Статті в журналах: "Sensing-based control"

1

Li, Shuai, and Ashish Pandharipande. "LED-Based Color Sensing and Control." IEEE Sensors Journal 15, no. 11 (November 2015): 6116–24. http://dx.doi.org/10.1109/jsen.2015.2453408.

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2

Zhang, Shi Ding, Hai Lian Wang, and Jing Ping Mei. "Sensing Confidence Level-Based Cooperative Spectrum Sensing Algorithm." Applied Mechanics and Materials 380-384 (August 2013): 1499–504. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1499.

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Cooperative spectrum sensing is a key technology to tackle the challenges such as fading or hidden terminal problem in local spectrum sensing of cognitive radio system. Conventional cooperative method can improve the detection performance in some sense, but increase overhead of control channel. In order to reduce the overhead, a new cooperative spectrum sensing algorithm based on confidence level is proposed. In this algorithm, the maximum-eigenvalue-based detection scheme is carried out to obtain the local spectrum detection and the detection probability and false alarm probability of each secondary user are used to estimate the reliability of the sensing decision. The test statistic of the secondary users with high reliability are chosen and sent to fusion center. Then weighted factors of chosen secondary users are derived from creditability values, and the global decision is made by weighted fusion at fusion center. The simulation results show that the proposed algorithm improves the detection probability in the guarantee of the false-alarm probability close to 0 and saves half of the overhead in the control channel.

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3

Oertel, Carl-Henrik. "Machine vision-based sensing for helicopter flight control." Robotica 18, no. 3 (May 2000): 299–303. http://dx.doi.org/10.1017/s0263574799002192.

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Machine vision-based sensing enables automatic hover stabilization of helicopters. The evaluation of image data, which is produced by a camera looking straight to the ground, results in a drift free autonomous on-board position measurement system. No additional information about the appearance of the scenery seen by the camera (e.g. landmarks) is needed. The technique being applied is a combination of the 4D-approach with two dimensional template tracking of a priori unknown features.

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4

Hewing, Lukas, Kim P. Wabersich, Marcel Menner, and Melanie N. Zeilinger. "Learning-Based Model Predictive Control: Toward Safe Learning in Control." Annual Review of Control, Robotics, and Autonomous Systems 3, no. 1 (May 3, 2020): 269–96. http://dx.doi.org/10.1146/annurev-control-090419-075625.

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Recent successes in the field of machine learning, as well as the availability of increased sensing and computational capabilities in modern control systems, have led to a growing interest in learning and data-driven control techniques. Model predictive control (MPC), as the prime methodology for constrained control, offers a significant opportunity to exploit the abundance of data in a reliable manner, particularly while taking safety constraints into account. This review aims at summarizing and categorizing previous research on learning-based MPC, i.e., the integration or combination of MPC with learning methods, for which we consider three main categories. Most of the research addresses learning for automatic improvement of the prediction model from recorded data. There is, however, also an increasing interest in techniques to infer the parameterization of the MPC controller, i.e., the cost and constraints, that lead to the best closed-loop performance. Finally, we discuss concepts that leverage MPC to augment learning-based controllers with constraint satisfaction properties.

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5

Tissera, Ponsuge Surani Shalika, Sangho Choe, and Rajiv Punmiya. "Quorum Sensing-Based Nanonetwork Synchronization." IEEE Wireless Communications Letters 8, no. 3 (June 2019): 893–96. http://dx.doi.org/10.1109/lwc.2019.2898980.

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6

Costanzo, Marco. "Control of robotic object pivoting based on tactile sensing." Mechatronics 76 (June 2021): 102545. http://dx.doi.org/10.1016/j.mechatronics.2021.102545.

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7

R. Kalidindi, Ramaprasada, KVSVN Raju, V. Valli Kumari, and C. S. Reddy. "Trust Based Participant Driven Privacy Control in Participatory Sensing." International Journal of Ad hoc, Sensor & Ubiquitous Computing 2, no. 1 (March 24, 2011): 71–84. http://dx.doi.org/10.5121/ijasuc.2011.2107.

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8

Stieber, M. E., M. McKay, G. Vukovich, and E. Petriu. "Vision-based sensing and control for space robotics applications." IEEE Transactions on Instrumentation and Measurement 48, no. 4 (1999): 807–12. http://dx.doi.org/10.1109/19.779178.

