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Journal articles on the topic 'Distributed Sensing and Control'

Author: Grafiati

Published: 4 June 2021

Last updated: 21 February 2023

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1

Henderson, Tom, Chuck Hansen, and Bir Bhanu. "The specification of distributed sensing and control." Journal of Robotic Systems 2, no. 4 (1985): 387–96. http://dx.doi.org/10.1002/rob.4620020405.

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2

Yuksel, S., and S. Tatikonda. "A Counterexample in Distributed Optimal Sensing and Control." IEEE Transactions on Automatic Control 54, no. 4 (2009): 841–44. http://dx.doi.org/10.1109/tac.2008.2009680.

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3

Tang, Yujie, Vikram Ramanathan, Junshan Zhang, and Na Li. "Communication-Efficient Distributed SGD With Compressed Sensing." IEEE Control Systems Letters 6 (2022): 2054–59. http://dx.doi.org/10.1109/lcsys.2021.3137859.

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4

ZHANG, WEIJIAN. "Gain of optical distributed sensing in distributed parameter systems." International Journal of Systems Science 22, no. 12 (1991): 2521–40. http://dx.doi.org/10.1080/00207729108910811.

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5

Martin, Jeffrey W., Tammy D. Henson, Joseph C. Wehlburg, James M. Redmond, Patrick S. Barney, and John A. Main. "Distributed Sensing and Shape Control of Piezoelectric Bimorph Mirrors." Journal of Intelligent Materials Systems and Structures 11, no. 10 (2000): 744–57. http://dx.doi.org/10.1177/104538900772663784.

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6

Ningxu Cai, M. Gholami, Litao Yang, and R. W. Brennan. "Application-Oriented Intelligent Middleware for Distributed Sensing and Control." IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 42, no. 6 (2012): 947–56. http://dx.doi.org/10.1109/tsmcc.2011.2174982.

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7

Panagou, Dimitra, Dusan M. Stipanovic, and Petros G. Voulgaris. "Distributed Dynamic Coverage and Avoidance Control Under Anisotropic Sensing." IEEE Transactions on Control of Network Systems 4, no. 4 (2017): 850–62. http://dx.doi.org/10.1109/tcns.2016.2576403.

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8

Martin, Jeffrey W., James M. Redmond, Patrick S. Barney, Tammy D. Henson, Joseph C. Wehlburg, and John A. Main. "Distributed Sensing and Shape Control of Piezoelectric Bimorph Mirrors." Journal of Intelligent Material Systems and Structures 11, no. 10 (2000): 744–57. http://dx.doi.org/10.1106/2ulx-mnqh-y1af-8b5v.

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9

Choi, Jinho. "Data-Aided Sensing for Distributed Detection." IEEE Wireless Communications Letters 10, no. 5 (2021): 1138–41. http://dx.doi.org/10.1109/lwc.2021.3064690.

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10

Tzou, H. S. "Integrated distributed sensing and active vibration suppression of flexible manipulators using distributed piezoelectrics." Journal of Robotic Systems 6, no. 6 (1989): 745–67. http://dx.doi.org/10.1002/rob.4620060606.

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11

Papatheodorou, Sotiris, Anthony Tzes, Konstantinos Giannousakis, and Yiannis Stergiopoulos. "Distributed area coverage control with imprecise robot localization." International Journal of Advanced Robotic Systems 15, no. 5 (2018): 172988141879749. http://dx.doi.org/10.1177/1729881418797494.

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This article examines the static area coverage problem by a network of mobile, sensor-equipped agents with imprecise localization. Each agent has uniform radial sensing ability and is governed by first-order kinodynamics. To partition the region of interest, a novel partitioning scheme, the Additively Weighted Guaranteed Voronoi diagram is introduced which takes into account both the agents’ positioning uncertainty and their heterogeneous sensing performance. Each agent’s region of responsibility corresponds to its Additively Weighted Guaranteed Voronoi cell, bounded by hyperbolic arcs. An app

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12

Bullock, Darcy, Chris Schwehm, and John Broemmelsiek. "Distributed Sensing and Control Technology for Intelligent Civil Infrastructure Systems." Computer-Aided Civil and Infrastructure Engineering 11, no. 2 (1996): 77–86. http://dx.doi.org/10.1111/j.1467-8667.1996.tb00312.x.

