Lai, Xin Li, Dewei Ma, Weiguo Hong Kong University of Science and Technology Department of Chemical and Biological Engineering Kowloon Hong Kong School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Nantong University College of Electrical Engineering Nantong Jiangsu226019 China

ISBN: (纸本)9781665473538

This paper discusses optimal batch-to-batch (B2B) control problems and presents a gradient descent method solution for unknown linear batch process systems. Using historical process data, we design a model-free method for B2B optimization that eliminates the need for model information about the system. By using quadratic programming (QP) to formulate the optimal controller design, we first present the optimal iterative learning control (ILC) results. Next, using the gradient descent method, we replace the uncertain term with the actual measurements and develop a new ILC approach based on convex hull representations of uncertain realizations. As compared to the norm-optimal ILC, our proposed ILC can guarantee superior performance with reasonably selected parameters. Finally, we demonstrate our design with an illustrative numerical example. © 2023 IEEE.

关键词： Process control

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Device optimized simulation for Silicon-Based MEMS Piezoresistive Pressure Sensors 3

Device optimized simulation for Silicon-Based MEMS Piezoresi...

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3rd international symposium on Sensor Technology and control, ISSTC 2024

作者： Guo, Junwei Lv, Siyuan Zhang, Chen Duanmu, Zheng Gong, Xiaofeng Wan, Caixin Zhao, Chenglong School of Instrument Science and Opto-Electronics Engineering Beijing Information Science and Technology University Beijing China Wuxi Willmems Semiconductor Co. Ltd. Wuxi China

ISBN: (纸本)9798331541637

In this research, we have developed a comprehensive simulation project that integrates force-electric coupling to examine the impact of multiple variables on MEMS pressure sensor performance. The project's distinctive feature is its ability to automatically process various input parameters within a specified tolerance range, swiftly displaying post-processing results that aid in structural optimization. Based on the outcomes of our simulations, we developed a piezoresistive sensor featuring a membrane that measures 200 μ m × 200 μ m × 3 μ m and piezoresistors sized 24 μ m × 5 μ m. The designed sensor demonstrates a sensitivity of 0.494 mV kPa and a non-linearity of 0.0039% FS. The simulated sensitivity result is coordinated with the experimental device outputs and the non-linearity result is much better than the device. After post optimization, the device's sensitivity is enhanced by 13.3%. This simulation study stands as a testament to the potential of simulation in advancing MEMS technology, paving the way for more sophisticated and efficient sensor designs. © 2024 IEEE.

关键词： Structural optimization

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Challenges in using NVIDIA Jetson Nano board for an Autonomous Underwater Vehicle 3

Challenges in using NVIDIA Jetson Nano board for an Autonomo...

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3rd IEEE international Conference on robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Roy, Arindom Sarkar, Arnob Paul, Bidyut Kanti Krishna Roy, Binoy National Institute of Technology Silchar Department of Electrical Engineering Assam 788010 India

ISBN: (纸本)9798331534400

The development of autonomous underwater vehicles presents unique challenges, particularly in integrating and operating various sensors and control mechanisms. This paper focuses on the challenges of using the NVIDIA Jetson Nano platform to implement an autonomous underwater vehicle for pisciculture. There are many reported papers on AUVs using the NVIDIA Jetson Nano platform. However, these papers do not disclose the challenges generally faced by the new builders of AUVs. This paper presents the initial setup of the Jetson Nano, including installing essential software packages and configuring the Python environment for AUV communication. The details of physical connections of various components with the Jetson Nano board and testing procedures of various sensors like pH, turbidity, pressure, and dissolved oxygen. Also, the connection and control of T200 thrusters and a camera. Challenges encountered during the initialization and setup processes and solutions derived from extensive troubleshooting are discussed. Our findings provide a comprehensive guideline for future developers working with an NVIDIA Jetson Nano board. The successful integration and testing of the components on the NVIDIA Jetson Nano demonstrate its viability for controlling and managing the autonomous underwater vehicle effectively. © 2024 IEEE.

关键词： Dissolved oxygen sensors

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A Self-Aware Robotic Machining Architecture Based on Physics-Informed Neural Networks 3

A Self-Aware Robotic Machining Architecture Based on Physics...

