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Journal articles on the topic "Continuous and aperiodic sampled measurements":
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Guo, Meng, and Dimos V. Dimarogonas. "Nonlinear consensus via continuous, sampled, and aperiodic updates." International Journal of Control 86, no. 4 (April 2013): 567–78. http://dx.doi.org/10.1080/00207179.2012.747735.
Sferlazza, Antonino, Sophie Tarbouriech, and Luca Zaccarian. "State observer with Round-Robin aperiodic sampled measurements with jitter." Automatica 129 (July 2021): 109573. http://dx.doi.org/10.1016/j.automatica.2021.109573.
Song, Chengcheng, Haoping Wang, and Yang Tian. "Event-triggered piecewise-continuous observer design based on system output data received from network." Transactions of the Institute of Measurement and Control 40, no. 15 (January 24, 2018): 4166–74. http://dx.doi.org/10.1177/0142331217744616.
This paper proposes an event-triggered piecewise-continuous observer (E-PCO) that can estimate continuous-time undelayed system state using event-triggered (aperiodic) sampled and delayed system output that is received from network. The key point of this estimation method is the design of three reconstructions and an event-triggered reduced-order discrete-time Luenberger observer (E-RODL-O). First, Reconstruction I compensates for the effects of event-triggered sampling. Based on Reconstruction I, the E-RODL-O is designed for obtaining a periodic sampled delayed system state. Then, Reconstruction II makes up for the influences of time delays, which brings the periodic sampled undelayed system state. Based on this, Reconstruction III finally calculates the continuous-time undelayed system state. Through some parameters selections, the stability of E-PCO system is guaranteed. The theoretical design is applied to a networked visual servoing mobile cart system for verifying its validity.
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Abdalmoaty, Mohamed, and Alexander Medvedev. "Continuous Time-Delay Estimation From Sampled Measurements." IFAC-PapersOnLine 56, no. 2 (2023): 6982–87. http://dx.doi.org/10.1016/j.ifacol.2023.10.534.
This study addresses one of the most essential distributed control problems in multiagent systems, called the average consensus issue, using a new event-triggered sampling control perspective. Although the continuous-time sampling for average consensus has provided good results currently, a systematic investigation into the continuous-time agent dynamics with sampled-data control inputs under an event-triggered mechanism is critically lacking. The problem considered in this paper can be formulated into an average consensus problem of hybrid systems. The method considers three types of control schemes, among which periodic sampling is integrant. The first scheme is a classical sampling controller reinvestigated through a lemma. The second scheme realizes aperiodic control update as well as periodic communication, while the third scheme achieves both aspects aperiodically. Corresponding sufficient conditions of the aforementioned three schemes are derived such that the asymptotic stability of systems is ensured by using algebraic graph theory, matrix analysis, and Lyapunov theory. The constraints for the allowed sampling period, event parameter, and maximum eigenvalue of graph Laplacian are explicitly derived. Moreover, the potential Zeno behavior of agents due to the sampling control theory is avoided. Thus, a digitally implementable technique is provided. Finally, some numerical examples are provided to verify the effectiveness of the proposed theoretical analysis.
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Liu, Zhi-Wei, Zhi-Hong Guan, Xuemin Shen, and Gang Feng. "Consensus of Multi-Agent Networks With Aperiodic Sampled Communication Via Impulsive Algorithms Using Position-Only Measurements." IEEE Transactions on Automatic Control 57, no. 10 (October 2012): 2639–43. http://dx.doi.org/10.1109/tac.2012.2214451.
Shi, P. "H filtering for linear continuous-time systems with sampled measurements." IMA Journal of Mathematical Control and Information 15, no. 4 (December 1, 1998): 349–62. http://dx.doi.org/10.1093/imamci/15.4.349.
Shi, Peng, Youyi Wang, and Lihua Xie. "Robust Filtering for Interconnected Uncertain Systems Under Sampled Measurements." Journal of Dynamic Systems, Measurement, and Control 119, no. 2 (June 1, 1997): 337–40. http://dx.doi.org/10.1115/1.2801261.