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13

Liu, Guangjun, Sajan Abdul, and Andrew A. Goldenberg. "Distributed control of modular and reconfigurable robot with torque sensing." Robotica 26, no. 1 (2008): 75–84. http://dx.doi.org/10.1017/s0263574707003608.

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SUMMARYA major technical challenge in controlling modular and reconfigurable robots is associated with the kinematics and dynamic model uncertainties caused by reconfiguration. In parallel, conventional model uncertainties such as uncompensated joint friction still persist. This paper presents a modular distributed control technique for modular and reconfigurable robots that can instantly adapt to robot reconfigurations. Under the proposed control method that is based on joint torque sensing, a modular and reconfigurable robot is stabilized joint by joint, and modules can be added or removed w

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14

Mallory, K., M. A. Hsieh, E. Forgoston, and I. B. Schwartz. "Distributed allocation of mobile sensing swarms in gyre flows." Nonlinear Processes in Geophysics 20, no. 5 (2013): 657–68. http://dx.doi.org/10.5194/npg-20-657-2013.

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Abstract. We address the synthesis of distributed control policies to enable a swarm of homogeneous mobile sensors to maintain a desired spatial distribution in a geophysical flow environment, or workspace. In this article, we assume the mobile sensors (or robots) have a "map" of the environment denoting the locations of the Lagrangian coherent structures or LCS boundaries. Using this information, we design agent-level hybrid control policies that leverage the surrounding fluid dynamics and inherent environmental noise to enable the team to maintain a desired distribution in the workspace. We

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15

Ding, Y., E. A. Elsayed, S. Kumara, J. C. Lu, F. Niu, and J. Shi. "Distributed Sensing for Quality and Productivity Improvements." IEEE Transactions on Automation Science and Engineering 3, no. 4 (2006): 344–59. http://dx.doi.org/10.1109/tase.2006.876610.

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16

Tzou, H. S., and R. Ye. "Piezothermoelasticity and Precision Control of Piezoelectric Systems: Theory and Finite Element Analysis." Journal of Vibration and Acoustics 116, no. 4 (1994): 489–95. http://dx.doi.org/10.1115/1.2930454.

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Piezothermoelastic effects of distributed piezoelectric sensor/actuator and structural systems are studied. Distributed controls (static and dynamic) of piezoelectric laminates subjected to a steady-state temperature field are investigated. Piezothermoelastic constitutive equations are defined, followed by three energy functionals for the displacement, electric, and temperature fields, respectively. A new 3-D piezothermoelastic thin hexahedron finite element with three internal degrees of freedom is formulated using a variational formulation which includes thermal, electric, and mechanical ene

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17

Ellmauthaler, Andreas, Brian C. Seabrook, Glenn A. Wilson, et al. "Distributed acoustic sensing of subsea wells." Leading Edge 39, no. 11 (2020): 801–7. http://dx.doi.org/10.1190/tle39110801.1.

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Topside distributed acoustic sensing (DAS) of subsea wells requires advanced optical engineering solutions to compensate for reduced acoustic bandwidth, optical losses, and back reflections that are accumulated through umbilicals, multiple wet- and dry-mate optical connectors, splices, optical feedthrough systems, and downhole fibers. To address these issues, we introduce a novel DAS solution based on subsea fiber topology consisting of two transmission fibers from topside and an optical circulator deployed in the optical flying lead at the subsea tree. This solution limits the sensing fiber p

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18

Abbracciavento, Francesco, Simone Formentin, Jacopo Balocco, Andrea Rota, Vincenzo Manzoni, and Sergio M. Savaresi. "Anomaly detection via distributed sensing: a VAR modeling approach." IFAC-PapersOnLine 54, no. 7 (2021): 85–90. http://dx.doi.org/10.1016/j.ifacol.2021.08.339.

