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sensorless Control of PMSM using SMC and sensor Fault Detection Observer 18

Sensorless Control of PMSM using SMC and Sensor Fault Detect...

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18th International Multi-conference on systems, Signals & Devices (SSD)

作者： Nicola, Marcel Nicola, Claudiu-Ionel Natl Inst Res Dev & Testing Elect Engn Res & Dev Dept Craiova Romania Univ Craiova Dept Automat Control & Elect Craiova Romania

ISBN: (纸本)9781665414937

In this article is presented a type of sensorless control system for a PMSM using a Sliding Mode Control (SMC) type controller, which replaces the PI-type controller of a PMSM rotor speed control loop, and the speed is estimated using a Sliding Mode Observer (SMO) type observer. For the detection of the faults from power supply lines given by current sensors of the PMSM, the Fault Detection Observer (FDO) type observer is used. the equations of the SMC-type controller, of the SMO-type observer, and of the fault detection observer, as well as their implementation in Matlab/Simulink graphical programming environment are presented in this article. Following the numerical simulations, the special performances of the SMC-type controller are presented, but also as compared to the PI speed controller in the classic Field Oriented Control (FOC) type structure. the FDO-type observer has a good response time and works with good results even under the conditions where uniformly distributed disturbances act on the system. the future papers will approach the methods of implementation in real time in embedded system of the SMC control and of the described observers.

关键词： permanent magnet motors sliding mode control fault detection motor drives automatic control

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Visual and inertial sensor fusion for mobile X-ray detector tracking: Demo abstract 20

Visual and inertial sensor fusion for mobile X-ray detector ...

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18th ACM conference on embedded networked sensor systems, SenSys 2020

作者： Zhao, Yang Tkaczyk, Eric Pan, Feng Ge Research NiskayunaNY United States Spark Insights BostonMA United States

ISBN: (纸本)9781450375900

Robust 3D pose tracking of an object is a critical technique for various mobile sensing applications. Computer vision-based pose tracking method provides a cost-effective solution, but it is sensitive to occlusion and illumination change issues. In this work, we propose a novel visual-inertial sensor fusion framework and demonstrate the real-time implementation of a tightly-coupled sensor fusion algorithm: inertial perspective-n-point (IPNP) algorithm. With measurements from an inertial measurement unit (IMU), the prototype system only needs to detect two keypoints to track all six degrees of freedom of a planar object, e.g., a mobile X-ray detector, a 50% reduction on required number of keypoints, compared with the vision-based perspective-n-point algorithm. © 2020 ACM.

关键词： Cost effectiveness

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Resource Allocation for Reliable Transmission in IRS-Assisted Industrial Wireless sensor Networks 18th

Resource Allocation for Reliable Transmission in IRS-Assis...

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18th China conference on Wireless sensor Networks, CWSN 2024

作者： Wang, Chuqing Zheng, Meng Liang, Wei Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789819621880

Intelligent Reflecting Surface (IRS) is one of the promising technologies for improving transmission reliability of Industrial Wireless sensor Networks (IWSNs) by creating a virtual line-of-sight (LoS) link to bypass obstacles between transceivers. In this paper, we consider an IRS-assisted IWSN and propose a resource allocation method for reliable transmission in the IRS-assisted IWSN. First, a transmission reliability optimization problem in terms of the reflective beamforming at the IRS and the timeslot and power allocated to sensors is formulated. Second, the formulated optimization problem is transformed into an equivalent but simplified problem. In subsequent, a particle swarm optimization based method is utilized to obtain a near-optimal solution. Simulation results demonstrate that this work yields higher transmission reliabilities than existing benchmark schemes. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Particle swarm optimization (PSO)

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Magnetic sensor based indoor positioning by multi-channel deep regression: Poster abstract 20

Magnetic sensor based indoor positioning by multi-channel de...

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18th ACM conference on embedded networked sensor systems, SenSys 2020

作者： Antsfeld, Leonid Chidlovskii, Boris Borisov, Dmitrii Naver Labs Europe France Grenoble Alpes University France

ISBN: (纸本)9781450375900

Modern smartphones are equipped with built-in magnetometers that capture disturbances of the Earth's magnetic field induced by ferromagnetic objects. In indoor environment, using magnetic field data turns to be a strong alternative to conventional localization techniques as requiring no special infrastructure. We revise the state of the art methods based on landmark classification [5] and propose a novel approach. We represent magnetic data time series as image sequences and compose multi-channel input to a deep neural network. We use four methods, Recurrence plots, Gramian Angular Fields and Markov Transition Fields, to capture different patterns in magnetic data stream. We complete the landmark-based classification with deep regression on the user's position and combine convolutional and recurrent layers in the deep network. We evaluate our methods on the recently published MagPie dataset [3] and show that they outperform the state of the art methods. © 2020 ACM.