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3rd international Conference on Mechatronics, control and robotics, ICMCR 2025

作者： Zhang, Yuanhui Wang, Mingfeng Wu, Kai South China University of Technology Shien-Ming Wu School of Intelligent Engineering Guangzhou China Engineering Brunel University Department of Mechanical and Aerospace London United Kingdom

ISBN: (纸本)9798331544546

Industrial robots have been widely used in various industrial scenarios due to their flexibility and expandability. However, robots are susceptible to instability at high speeds and load conditions due to their low stiffness and dynamic characteristics variation with posture. Enhancing the processing stability of industrial robots through data-driven modeling and physical modeling approaches suffers from different drawbacks, such as solution complexity and weak interpretability. With the emergence of physics-informed neural networks (PINNs), new methodologies can be developed to enhance the self-aware processing of robots. In this paper, typical industry application scenarios and dynamics of robotics as well as PINNs are introduced and analyzed, and a framework and method based on PINNs are proposed to enhance the self-aware operation of industrial robots. This framework and methodology contribute to the researcher's efforts to apply PINNs more intensively to robot operation in the future to improve the stability and intelligence of robot operation. © 2025 IEEE.

关键词： Industrial robots

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Base Long-short Term Memory Network and Proportional Integral Derivative control on machine arm 3

Base Long-short Term Memory Network and Proportional Integra...

引用

3rd international symposium on Computer Applications and Information Systems, ISCAIS 2024

作者： Chen, Jinhuang Liu, Yifeng Chen, Zhaoqi Liang, Jianwen Tu, Peiqi Zhang, Jinzong Guangzhou Xinhua University Guangzhou510000 China

ISBN: (纸本)9781510681316

To achieve high-precision control at a lower cost, researchers propose combining the traditional machine arm method with new hardware, Long-short Term Memory (LSTM) Network, and Proportional Integral Derivative (PID) control. The machine arm method provides reliable control but lacks precision. LSTM Networks capture long-term dependencies, improving accuracy. PID control continuously adjusts control signals for stability. This integrated approach offers a cost-effective solution for industries seeking precise control. © 2024 SPIE.

关键词： Long short-term memory

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Care Guard: Holistic Health Monitoring and Autonomous Care System 3

Care Guard: Holistic Health Monitoring and Autonomous Care S...

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3rd international Conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Deepthi, J. Dharani, N.P. Aswini, Somu Priya, Desingh Geetha Harsha, Kurra Mani Bhargav, Yandamuri Sri Surya Siva Sree Vidyanikethan Engineering College Electronics and Instrumentation Engineering Tirupati India Electronics and Communication Engineering Tirupati India

ISBN: (纸本)9798350375190

Care Guard: Holistic Health Monitoring and Autonomous Care System outlines a comprehensive system integrating various sensors, microcontrollers, and communication technologies to monitor health parameters and provide assistance. The system employs a 12V battery for energy supply and incorporates components for instance, a temperature sensor, pulse oximeter, RFID, touch sensor, Arduino MCU, air quality sensor, LCD (16x2 lines), motor drivers M1 and M2, WiFi, and IoT. The project aims to enhance healthcare by leveraging IoT and robotics technologies to create an intelligent health monitoring and assistance system. The system continuously monitors vital health parameters such as temperature and pulse oximetry, providing real-time data comment addressed for users via the LCD. Additionally, it utilizes RFID technology for patient identification and touch sensors for user interaction. Furthermore, the method incorporates an automatic nurse assistant robot, which utilizes motor drivers for locomotion and navigation. The robot assists users by providing reminders for medication intake, scheduling appointments, and offering guidance on health-related queries. The incorporation of WiFi and IoT enables remote monitoring and control of the system, allowing healthcare professionals to access patient data and provide timely assistance from anywhere. Overall, this project presents a comprehensive solution for health tracking and assistance, leveraging IoT, robotics, and sensor technologies to improve healthcare accessibility and quality. © 2024 IEEE.

关键词： Temperature sensors

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Research on control of Micro Turbojet Engine Based on All-Coefficient Adaptive control 3

Research on Control of Micro Turbojet Engine Based on All-Co...