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19

FANG Yuan-kun, 方元坤, 袁斌文 YUAN Bin-wen, 孟子阳 MENG Zi-yang, 尤. 政. YOU Zheng, and 张高飞 ZHANG Gao-fei. "Attitude control in multi-satellite cooperative observations for distributed remote sensing." Optics and Precision Engineering 27, no. 1 (2019): 58–68. http://dx.doi.org/10.3788/ope.20192701.0058.

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20

Sarlette, Alain, and Rodolphe J. Sepulchre. "Control limitations from distributed sensing: Theory and Extremely Large Telescope application." Automatica 50, no. 2 (2014): 421–30. http://dx.doi.org/10.1016/j.automatica.2013.12.014.

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21

Ouyang, Jianshu, Xianming Chen, Zehua Huangfu, Cheng Lu, Dahai Huang, and Yangbo Li. "Application of distributed temperature sensing for cracking control of mass concrete." Construction and Building Materials 197 (February 2019): 778–91. http://dx.doi.org/10.1016/j.conbuildmat.2018.11.221.

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22

Shih, Hui-Ru. "Distributed vibration sensing and control of a piezoelectric laminated curved beam." Smart Materials and Structures 9, no. 6 (2000): 761–66. http://dx.doi.org/10.1088/0964-1726/9/6/304.

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23

Morye, Akshay A., Chong Ding, Amit K. Roy-Chowdhury, and Jay A. Farrell. "Distributed Constrained Optimization for Bayesian Opportunistic Visual Sensing." IEEE Transactions on Control Systems Technology 22, no. 6 (2014): 2302–18. http://dx.doi.org/10.1109/tcst.2014.2300416.

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24

Taira, Tetsuya, and Nobuyuki Yamasaki. "Functionally Distributed Control Architecture for Autonomous Mobile Robots." Journal of Robotics and Mechatronics 16, no. 2 (2004): 217–24. http://dx.doi.org/10.20965/jrm.2004.p0217.

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This paper explains the design and implementation of functionally distributed control architecture that realizes real-time control of autonomous mobile robots. To operate successfully in human society, autonomous mobile robots must achieve both local and global control in real-time. We focus on robots operating in parallel, such as moving while sensing, and propose a functionally distributed control architecture designed as a parallel/distributed computer consisting of many functionally distributed modules. Each module has an exclusive Processing Unit (PU) that processes one function of robot,

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25

Yang, B., and C. D. Mote. "Frequency-Domain Vibration Control of Distributed Gyroscopic Systems." Journal of Dynamic Systems, Measurement, and Control 113, no. 1 (1991): 18–25. http://dx.doi.org/10.1115/1.2896350.

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A new method is presented for vibration control of distributed gyroscopic systems. The control is formulated in the Laplace transform domain. The transfer function of a closed-loop system, consisting of the plant, a feedback control law and the dynamics of the sensing and actuation devices, is derived. Stability analyses of the closed-loop system use both the root locus method and the generalized Nyquist criterion. Two stability criteria are obtained. Design of stabilizing controllers is carried out for both colocation and noncolocation of the sensor and actuator. The effects of time-delay and

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26

Kharaz, A., and B. Jones. "A Distributed Fibre Optic Sensing System for Humidity Measurement." Measurement and Control 28, no. 4 (1995): 101–3. http://dx.doi.org/10.1177/002029409502800402.

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27

Rao, S. S., and M. Sunar. "Piezoelectricity and Its Use in Disturbance Sensing and Control of Flexible Structures: A Survey." Applied Mechanics Reviews 47, no. 4 (1994): 113–23. http://dx.doi.org/10.1115/1.3111074.