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9

Hu, Dongming, and Radovan Kovacevic. "Sensing, modeling and control for laser-based additive manufacturing." International Journal of Machine Tools and Manufacture 43, no. 1 (January 2003): 51–60. http://dx.doi.org/10.1016/s0890-6955(02)00163-3.

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10

Klančar, Gregor, Sašo Blažič, Drago Matko, and Gašper Mušič. "Image-Based Attitude Control of a Remote Sensing Satellite." Journal of Intelligent & Robotic Systems 66, no. 3 (August 16, 2011): 343–57. http://dx.doi.org/10.1007/s10846-011-9621-1.

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11

Zhao, Yun-Bo, Jongrae Kim, and Guo-Ping Liu. "Error Bounded Sensing for Packet-Based Networked Control Systems." IEEE Transactions on Industrial Electronics 58, no. 5 (May 2011): 1980–89. http://dx.doi.org/10.1109/tie.2010.2052539.

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12

Marian, S., D. Tsiulyanu, T. Marian, and H. D. Liess. "Chalcogenide-based chemical sensors for atmospheric pollution control." Pure and Applied Chemistry 73, no. 12 (January 1, 2001): 2001–4. http://dx.doi.org/10.1351/pac200173122001.

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The authors report about characterization of chalcogenide-based thin films, as a materials for gas-sensing applications. The sensing behavior of the AsSTe films was tested with environmental pollutant gases such as NO2, CO, and SO2. A significant sensitivity has been observed for nitrogen dioxide. The detection range for NO2 was between 0.951.9 ppm in ambient air. The response and the recovery time is rapid, with good reproducibility and high sensibility. All the measurements were performed at room temperature. Gas-sensing applications are considered.

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13

Usama, Muhammad, and Jaehong Kim. "Improved Self-Sensing Speed Control of IPMSM Drive Based on Cascaded Nonlinear Control." Energies 14, no. 8 (April 15, 2021): 2205. http://dx.doi.org/10.3390/en14082205.

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This paper presents a nonlinear cascaded control design that has been developed to (1) improve the self-sensing speed control performance of an interior permanent magnet synchronous motor (IPMSM) drive by reducing its speed and torque ripples and its phase current harmonic distortion and (2) attain the maximum torque while utilizing the minimum drive current. The nonlinear cascaded control system consists of two nonlinear controls for the speed and current control loop. A fuzzy logic controller (FLC) is employed for the outer speed control loop to regulate the rotor shaft speed. Model predictive current control (MPCC) is utilized for the inner current control loop to regulate the drive phase currents. The nonlinear equation for the dq reference current is derived to implement the maximum torque per armature (MTPA) control to achieve the maximum torque while using the minimum current values. The model reference adaptive system (MRAS) was employed for the speed self-sensing mechanism. The self-sensing speed control performance of the IPMSM motor drive was compared with that of the traditional cascaded control schemes. The stability of the sensorless mechanism was studied using the pole placement method. The proposed nonlinear cascaded control was verified based on the simulation results. The robustness of the control design was ensured under various loads and in a wide speed range. The dynamic performance of the motor drive is improved while circumventing the need to tune the proportional-integral (PI) controller. The self-sensing speed control performance of the IPMSM drive was enhanced significantly by the designed cascaded control model.

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14

Lee, Jangwon, Jin Wang, Jesus Flores-Cerrillo, and Q. Peter He. "Improving Featured-based Soft Sensing through Feature Selection." IFAC-PapersOnLine 53, no. 2 (2020): 11338–43. http://dx.doi.org/10.1016/j.ifacol.2020.12.542.

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15

Zhijiang, WANG, XUE Kunxi, WU Dingyong, YANG Hui, SHEN Junqi, LIU Jie, and HU Shengsun. "Robotic Weld Seam Correction Control System Based on Visual Sensing." Journal of Mechanical Engineering 55, no. 17 (2019): 48. http://dx.doi.org/10.3901/jme.2019.17.048.

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16

CHENG, Jun, Ou LI, Yue-jin LI, Tie-feng LI, and Gang ZHANG. "Double-granularity connection admission control scheme based on compression sensing." Journal of Computer Applications 29, no. 7 (July 30, 2009): 1858–60. http://dx.doi.org/10.3724/sp.j.1087.2009.01858.