This paper presents the results of robust filtering for a class of interconnected uncertain systems under sampled measurements. We address the problem of designing filters, using sampled measurements, which would guarantee a prescribed H∞ performance in the continuous-time context, irrespective of the parameter uncertainty and unknown initial states. Both the cases of finite and infinite horizon filtering are investigated in terms of N pairs of Riccati equations with finite discrete jumps.
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Dinh, Thach Ngoc, Vincent Andrieu, Madiha Nadri, and Ulysse Serres. "Continuous-Discrete Time Observer Design for Lipschitz Systems With Sampled Measurements." IEEE Transactions on Automatic Control 60, no. 3 (March 2015): 787–92. http://dx.doi.org/10.1109/tac.2014.2329211.
Shi, Peng. "Control of continuous-time systems with discrete jumps." Journal of the Australian Mathematical Society. Series B. Applied Mathematics 41, no. 1 (July 1999): 58–82. http://dx.doi.org/10.1017/s0334270000011036.
AbstractIn this paper, the design of output feedback controllers for linear systems under sampled measurements is investigated. The performance we use is the worst-case gain from disturbances to the controlled output, which comprises both a continuous-time and a discretetime signal to be controlled. Control problems in both the finite and infinite horizonare addressed. Necessary and sufficient conditions for the existence of a suitable sampled-data output feedback controller are given in terms of two Riccati differential equations with finite discrete jumps. A numerical example is given to show the potential of the proposed technique.
Dissertations / Theses on the topic "Continuous and aperiodic sampled measurements":
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Bouchama, Fawzia. "Synthèse d’observateurs continus-discrets pour les systèmes non linéaires : Application au Train Autonome." Electronic Thesis or Diss., Valenciennes, Université Polytechnique Hauts-de-France, 2024. http://www.theses.fr/2024UPHF0005.
Ce travail de thèse contribue au projet collaboratif "Train de Fret Autonome'' porté par la SNCF et a pour but d’automatiser la conduite du train de Fret afin de garantir une conduite autonome fiable et sécurisée dans toutes conditions environnementales. Dans ce contexte, nos contributions concernent le développement d’estimateurs permettant de reconstruire avec précision la position et la vitesse longitudinale du train dans des conditions variables d’adhérence roue-rail. La difficulté majeure provient du fait que les capteurs odométriques embarqués fournissent une mesure de la rotation des roues au niveau des essieux mais ne détectent pas directement le phénomène de glissement des roues, ce qui entraîne une grande imprécision au niveau de l’estimation de la vitesse longitudinale du train. Pour faire face à ce problème, il est nécessaire de faire un recalage précis en utilisant la position du train mesurée par des radio-balises installées sur le rail. Néanmoins, cette mesure est discrète avec une période d’échantillonnage variable. L’un des challenges est de considérer les mesures du train qui combinent à la fois des mesures considérées continues et des mesures apériodiquement échantillonnées. Ainsi, la principale contribution théorique de cette thèse est la conception d’un observateur continu-discret pour une classe de systèmes multi-entrées/multi-sorties avec des sorties continues entachées de bruits de mesures et des sorties apériodiquement échantillonnées. Cet observateur est conçu pour répondre au cahier de charge du projet ``Train de Fret Autonome'' afin d’estimer la vitesse du train dans des conditions variables d’adhérence. Les performances de cet observateur sont montrées en simulation et comparées avec d’autres approches d’estimation de la vitesse du train puis ensuite validées expérimentalement via une campagne d’essais réalisée au Centre d’Essai Ferroviaire de Tronville-en-Barrois This thesis contributes to the collaborative project "Train de Fret Autonome'' led by the SNCF and aims to control autonomous freight trains in order to guarantee reliable and safe autonomous driving in all environmental conditions. In this context, our contributions concern the development of estimators for accurately reconstructing the train position and longitudinal speed under variable wheel-rail adhesion conditions. The major difficulty arises from the fact that on-board odometric sensors provide a measurement of wheel rotation at axle level, but do not directly detect the phenomenon of wheel slippage, resulting in inaccurate estimation of the longitudinal speed of the train. To overcome this problem, it is necessary to make a precise recalibration using the position of the train measured by radio beacons installed on the rail. Nevertheless, this measurement is discrete with a variable sampling period. One of the challenges is to consider train measurements that combine both continuous and aperiodically sampled measurements. Thus, the main theoretical contribution of this thesis is the design of a continuous-discrete observer for a class of multi-input/multi-output systems with continuous noisy outputs and aperiodically sampled outputs. This observer is designed to meet the specifications of the "Autonomous Freight Train" project, in order to estimate train speed under variable adhesion conditions. The performance of this observer is shown in simulation and compared with other approaches to train speed estimation, then validated experimentally via an experimental test program carried out at the Centre d'Essai Ferroviaire of Tronville-en-Barrois
Book chapters on the topic "Continuous and aperiodic sampled measurements":
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Herff, Christian, and Dean J. Krusienski. "Extracting Features from Time Series." In Fundamentals of Clinical Data Science, 85–100. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99713-1_7.