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Piezoelectric materials are being used at an increasing rate by researchers in the areas of vibration, measurement and control. Due to their distinct features, these materials can be employed in the distributed sensing and control of intelligent structures that have a highly integrated control architecture. By employing piezoelectric materials, it is feasible to achieve an accurate response monitoring and effective control of flexible structures. In this survey paper, the recent research trends addressing piezoelectricity in the context of distributed sensing and control of flexible structures

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28

Franzini, Giovanni, and Mario Innocenti. "Distributed cooperative deployment of heterogeneous autonomous agents: a Pareto suboptimal approach." Robotica 36, no. 12 (2018): 1943–62. http://dx.doi.org/10.1017/s0263574718000814.

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SUMMARYThe paper presents a distributed cooperative control law for autonomous deployment of a team of heterogeneous agents. Deployment problems deal with the coordination of groups of agents in order to cover one or more assigned areas of the operational space. In particular, we consider a team composed by agents with different dynamics, sensing capabilities, and resources available for the deployment. Sensing heterogeneity is addressed by means of the descriptor function framework, an abstraction that provides a set of mathematical tools for describing both agent sensing capabilities and the

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29

Lu, Xin, Peter James Thomas, and Jon Oddvar Hellevang. "A Review of Methods for Fibre-Optic Distributed Chemical Sensing." Sensors 19, no. 13 (2019): 2876. http://dx.doi.org/10.3390/s19132876.

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Chemical sensing is of great importance in many application fields, such as medicine, environmental monitoring, and industrial process control. Distributed fibre-optic sensing received significant attention because of its unique feature to make spatially resolved measurements along the entire fibre. Distributed chemical sensing (DCS) is the combination of these two techniques and offers potential solutions to real-world applications that require spatially dense chemical measurements covering large length scales. This paper presents a review of the working principles, current status, and the em

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30

Rahman, Saifur, Farman Ali, Fazal Muhammad, et al. "Analyzing Distributed Vibrating Sensing Technologies in Optical Meshes." Micromachines 13, no. 1 (2022): 85. http://dx.doi.org/10.3390/mi13010085.

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Hundreds of kilometers of optical fibers are installed for optical meshes (OMs) to transmit data over long distances. The visualization of these deployed optical fibers is a highlighted issue because the conventional procedure can only measure the optical losses. Thus, this paper presents distributed vibration sensing (DVS) estimation mechanisms to visualize the optical fiber behavior installed for OMs which is not possible by conventional measurements. The proposed technique will detect the power of light inside the optical fiber, as well as different physical parameters such as the phase of

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31

Liang, Jing, and Chengchen Mao. "Distributed compressive sensing in heterogeneous sensor network." Signal Processing 126 (September 2016): 96–102. http://dx.doi.org/10.1016/j.sigpro.2015.10.026.

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32

Kan, Zhen, Emily A. Doucette, and Warren E. Dixon. "Distributed Connectivity Preserving Target Tracking With Random Sensing." IEEE Transactions on Automatic Control 64, no. 5 (2019): 2166–73. http://dx.doi.org/10.1109/tac.2018.2867594.

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33

Akbarpour-Kasgari, Abbas, and Mehrdad Ardebilipour. "Massive MIMO-OFDM Channel Estimation via Distributed Compressed Sensing." IEEE Wireless Communications Letters 8, no. 2 (2019): 376–79. http://dx.doi.org/10.1109/lwc.2018.2873339.

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34

Papatheodorou, Sotiris, and Anthony Tzes. "Fault tolerant area coverage control for multiagent systems." MATEC Web of Conferences 188 (2018): 05010. http://dx.doi.org/10.1051/matecconf/201818805010.