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17

C. Yang, S. M. Greenberg, and J. H. Everitt. "EVALUATION OF HERBICIDE-BASED COTTON REGROWTH CONTROL USING REMOTE SENSING." Transactions of the ASAE 48, no. 5 (2005): 1987–94. http://dx.doi.org/10.13031/2013.19991.

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18

Lv, Na, Yanling Xu, Sichen Li, Xinwen Yu, and Shanben Chen. "Automated control of welding penetration based on audio sensing technology." Journal of Materials Processing Technology 250 (December 2017): 81–98. http://dx.doi.org/10.1016/j.jmatprotec.2017.07.005.

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19

Kim, Byung Wook, and Sung-Yoon Jung. "Dimming control technique for compressed sensing-based optical camera communications." Photonic Network Communications 36, no. 1 (May 23, 2018): 165–73. http://dx.doi.org/10.1007/s11107-018-0775-7.

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20

Wang, Shuyu, Zhaojia Sun, Shuaiyang Duan, Yuliang Zhao, Xiaopeng Sha, Shifeng Yu, and Lei Zuo. "A Hydrogel-Based Self-Sensing Underwater Actuator." Micromachines 13, no. 10 (October 19, 2022): 1779. http://dx.doi.org/10.3390/mi13101779.

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Soft robots made of hydrogels are suited for underwater exploration due to their biocompatibility and compliancy. Yet, reaching high dexterity and actuation force for hydrogel-based actuators is challenging. Meanwhile, real-time proprioception is critical for feedback control. Moreover, sensor integration to mimic living organisms remains problematic. To address these challenges, we introduce a hydrogel actuator driven by hydraulic force with a fast response (time constant 0.83 s). The highly stretchable and conductive hydrogel (1400% strain) is molded into the PneuNet shape, and two of them are further assembled symmetrically to actuate bi-directionally. Then, we demonstrate its bionic application for underwater swimming, showing 2 cm/s (0.19 BL/s) speed. Inspired by biological neuromuscular systems’ sensory motion, which unifies the sensing and actuation in a single unit, we explore the hydrogel actuator’s self-sensing capacity utilizing strain-induced resistance change. The results show that the soft actuator’s proprioception can monitor the undulation in real-time with a sensitivity of 0.2%/degree. Furthermore, we take a finite-element method and first-order differential equations to model the actuator’s bending in response to pressure. We show that such a model can precisely predict the robot’s bending response over a range of pressures. With the self-sensing actuator and the proposed model, we expect the new approach can lead to future soft robots for underwater exploration with feedback control, and the underlying mechanism of the undulation control might offer significant insights for biomimetic research.

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21

Bhat, Owais, Dawood A. Khan, and Rameez Yousuf. "Automated Glucose Control." International Journal of E-Health and Medical Communications 12, no. 6 (November 2021): 1–18. http://dx.doi.org/10.4018/ijehmc.20211101.oa12.

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Automated blood glucose control for diabetes mellitus is a highly desired pursuit of researchers around the globe. Advancement in sensing and control capabilities has paced the development of closed-loop control systems for insulin dependent diabetes. Traditional treatment methods and recent approaches using automated control systems are reviewed in this article. Invasive and non-invasive glucose sensing methods along with insulin therapy are presented in detail. Control algorithms are studied and evaluated based on their ability to keep blood glucose levels in euglycemic range by regulating the amounts of insulin bolus. The article highlight the advantages of using automated control system over the traditional control strategies for insulin dependent diabetes.

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22

Pan, Min, Chenggang Yuan, Hastha Anpalagan, Andrew Plummer, Jun Zou, Junhui Zhang, and Chris Bowen. "Soft Controllable Carbon Fibre-based Piezoresistive Self-Sensing Actuators." Actuators 9, no. 3 (August 30, 2020): 79. http://dx.doi.org/10.3390/act9030079.