关键词： Indoor positioning systems

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Towards the Plant-Based sensor: Agricultural Energy Harvesting and Sensing Experiments 22

Towards the Plant-Based Sensor: Agricultural Energy Harvesti...

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Proceedings of the 20th ACM conference on embedded networked sensor systems

作者： Tyler Luong Stewart J. thomas Bucknell University

ISBN: (纸本)9781450398862

With an ongoing search for alternative energy sources, plants may serve as a viable means for operating low-power digital circuits. Biopotential, the electrical signals found within the body due to electrochemical activity, can be monitored and harnessed within plants and vegetables. Measuring plant biopotential, in combination with electrogenic microbial fuel cell (MFC) technology [14], suggests that a self-sufficient and micro-power generation system can be made using a microbial fuel cell in tandem with a living plant [18]. this research presents ongoing work in proposed sub-systems within this power generation system and their compatibility with low-power electronics, a project inspired from works focused on converting plants into batteries [7, 8]. the power harvesting aspect of the project consists of long deployment experiments with mud based MFCs using MudWatt kits, as well as a plant based MFC. the plant sensing aspect of the project is depending on thigmonastic reactions from the plant specie Mimosa pudica.

关键词： bioelectricity energy harvesting plant monitoring

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Exploring effectiveness of a predictive light control mechanism for wireless sensor networks: Poster abstract 20

Exploring effectiveness of a predictive light control mechan...

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18th ACM conference on embedded networked sensor systems, SenSys 2020

作者： Takayama, Yuki Yokota, Yusuke Japan Women's University Graduate School of Science Tokyo Japan Japan Women's University Faculty of Science Tokyo Japan

ISBN: (纸本)9781450375900

Light management for buildings or streets is important for safety, security and comfort. However, it is not economical to keep the lights on in places without people. Although there is a lighting system with power-saving feature that lights up automatically when it detects moving objects, it has a problem that it does not light up unless the objects approach the immediate vicinity of the lights. In this work, we aim to realize the system that collects motion detection data of objects using a wireless sensor network, predicts the approach of a person from a position farther than before, and appropriately controls lighting on / off. In this system, data is exchanged between neighboring nodes, and each node autonomously judges lighting control. We discussed a predictive control method and made experiments for an adequacy confirmation. First, we constructed a system to verify the predictive control method and made a data acquisition experiment using PIR motion sensors. Next, we examined methods for a movement prediction and lighting control based on the acquired data, and confirmed that control results provide sufficient utility. © 2020 ACM.

关键词： sensor nodes

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Fishing activity sensing and visualization system using sensor-equipped fishing rod: Demo abstract 20

Fishing activity sensing and visualization system using sens...

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18th ACM conference on embedded networked sensor systems, SenSys 2020

作者： Fukuda, Shuichi Choi, Hyuckjin Matsuda, Yuki Yasumoto, Keiichi Nara Institute of Science and Technology Ikoma Nara Japan

ISBN: (纸本)9781450375900

In recent years, many studies and development of Cyber Physical systems (CPS) have been carried out to feed back analysis results to human users in a physical space by using machine learning, aiming to analyze a huge amount of information obtained from physical space in a cyber space. To apply CPS to sports, a lot of studies have been conducted on sensing and recognizing actions and movements of athletes using machine learning. In this study, we focus on fishing as a sport, and propose a fishing CPS that recognizes anglers' actions in real-time and provides information on the past useful actions that are linked to fishing results depending on time and place as a decision support when the anglers do not make catch. In addition, this paper reports on the development of an IoT (Internet of things) device that acquires positional information, acceleration and gyroscope information, and a web system that displays results of real-time activity recognition along with the place and time by animation for realizing the fishing CPS. We have evaluated the developed IoT device and web system from the viewpoint of practical use. As a result, we have confirmed that the GPS and acceleration sensors, in the actual breakwater environment, were constantly transmitting data to a server via UDP communication for 4 hours and 40 minutes. © 2020 ACM.

关键词： Internet of things

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LidarPhone: Acoustic eavesdropping using a lidar sensor: Poster abstract 20

LidarPhone: Acoustic eavesdropping using a lidar sensor: Pos...