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The fault tolerance characteristics of a distributed multi-agent coverage algorithm are examined. A team of sensor-equipped mobile agents is tasked with covering a planar region of interest. A distributed, gradient-based control scheme is utilized for this purpose. The agents are assumed to consist of three subsystems, each one of which may fail. The subsystems under examination are the actuation, sensing and the communication subsystem. Partial and catastrophic faults are examined. Several simulation studies are conducted highlighting the robustness of the distributed nature of the control sc

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35

Haile, Mulugeta A., Nathaniel E. Bordick, and Jaret C. Riddick. "Distributed acoustic emission sensing for large complex air structures." Structural Health Monitoring 17, no. 3 (2017): 624–34. http://dx.doi.org/10.1177/1475921717714614.

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The vast majority of existing work on acoustic emission–based structural health monitoring is for geometrically simple structures with uninterrupted propagation path and constant wave speed. Realistic systems such as a full-scale fuselage, however, are built from interconnected pieces of acoustically mismatched parts such as sandwich core panels, stringer stiffened skin, and fastener holes. The geometric complexity and dynamic operating environment of realistic systems mean that the acoustic emission wave undergoes multiple reflections, refractions, and mode changes resulting in overlapped tra

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36

Denney, Dennis. "Combining Distributed-Temperature Sensing With Inflow-Control Devices for Improved Injection Profile." Journal of Petroleum Technology 62, no. 06 (2010): 79–80. http://dx.doi.org/10.2118/0610-0079-jpt.

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37

KIM, Su Min, and Junsu KIM. "Adaptive Sensing Period Based Distributed Medium Access Control for Cognitive Radio Networks." IEICE Transactions on Communications E97.B, no. 11 (2014): 2502–11. http://dx.doi.org/10.1587/transcom.e97.b.2502.

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38

Zhao, F., C. Bailey-Kellogg, and M. P. J. Fromherz. "Physics-based encapsulation in embedded software for distributed sensing and control applications." Proceedings of the IEEE 91, no. 1 (2003): 40–63. http://dx.doi.org/10.1109/jproc.2002.805819.

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39

Chandiramani, N. K., and S. P. Purohit. "Semi-Active Control Using Magnetorhelogical Dampers with Output Feedback and Distributed Sensing." Shock and Vibration 19, no. 6 (2012): 1427–43. http://dx.doi.org/10.1155/2012/838140.

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Control of seismic response of a building fitted with magnetorheological dampers is considered using Optimal Static Output Feedback (OSOF) for desired damper forces. The Modified Bouc-Wen damper model is used and two control voltage laws based on the MR constraint filter, i.e., Semi-inverse Quadratic Voltage Law and Semi-inverse On-Off Voltage Law, are proposed. These appear to perform at least as well as an existing Clipped Voltage Law. Comparisons with available results from a robust reliability-based controller show OSOF control to be quite effective. Controlled response using OSOF is compa

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40

Ilic, Marija D., Le Xie, Usman A. Khan, and José M. F. Moura. "Modeling of Future Cyber–Physical Energy Systems for Distributed Sensing and Control." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 40, no. 4 (2010): 825–38. http://dx.doi.org/10.1109/tsmca.2010.2048026.

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41

Krieg, Michael, Kevin Nelson, and Kamran Mohseni. "Distributed sensing for fluid disturbance compensation and motion control of intelligent robots." Nature Machine Intelligence 1, no. 5 (2019): 216–24. http://dx.doi.org/10.1038/s42256-019-0044-1.

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42

SAKURAI, Hiroshi, and Yasuhiko HANGAI. "SENSING AND VIBRATION CONTROL OF PIEZOELECTRIC SHELLS : Segmented distributed sensors and actuators." Journal of Structural and Construction Engineering (Transactions of AIJ) 63, no. 504 (1998): 65–72. http://dx.doi.org/10.3130/aijs.63.65_1.

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43

Caicedo, David, and Ashish Pandharipande. "Distributed Illumination Control With Local Sensing and Actuation in Networked Lighting Systems." IEEE Sensors Journal 13, no. 3 (2013): 1092–104. http://dx.doi.org/10.1109/jsen.2012.2228850.