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Soft robots and devices exploit deformable materials that are capable of changes in shape to allow conformable physical contact for controlled manipulation. While the use of embedded sensors in soft actuation systems is gaining increasing interest, there are limited examples where the body of the actuator or robot is able to act as the sensing element. In addition, the conventional feedforward control method is widely used for the design of a controller, resulting in imprecise position control from a sensory input. In this work, we fabricate a soft self-sensing finger actuator using flexible carbon fibre-based piezoresistive composites to achieve an inherent sensing functionality and design a dual-closed-loop control system for precise actuator position control. The resistance change of the actuator body was used to monitor deformation and fed back to the motion controller. The experimental and simulated results demonstrated the effectiveness, robustness and good controllability of the soft finger actuator. Our work explores the emerging influence of inherently piezoresistive soft actuators to address the challenges of self-sensing, actuation and control, which can benefit the design of next-generation soft robots.

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23

Shang, Yi, and Hongchi Shi. "Flexible Energy Efficient Density Control on Wireless Sensor Networks." International Journal of Distributed Sensor Networks 3, no. 1 (February 1, 2007): 5–21. http://dx.doi.org/10.1080/15501320601066727.

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In dense wireless sensor networks, density control is an important technique for prolonging the network's lifetime while providing sufficient sensing coverage. In this paper, we develop three new density control protocols by considering the tradeoff between energy usage and coverage. The first one, Non-Overlapping Density Control, aims at maximizing coverage while avoiding the overlap of sensing areas of active sensors. For the ideal case, a set of optimality conditions are derived to select sensors such that the sensing space is covered systematically to maximize the usage of each sensor and minimize the coverage gap. Based on theoretical optimality conditions, we develop a distributed protocol that can be efficiently implemented in large sensor networks. Next, we present a protocol called Non-Overlapping Density Control Based on Distances that does not require location information of the nodes. This protocol is more flexible and easier to implement than existing location-based methods. Finally, we present a new range-adjustable protocol called Non-Overlapping Density Control for Adjustable Sensing Ranges. It allows heterogenous sensing ranges for different sensors to save energy consumption. Extensive simulation shows promising results of the new protocols.

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24

Chawda, Vinay, and Marcia K. O'Malley. "Vision-based force sensing for nanomanipulation." IEEE/ASME Transactions on Mechatronics 16, no. 6 (December 2011): 1177–83. http://dx.doi.org/10.1109/tmech.2010.2093535.

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25

Sun, Zeyu, Jun Liu, Zhixian Li, Tian Wang, Zhijian Wang, Fuqian Jia, and Chunxiao Lai. "CSR-IM: Compressed Sensing Routing-Control- Method With Intelligent Migration-Mechanism Based on Sensing Cloud-Computing." IEEE Access 8 (2020): 28437–49. http://dx.doi.org/10.1109/access.2020.2971537.

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26

Son, Donggun, Seung Jeon, and Haecheon Choi. "A proportional–integral–differential control of flow over a circular cylinder." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369, no. 1940 (April 13, 2011): 1540–55. http://dx.doi.org/10.1098/rsta.2010.0357.

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In the present study, we apply proportional (P), proportional–integral (PI) and proportional–differential (PD) feedback controls to flow over a circular cylinder at Re =60 and 100 for suppression of vortex shedding in the wake. The transverse velocity at a centreline location in the wake is measured and used for the feedback control. The actuation (blowing/suction) is provided to the flow at the upper and lower slots on the cylinder surface near the separation point based on the P, PI or PD control. The sensing location is varied from 1 d to 4 d from the centre of the cylinder. Given each sensing location, the optimal proportional gain in the sense of minimizing the sensing velocity fluctuations is obtained for the P control. The addition of I and D controls to the P control certainly increases the control performance and broadens the effective sensing location. The P, PI and PD controls successfully reduce the velocity fluctuations at sensing locations and attenuate vortex shedding in the wake, resulting in reductions in the mean drag and lift fluctuations. Finally, P controls with phase shift are constructed from successful PI controls. These phase-shifted P controls also reduce the strength of vortex shedding, but their results are not as good as those from the corresponding PI controls.

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27

Guo, Chen, Ming Jin, Qinghua Guo, and Youming Li. "Antieigenvalue-Based Spectrum Sensing for Cognitive Radio." IEEE Wireless Communications Letters 8, no. 2 (April 2019): 544–47. http://dx.doi.org/10.1109/lwc.2018.2879339.

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28

Xue, Yuanfei, and Zhijiang Lou. "Intelligent Control of a Driverless Energy Vehicle Based on an Environment Sensing Sensor." Wireless Communications and Mobile Computing 2022 (May 26, 2022): 1–10. http://dx.doi.org/10.1155/2022/4297888.