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18th ACM conference on embedded networked sensor systems, SenSys 2020

作者： Sami, Sriram Tan, Sean Rui Xiang Dai, Yimin Roy, Nirupam Han, Jun National University of Singapore Singapore University of Maryland College Park United States

ISBN: (纸本)9781450375900

Private conversations are an attractive target for malicious actors intending to conduct audio eavesdropping attacks. Previous works discovered unexpected vectors for these attacks, such as analyzing high-speed video of objects adjacent to sound sources, or using WiFi signal information. We propose LidarPhone, a novel side-channel attack that exploits the lidar sensors in commodity robot vacuum cleaners to perform acoustic eavesdropping attacks. LidarPhone is able to detect the minute vibrations induced on objects that are near audio sources, and extract meaningful signals from inherently noisy raw lidar returns. We evaluate a realistic scenario for potential victims: recovering privacy-sensitive digits (e.g., credit card numbers, social security numbers) emitted by computer speakers during teleconferencing calls. We implement LidarPhone on a Xiaomi Roborock vacuum cleaning robot and perform a comprehensive series of real-world experiments to determine its performance. LidarPhone achieves up to 91% accuracy for digit classification. © 2020 ACM.

关键词： Security systems

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Design of Temperature Monitoring System Using Distributed Intelligent CAN Bus Networks 8th

Design of Temperature Monitoring System Using Distributed In...

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8th International conference on Artificial Intelligence and Security (ICAIS)

作者： Su, Yu Hou, Lingjuan Li, Sinan Jiang, Zhaochang China Elect Technol Grp Corp Res Inst 54 Shijiazhuang 050081 Hebei Peoples R China Tianjin Normal Univ Sch Management Tianjin 300387 Peoples R China Sehan Univ Grad Sch Mokpo 58613 South Korea

ISBN: (纸本)9783031067945;9783031067938

Temperature sensing and control remain challenges since temperature is a critical index of the increasingly growing in agriculture and smart planting. CAN (Controller Area Network) bus, due to its high stability, anti-interference ability, timeliness, adaptability to complex industrial environment, good performance, it has been widely used industrial communication among networked instrument. In this project a STC89C52 microcontroller is selected as the master chip, using as an independent CAN controller SJA1000, PCA82C250 as the CAN bus driver to achieve CAN bus communication, designed and implemented based on CAN bus network multi-node temperature monitoring system, including the master node controller, from the node controller and PC server-side procedures. the system in real time from a node can collect temperature sensor DS18B20 temperature signal transmitted via the CAN controller SJA1000 CAN controller to the receiver, and then before sending the master node, the master node receives the signal can be displayed on the LCD screen, you can also via RS-232 bus serial transmission to the host computer program computer display, the other computer can also send commands through the host computer to control the master/slave node, enabling on-line monitoring distributed CAN bus network in site-specific farming.

关键词： Controller Area Network bus (CAN-bus) Temperature sensor Temperature measurement and conditioning Fieldbus embedded systems (ES)

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ePerceptive-Energy Reactive embedded Intelligence for Batteryless sensors 20

ePerceptive-Energy Reactive Embedded Intelligence for Batter...

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18th conference on embedded networked sensor systems

作者： Montanari, Alessandro Sharma, Manuja Jenkus, Dainius Alloulah, Mohammed Qendro, Lorena Kawsar, Fahim Nokia Bell Labs Cambridge England Univ Washington Seattle WA 98195 USA Newcastle Univ Newcastle Upon Tyne Tyne & Wear England Univ Cambridge Cambridge England Delft Univ Technol Delft Netherlands Nokia Bell Labs Cambridge Pervas Syst Dept Cambridge England

ISBN: (纸本)9781450375900

For long, we have studied tiny energy harvesters to liberate sensors from batteries. With remarkable progress in embedded deep learning, we are now re-imagining these sensors as intelligent compute nodes. Naturally, we are approaching a crossroad where sensor intelligence is meeting energy autonomy enabling maintenance-free swarm intelligence and unleashing a plethora of applications ranging from precision agriculture to ubiquitous asset tracking to infrastructure monitoring. One of the critical challenges, however, is to adapt intelligence fidelity in response to available energy to maximise the overall system availability. To this end, we present the design and implementation of ePerceptive: a novel framework for best-effort embedded intelligence, i.e., inference fidelity varies in proportion to the instantaneous energy supplied. ePerceptive operates on two core principles. First, it enables training a single deep neural network (DNN) to operate on multiple input resolutions without compromising accuracy or incurring memory overhead. Second, it modifies a DNN architecture by injecting multiple exits to guarantee valid, albeit lower-fidelity inferences in the event of energy interruption. the combination of these techniques offers a smooth adaptation between inference latency and recognition accuracy while matching the computational load to the available power budget. We report the manifestation of ePerceptive in designing batteryless cameras and microphones built with TI MSP430 MCU and off-the-shelf RF and solar energy harvesters. Our evaluation of these batteryless sensors with multiple vision and acoustic workloads suggest that the dynamic adaptation of ePerceptive can increase the inference throughput by up to 80% compared to a static baseline while ensuring a maximum accuracy drop of less than 6%.

关键词： Energy autonomous embedded intelligence batteryless devices

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