AbstractClinical data is often collected and processed as time series: a sequence of data indexed by successive time points. Such time series can be from sources that are sampled over short time intervals to represent continuous biophysical wave-(one word waveforms) forms such as the voltage measurements representing the electrocardiogram, to measurements that are sampled daily, weekly, yearly, etc. such as patient weight, blood triglyceride levels, etc. When analyzing clinical data or designing biomedical systems for measurements, interventions, or diagnostic aids, it is important to represent the information contained within such time series in a more compact or meaningful form (e.g., noise filtering), amenable to interpretation by a human or computer. This process is known as feature extraction. This chapter will discuss some fundamental techniques for extracting features from time series representing general forms of clinical data.
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Goovaerts, Pierre. "Local Estimation: Accounting for Secondary Information." In Geostatistics for Natural Resources Evaluation, 185–258. Oxford University PressNew York, NY, 1997. http://dx.doi.org/10.1093/oso/9780195115383.003.0006.
Abstract Direct measurements of the primary attribute of interest are often supplemented by secondary information originating from other related categorical or continuous attributes. The estimation generally improves when this additional and usually denser information is taken into consideration, particularly when the primary data are sparse or poorly correlated in space. Section 6.1 presents three kriging algorithms to incorporate exhaustively sampled secondary data: kriging within strata, simple kriging with varying local means, and kriging with an external drift.
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Sallam, Gehan A. H., Tahani Youssef, Mohamed El-Sayed Embaby, and Fatma Shaltot. "Using Geographic Information System to Infollow the Fertilizers Pollution Migration." In Green Technologies, 564–86. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-472-1.ch312.
In recent years, many countries have faced great challenges due to their limited water resources. According to these challenges, they have undertaken large scale projects to reuse agricultural drainage water in irrigation purpose. The Governments in these countries can enhance water management and sustainable development by adopting policies that enable them to meet water demands and supply management. Therefore, there is a need for unconventional methods to provide better tools for the assessment and management of water quality problems to adopt management policies and set the limits for sustainable drainage water reuse. The implementation of Geographic Information System (GIS) in this field offers an ideal tool for measurements with limited number of sampled points. Statistical analysis that can be provided within GIS is rapidly becoming an impressive tool for statistical analysis of continuous data. The main objective of this chapter is to discuss using GIS to in-follow the pollution caused by fertilizers migration to the water and the soil by applying statistical analysis within the GIS using geostatistical analyst. Geostatistical analyst is an extension of Arc Map™ that bridges the gap between geostatistics and GIS and provides a powerful collection of tools for the management and visualization of spatial data by applying Spatial Statistics.
Conference papers on the topic "Continuous and aperiodic sampled measurements":
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Hann, Cheikh A. B., Vincent Van Assche, Naveena Crasta, and Francoise Lamnabhi-Lagarrigue. "Dynamical continuous high gain observer for sampled measurements systems." In 2012 IEEE 51st Annual Conference on Decision and Control (CDC). IEEE, 2012. http://dx.doi.org/10.1109/cdc.2012.6426327.
Huichai Zhang, M. V. Basin, and M. Skliar. "Optimal state estimation with continuous, multirate and randomly sampled measurements." In Proceedings of the 2004 American Control Conference. IEEE, 2004. http://dx.doi.org/10.23919/acc.2004.1384506.
Zhang, Daoyuan, Yanjun Shen, and Yi Shen. "Continuous observers design for nonlinear systems based on sampled output measurements." In 2014 33rd Chinese Control Conference (CCC). IEEE, 2014. http://dx.doi.org/10.1109/chicc.2014.6895591.