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In order to solve the complex environment in the process of vehicle driving and the complexity of self-vehicle structure, intelligent vehicles are prone to rear end collision, lateral collision, and other safety accidents in the presence of tall trees, mountains, and other road environments, endangering the safety of people on board. According to parameters such as the speed of the vehicle, the movement of the blind spot, and the relationship between the vehicle and the blind spot, the model is based on the safety mode of the preceding vehicle. Based on the static obstacles that may exist in the sensing blind area, a sensor sensing blind area safety distance model is established. Based on the possible dynamic obstacles, the active collision avoidance algorithm based on the sensor perceived blind area is studied and simulated. The experimental results show that the selected sensor sensing blind area active collision avoidance controller can well adapt to a variety of special and emergency working conditions, can accurately complete the accurate control of sensor sensing blind area active collision avoidance, and avoid collision accidents to the greatest extent. Compared with the control group, the system designed in this paper can avoid more than 80% of the collision scenes compared with the previous anticollision system. It provides a reference for the future research of sensor sensing blind area-related topics and sensor sensing blind area active collision avoidance system. To a certain extent, it can improve the ability of intelligent vehicle environmental perception and reduce the incidence of rear end collision accidents.

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29

Lee, Sang-Hak, and Sang-Woo Kim. "Actuation Characteristics of SMA Actuator for Self-sensing Based Position Control." Transactions of the Korean Society of Mechanical Engineers - A 42, no. 8 (August 31, 2018): 709–19. http://dx.doi.org/10.3795/ksme-a.2018.42.8.709.

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30

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 model allows to take into account the different levels of degradation over time in the sensors' performances associated with the different geographic partitions, progressively increasing the severity of the control. To this end, through the introduction of a reliability curve, a revised traditional control chart for variables is proposed.The proposed approach, further constituting an element of the scientific debate, aims to be a useful operational tool for professionals and managers employed in the environment control.

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31

Liu, Li Jun, and Ying Hou Lou. "Deviation Control of Weld Seam Tracking Based on Laser Image Sensing." Applied Mechanics and Materials 37-38 (November 2010): 358–61. http://dx.doi.org/10.4028/www.scientific.net/amm.37-38.358.

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Because welding system is given the look function by laser image sensing, the automation of welding system is well improved. But the two problems are image processing deviation under welding interference and adjusting deviation of machine set tracking. Targeting at these problems, the weld seam tracking (WST) system is designed. Some mathematics are brought forward, including the log grey transformation, Laplace edge detection, extracting center route of laser strip and detecting the characteristic points of weld seam image. The dynamic trend of WST is controlled by the current seam deviation calculated by seam characteristic points. The subsection control strategy and the decision algorithm of WST stability in abnormal circumstances are used. The WST experimental results show that tracking S shape weld seam is delivered effectively with high precision based on the proposed weld seam tracking, can meet welding technology requirement and provide experimental data for manufacturing WST system.

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32

Wu, X. Alice, Tae Myung Huh, Aaron Sabin, Srinivasan A. Suresh, and Mark R. Cutkosky. "Tactile Sensing and Terrain-Based Gait Control for Small Legged Robots." IEEE Transactions on Robotics 36, no. 1 (February 2020): 15–27. http://dx.doi.org/10.1109/tro.2019.2935336.

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33

Ma, Lichuan, Yong Xiang, Qingqi Pei, Yang Xiang, and Haojin Zhu. "Robust Reputation-Based Cooperative Spectrum Sensing via Imperfect Common Control Channel." IEEE Transactions on Vehicular Technology 67, no. 5 (May 2018): 3950–63. http://dx.doi.org/10.1109/tvt.2017.2763980.

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Ehsani, M., and K. R. Ramani. "Direct control strategies based on sensing inductance in switched reluctance motors." IEEE Transactions on Power Electronics 11, no. 1 (January 1996): 74–82. http://dx.doi.org/10.1109/63.484419.

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35

D. K. Giles, M. J. Delwiche, and R. B. Dodd. "Control of Orchard Spraying Based on Electronic Sensing of Target Characteristics." Transactions of the ASAE 30, no. 6 (1987): 1624–36. http://dx.doi.org/10.13031/2013.30614.