引用

3rd international symposium on Aerospace engineering and Systems, ISAES 2024

作者： Zhang, Jiahui Liang, Shuang Guo, Mingming Wang, Heng Du, Xingmao Zhang, Hua Song, Wenyan School of Information Engineering Southwest University of Science and Technology Swust Mianyang China School of Power and Energy Northwestern Polytechnical University Npu Xi'an China

ISBN: (纸本)9798350350418

Aiming at the problem that the 150kg thrust stage micro turbojet engine has strong nonlinearity in the starting, acceleration and deceleration process under complex environment, is susceptible to external interference, and too long operation time leads to component aging and system time-varying. An all-coefficient adaptive control (ACAC) method based on characteristic model is proposed. It avoids the defect that the traditional proportional-integral-derivative (PID) controller cannot adjust adaptively when facing the nonlinear time-varying system. Firstly, based on the ground test data of the micro turbojet engine, a simple empirical mathematical model (including the rotational speed model and thrust model) is established by using deep neural network method, and the accuracy of the model can reach 96.8%. Secondly, the control effect of ACAC algorithm and PID control algorithm on thrust is compared by simulation. The results show that the adjustment time of ACAC control algorithm is 0.05 s and 0.04s higher than that of PID when the system has disturbance and the system gain changes. It is verified that the method has better rapidity and strong anti-disturbance ability, which provides important engineering value for the selection of control strategies to improve the acceleration and deceleration characteristics of micro turbojet engines with large thrust level. © 2024 IEEE.

关键词： Deep neural networks

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A New control Strategy for Improving the Voltage Quality of Inverter Grid Connected System 3

A New Control Strategy for Improving the Voltage Quality of ...

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3rd international symposium on Semiconductor and Electronic Technology, ISSET 2024

作者： Li, Zhuoting Yu, Shaojuan Liu, Liqun School of Electronic and Information Engineering Taiyuan University of Science and Technology Shanxi Province Taiyuan China

ISBN: (纸本)9798350390285

A Bayesian regularization neural network control strategy has been proposed to address the impact of changes in grid impedance on the output voltage amplitude and frequency of inverter grid connected systems, given an ideal SVPWM input voltage. The LCL type three-phase inverter grid connected system model has been built in the first step, and it has been demonstrated that a given ideal SVPWM input voltage can eliminate the influence of grid impedance changes on the common coupling point (PCC) voltage frequency of the grid connected system. Based on this, the duty cycle of the buck boost converter has been predicted through a neural network to adapt to changes in grid impedance, and direct voltage control has been achieved. Then, the performance function of the Bayesian regularization neural network has been elaborated, and the control performance of the neural network has been verified. Finally, a traditional resonant damping control system was constructed, and the performance of the proposed control strategy and traditional resonant damping control method was compared through Simulink simulation results. The experimental results show that the proposed control strategy can avoid the impact of grid impedance changes on the output voltage quality of PCC points, and expand the adaptability range of inverter grid connected systems to grid impedance changes. © 2024 IEEE.

关键词： Buck-Boost converter

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Ultra-Sensitive Anti-Parity-Time-Symmetric Wireless Sensor Based on Unidirectional Couplings 3

Ultra-Sensitive Anti-Parity-Time-Symmetric Wireless Sensor B...

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3rd international symposium on Sensor Technology and control, ISSTC 2024

作者： Xu, Fei Ding, Chen Wu, Pengde Cheng, Yuhua Hangzhou Dianzi University MOE Engineering Research Center of Smart Microsensors and Microsystems Hangzhou China

ISBN: (纸本)9798331541637

The coupled LC resonators satisfying parity-time (PT) symmetry or anti-PT (APT) symmetry can be utilized as highly sensitive sensors if calibrating them at exceptional points (EPs) in advance. In practice, however, the existing VNA-free and wireless PT- and APT-symmetric systems are restricted by the vague EP position and the requirement of imaginary-value couplings, respectively. These issues are addressed by the proposed novel APT-symmetric wireless sensor, constructed by four coupled LC resonators. A pair of unidirectional and opposite real-value couplings is implemented to achieve the wireless sensing functionality. The property of different numbers of operating frequencies at the APT-symmetric and -broken states is utilized to calibrate the system at the EP. The time-domain working mode avoids using VNAs to sweep the frequency. The system behavior is analytically analyzed and validated through simulations. The simulated results show that the frequency deviation response to the resonant frequency perturbation (ω) features an ultra-high sensitivity, ∼|ω|0.5. © 2024 IEEE.

关键词： Natural frequencies

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