Ahmadzadeh, Hamid Reza, and Masoud Shafiee. "Sampled-Data-Based Descriptor Observer Design with Aperiodic Measurements for Lithium-Ion Batteries in Hybrid Electric Vehicles." In 2023 31st International Conference on Electrical Engineering (ICEE). IEEE, 2023. http://dx.doi.org/10.1109/icee59167.2023.10334767.
Liu, Zhiwei, Hong Zhou, Zhihong Guan, and Li Ding. "Impulsive consensus of multi-agent networks with aperiodic sampled communication and nonuniform time-varying delays using position-only measurements." In 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI). IEEE, 2012. http://dx.doi.org/10.1109/icaci.2012.6463117.
Giordani Titton, Mathias, João Manoel Gomes da Silva Jr., and Giórgio Valmórbida. "Stability of Sampled-Data Control for Lurie Systems with Slope-Restricted Nonlinearities." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1661.
This paper deals with the stability analysis of aperiodic sampled-data Lurie systems, where the nonlinearity is assumed to be both sector and slope restricted. The proposed method is based on the use of a new class of looped-functionals whose derivative is negative along the trajectories of the continuous-time system. In addition, it contains a generalized Lurie-type function that is quadratic on both the states and the nonlinearity and has a Lurie-Postnikov integral term, which provides some advantages in comparison to simpler candidate functions. On this basis, stability conditions in the form of linear matrix inequalities (LMIs) are formulated. It is shown that the proposed conditions guarantee that the Lurie function is strictly decreasing at the sampling instants, which also implies that the continuous-time trajectories converge asymptotically to the origin. We then formulate some optimization problems for computing themaximal intersampling interval or the maximal sector bounds for which the stability of the sampled-data closed-loop system is guaranteed. A numerical example to illustrate the results is provided.
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Wang, Chen, Shuai Li, Weiguo Xia, Jinan Sun, and Guangming Xie. "Formation control for multiple agents with local measurements: continuous-time and sampled-data-based cases." In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. http://dx.doi.org/10.1109/cdc40024.2019.9028870.
Zhang, Daoyuan, Yanjun Shen, Xiaojuan Xue, and Xiongfeng Huang. "Continuous output feedback stabilization for a class of nonlinear systems with sampled and delayed measurements." In 2016 35th Chinese Control Conference (CCC). IEEE, 2016. http://dx.doi.org/10.1109/chicc.2016.7553133.
He, Liang, Donald Bowe, Philips Thomas, and Ranajit Ghosh. "Improved Reliability of Dew Point Measurements of Furnace Atmosphere on a Continuous Basis." In HT 2017. ASM International, 2017. http://dx.doi.org/10.31399/asm.cp.ht2017p0146.
Abstract Dew point (DP) is a function of the furnace atmosphere composition. In a metal processing furnace, maintaining appropriate atmosphere composition is critical to achieving the desired gas/metal reactions and quality and consistency of the treated product. Continuous measurement of DP is always challenging because of particulates and vapor-phase contaminants in sampled gas stream which can potentially accumulate in filtering systems and on sensors. The DP measurement can also be affected by temperature variations within the sampling unit. Thus, DP readings can drift significantly, necessitating frequent cleaning, recalibration, and sensor replacement. Air Products has developed a DP monitoring system that addresses these issues and based on long-term testing at a customer site, drifts/changes of DP readings on calibration gas were not observed after more than one year of operation, without any maintenance. The contamination and drift issues have been mitigated by incorporating an automated self-cleaning and sensor calibration process after pre-set measurement periods. Temperature control of the sensor and the sampling system are also essential to maintain consistency, and can be achieved via various design features. Drifts/changes in DP that are reported through local monitoring/alarms or remotely through cloud server access can also help to address furnace operational issues quickly and efficiently.
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Konig, Stefan, Mark Schmidt, and Christian Hoene. "Precise time of flight measurements in IEEE 802.11 networks by cross-correlating the sampled signal with a continuous Barker code." In 2010 IEEE 7th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS). IEEE, 2010. http://dx.doi.org/10.1109/mass.2010.5663785.