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36

Siddiqui, Muhammad Faisal, Miles Rzechowicz, Winters Harvey, A. W. Zularisam, and G. Fane Anthony. "Quorum sensing based membrane biofouling control for water treatment: A review." Journal of Water Process Engineering 7 (September 2015): 112–22. http://dx.doi.org/10.1016/j.jwpe.2015.06.003.

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37

Dr. M. Varadharaj. "Density Based Traffic Control System with Smart Sensing Of Emergency Vehicles." International Journal of New Practices in Management and Engineering 8, no. 02 (June 30, 2019): 01–07. http://dx.doi.org/10.17762/ijnpme.v8i02.75.

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Present Traffic Light Controller (TLC) relies upon micro-controller and microchip. These TLC have restrictions as they are depend on pre-portrayed gear, which is filling in with respect to the program that doesn't have the versatility of adjustment on continuous reason. Owing to fixed time spans, orange and red signal’s holding up time is more and vehicle uses more fuel. To make traffic light leadership progressively beneficial, we abuse the advancement of new procedure called as “Density based traffic control system with smart sensing of emergency vehicles”. It is constructed mainly by using Magnetic Sensors for real world environment and by using IR modules for Model. The main objective of our project is to clear traffic efficiently by effective usage of the green signal time. In this system the density of the vehicle in a particular lane is obtained by the number of magnetic sensors kept in the road side which produces output signal with respect to the density of the traffic. Thus produced output signal is further processed by ARM microcontroller and according to the density obtained by the magnetic sensors the countdown time of the green signal is varied by the microcontroller and hence the usage of green signal even after all the vehicle pass by are prevented. In addition to this system our system also senses the emergency vehicle like ambulance that approaches the signal by detecting the RF signal transmitted by the Ambulance or other emergency vehicle with the help of RF receivers that kept at the road side and halts all the vehicles by putting red signal for all the four sides of road and puts special ‘green jeep signal’ for the emergency vehicle to pass by hence our system provide way for emergency vehicle. It can also prioritize the emergency vehicle with the help of RF transmitter and receiver. As the signalling board receives the RF signal, it turns the Corresponding lane ON, thus clearing the route for the emergency vehicle. DSS also analyses the pollution levels by placing a check over the vehicle emissions at the junctions. When the priorities of any two lanes clash, pollution levels are taken into account to provide the signals for them in turns. The gas sensors are fitted onto the signalling boards which help in calculating the pollutant levels.

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38

KACIRA, Murat, Sadanori SASE, Limi OKUSHIMA, and Peter P. LING. "Plant Response-Based Sensing for Control Strategies in Sustainable Greenhouse Production." Journal of Agricultural Meteorology 61, no. 1 (2005): 15–22. http://dx.doi.org/10.2480/agrmet.61.15.

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39

Nasser, Ahmed, Osamu Muta, Maha Elsabrouty, and Haris Gacanin. "Compressive Sensing Based Spectrum Allocation and Power Control for NOMA HetNets." IEEE Access 7 (2019): 98495–506. http://dx.doi.org/10.1109/access.2019.2929185.

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40

Merced, Emmanuelle, David Torres, Xiaobo Tan, and Nelson Sepulveda. "An Electrothermally Actuated VO2-Based MEMS Using Self-Sensing Feedback Control." Journal of Microelectromechanical Systems 24, no. 1 (February 2015): 100–107. http://dx.doi.org/10.1109/jmems.2014.2317944.

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41

Ye, Dengpan, Yuan Mei, Yueyun Shang, Jixiang Zhu, and Kun Ouyang. "Mobile crowd-sensing context aware based fine-grained access control mode." Multimedia Tools and Applications 75, no. 21 (May 31, 2015): 13977–93. http://dx.doi.org/10.1007/s11042-015-2693-3.

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42

Ren, Jinliang, J. F. Reid, and J. B. Litchfield. "Knowledge-based supervision and control of bioprocess with a machine vision-based sensing system." Journal of Biotechnology 36, no. 1 (July 1994): 25–34. http://dx.doi.org/10.1016/0168-1656(94)90019-1.

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43

Wu, Jin Wu, and Fei Tan. "Error Sensing Strategy for Active Structural Acoustic Control Based on Acoustic Radiation Modes." Advanced Materials Research 346 (September 2011): 682–88. http://dx.doi.org/10.4028/www.scientific.net/amr.346.682.