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44

Chang, Bao Rong, Hsiu-Fen Tsai, Jyong-Lin Lyu, and Chien-Feng Huang. "Distributed sensing units deploying on group unmanned vehicles." International Journal of Distributed Sensor Networks 17, no. 7 (2021): 155014772110368. http://dx.doi.org/10.1177/15501477211036877.

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This study aims to use two unmanned vehicles (aerial vehicles and ground vehicles) to implement multi-machine cooperation to complete the assigned tasks quickly. Unmanned aerial/ground vehicles can call each other to send instant inquiry messages using the proposed cooperative communication protocol to hand over the tasks between them and execute efficient three-dimensional collaborative operations in time. This study has demonstrated integrating unmanned aerial/ground vehicles into a group through the control platform (i.e. App operation interface) that uses the Internet of Things. Therefore,

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45

Sunar, M., and S. S. Rao. "Recent Advances in Sensing and Control of Flexible Structures Via Piezoelectric Materials Technology." Applied Mechanics Reviews 52, no. 1 (1999): 1–16. http://dx.doi.org/10.1115/1.3098923.

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Due to their special characteristics, piezoelectric materials can be used in distributed behavior sensing and control of flexible structures. These materials are usually incorporated with the precision sensing and control of highly adaptive intelligent structures. Many theoretical, numerical, and experimental research activities treating piezoelectricity in sensing and control of various flexible structures have been carried out over the last decade. This survey article aims at collecting the recent research studies in this important field. It contains 336 references which are classified accor

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46

Li, Xiaoyun, and David K. Hunter. "Distributed coordinate-free algorithm for full sensing coverage." International Journal of Sensor Networks 5, no. 3 (2009): 153. http://dx.doi.org/10.1504/ijsnet.2009.026363.

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47

De Falco, Stefano, and Giulia Fiorentino. "Remote sensing based on time variance control in configurable area partitioning." Proceedings of the ICA 4 (December 3, 2021): 1–9. http://dx.doi.org/10.5194/ica-proc-4-25-2021.

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Abstract. In this paper a sensor data fusion approach for characteristics field monitoring, based on time variance control model, is proposed. Distributed sensing and remote processing are the basic features of the employed architecture. In fact, in order to obtain meaningful information about the temporal and spatial variations, which characterize the field levels of some characteristics (electromagnetic, air pollution, seismic, etc), a distributed network of wireless and mobile smart-sensors has been designed.Starting from the partitioned configuration of a monitored geographic areas, this m

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48

Palangi, Hamid, Rabab Ward, and Li Deng. "Convolutional Deep Stacking Networks for distributed compressive sensing." Signal Processing 131 (February 2017): 181–89. http://dx.doi.org/10.1016/j.sigpro.2016.07.006.

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49

Kwon, Cheolhyeon, and Inseok Hwang. "Sensing-Based Distributed State Estimation for Cooperative Multiagent Systems." IEEE Transactions on Automatic Control 64, no. 6 (2019): 2368–82. http://dx.doi.org/10.1109/tac.2018.2867341.

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50

Tanaka, N., S. D. Snyder, and C. H. Hansen. "Distributed Parameter Modal Filtering Using Smart Sensors." Journal of Vibration and Acoustics 118, no. 4 (1996): 630–40. http://dx.doi.org/10.1115/1.2888345.

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This paper considers the design of distributed parameter modal sensors called “smart sensors,” with a particular emphasis on filtering the combination of appropriately weighted vibration modes providing a specific performance index in control strategy. First, with a two-dimensional distributed parameter sensor using a PVDF film, the necessary and sufficient condition for sensing the transformed modes of a structure is derived. Then, by considering the practicability of the two-dimensional sensors, an alternative approach based upon one-dimensional smart sensors is presented. It is found that t

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