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A new sensing strategy based on acoustic radiation modes for active structural acoustic control approach is proposed for the minimization of the acoustic radiation from a vibrating simply supported plate. Measuring a few points velocity on the vibrating surface and solving the underdetermined equations of the radiation mode expansion, the approximate values of amplitudes of the first radiation modes can be obtained. Taking the above approximate amplitudes as the input signals of the controller, this forms an error sensing strategy based on radiation modes and corresponding active control strategy. The numerical simulations results are presented to show the feasibility of this error sensing strategy.

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Fujisawa, Shoichiro, Kazuo Kawada, and Yoshihiro Ohnishi. "Special Issue on Education Based on Practical Exercise on Sensing and Control." Journal of Robotics and Mechatronics 31, no. 3 (June 20, 2019): 375. http://dx.doi.org/10.20965/jrm.2019.p0375.

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Control engineering and sensing engineering improve productivity and save resources and energy in industry, and they are also deeply related to the solving greater societal, economic, and environmental problems. Control engineering and sensing engineering have become dynamic forces that enrich various phases of life through interdisciplinary or cross-sectional study. Furthermore, in recent years, due to the development of information technology, as symbolized by terms such as “big data” or “AI,” “sensing and control at a higher level” has become possible, premised by big data processing that is faster by orders of magnitude than conventional data processing. All this has increased the importance of control engineering and sensing engineering. In response to the development of the fields of control engineering and sensing engineering associated with the advance of the “information society,” education in these fields has also needed to be enhanced. On the national scale, the Ministry of Education, Culture, Sports, Science and Technology will introduce Japanese elementary school computational thinking education into elementary school in fiscal year 2020, and the new Courses of Study for High School Information Education in fiscal year 2022. At the same time, individual companies, educational institutions, etc. have also been experimenting with various forms of education in control engineering and sensing engineering. During these changing times, the most advanced studies related to the development of instruction and evaluation methods for educational materials on control engineering, sensing engineering, and control technology have been collected, and the present special issue was planned. This special issue is a collection of practical papers related to measurement and control education, including one paper on Model-Based Development education in a company and eight papers on education in an educational institution. These eight papers include two on education using a robot contest in a university, one on introducing measurement and control engineering education in a national institute of technology college, three on introducing it in a junior high school, and two on introducing it in an elementary school. We hope that this special issue serves to support the readers’ future efforts in control engineering and sensing engineering education, and we thank the authors and reviewers of the papers.

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Kim, Euiyoung, and Haecheon Choi. "Linear proportional–integral control for skin-friction reduction in a turbulent channel flow." Journal of Fluid Mechanics 814 (February 8, 2017): 430–51. http://dx.doi.org/10.1017/jfm.2017.33.

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In the present study, we apply a proportional (P)–integral (I) feedback control to a turbulent channel flow for skin-friction reduction. The instantaneous wall-normal velocity at a sensing plane above the wall is measured as a sensing parameter, and blowing/suction is provided at the wall based on the PI control. The performance of PI controls is estimated by the change in the skin friction while varying the sensing plane location $y_{s}$ and the proportional and integral feedback gains ($\unicode[STIX]{x1D6FC}$ and $\unicode[STIX]{x1D6FD}$ respectively). The opposition control proposed by Choi et al. (J. Fluid Mech., vol. 262, 1994, pp. 75–110) corresponds to a P control with $\unicode[STIX]{x1D6FC}=1$. When the sensing plane is located close to the wall ($y_{s}^{+}\lesssim 10$), PI controls result in greater skin-friction reductions than corresponding P controls. The root-mean-square (r.m.s.) sensing velocity fluctuations, considered as the control error, approach zero with successful PI controls, but do not with P controls. Successful PI controls reduce the strength of near-wall coherent structures and the r.m.s. velocity fluctuations above the wall apart from those near the wall due to the control input. The frequency spectra of the sensing velocity show that the I component of PI controls significantly reduces the energy at low frequencies, much more than P controls do. Proportional–integral controls are also applied to a linearized flow model having transient growth of disturbances. The performance of PI controls for a linearized flow model is very similar to that for a turbulent channel flow, i.e. the low-frequency components of disturbances are significantly reduced by the I component of PI controls, and the transient energy growth is suppressed more than by P controls.

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Schroedter, Richard, Han Woong Yoo, David Brunner, and Georg Schitter. "Capacitive Charge-based Self-Sensing for Resonant Electrostatic MEMS mirrors." IFAC-PapersOnLine 53, no. 2 (2020): 8553–58. http://dx.doi.org/10.1016/j.ifacol.2020.12.568.

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Pan, Gong Yu, and Shen Shen Wang. "Study on the Vibration Control Based on the Piezoelectric Self-Sensing Vibration Damper." Applied Mechanics and Materials 752-753 (April 2015): 739–44. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.739.

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<p>As the sensing element and a driving element for vibration control using smart materials, the structural vibration control is very active field for research and application. This paper mainly study the characteristics of piezoelectric self-sensing vibration .Through the action analysis of research on Piezoelectric Actuator establish a self-sensing piezoelectric vibration damper and a model of self-sensing piezoelectric absorber . Then through the experiment and simulation, get the study on its characteristics.</p>

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Antunes, L. Caetano M., Rosana B. R. Ferreira, Michelle M. C. Buckner, and B. Brett Finlay. "Quorum sensing in bacterial virulence." Microbiology 156, no. 8 (August 1, 2010): 2271–82. http://dx.doi.org/10.1099/mic.0.038794-0.

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Bacteria communicate through the production of diffusible signal molecules termed autoinducers. The molecules are produced at basal levels and accumulate during growth. Once a critical concentration has been reached, autoinducers can activate or repress a number of target genes. Because the control of gene expression by autoinducers is cell-density-dependent, this phenomenon has been called quorum sensing. Quorum sensing controls virulence gene expression in numerous micro-organisms. In some cases, this phenomenon has proven relevant for bacterial virulence in vivo. In this article, we provide a few examples to illustrate how quorum sensing can act to control bacterial virulence in a multitude of ways. Several classes of autoinducers have been described to date and we present examples of how each of the major types of autoinducer can be involved in bacterial virulence. As quorum sensing controls virulence, it has been considered an attractive target for the development of new therapeutic strategies. We discuss some of the new strategies to combat bacterial virulence based on the inhibition of bacterial quorum sensing systems.

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Guan, Xinchun, Yi Ru, and Yonghu Huang. "A novel velocity self-sensing magnetorheological damper: Design, fabricate, and experimental analysis." Journal of Intelligent Material Systems and Structures 30, no. 4 (November 14, 2017): 497–505. http://dx.doi.org/10.1177/1045389x17740961.

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This article presents the development of a novel magnetorheological damper with velocity self-sensing capability. The velocity self-sensing mechanism, based on the optical tracking technology and numerical circuit technology, was adopted. The configuration and work principle of the velocity self-sensing magnetorheological damper were presented. The self-sensing circuits, built with optical mouse sensor and microcontrollers, were integrated into the hollow upper lid. The hollow upper lid provides a suitable place for the self-sensing circuits, can be installed and disassembled easily, and can be maintained efficiently. The velocity self-sensing magnetorheological damper prototype with 10 kN capacity was theoretically analyzed, fabricated, and investigated. Finally, the damping performance, self-sensing performance, and self-sensing control capability were tested and analyzed. The results indicated that self-sensing velocity unit has high accurate monitoring capability over a wide range of working conditions. The velocity self-sensing magnetorheological damper–based control system has sufficient ability to control the magnetorheological damper.

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Lisowski, Mateusz, and Tadeusz Uhl. "RFID Based Sensing for Structural Health Monitoring." Key Engineering Materials 569-570 (July 2013): 1178–85. http://dx.doi.org/10.4028/www.scientific.net/kem.569-570.1178.

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RFID is a rapidly developing technology of wireless communication and identification mostly used in supply chain systems, logistic and access control. Nowadays attempts to transfer this technology to other applications are carried out. This paper presents review of global researches performed last years, on application of RFID technology to tasks connected with wireless passive sensing in Structural Health Monitoring, with additional overview of works conducted in this subject by the authors. Sensors based on this technology require neither battery nor wire. It could be interrogated from distance, its lifetime is almost unlimited. Investigations, focused both on using RFID transponder as a sensing element, as well as, using antenna as a energy harvesting part that could power the sensor circuit, are mentioned. Performed studies show, that despite problems connected with using high frequencies, described wireless sensors should be useful for SHM tasks.

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