乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:54:26Z","timestamp":1740149666133,"version":"3.37.3"},"reference-count":36,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T00:00:00Z","timestamp":1710892800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62001254","52202496"]},{"name":"333 Talent Technology Research Project of Jiangsu","award":["2022021"]},{"name":"Natural Science Foundation of the Higher Education Institutions of Jiangsu Province","award":["22KJB510040"]},{"name":"Basic Science Research Program of Nantong City","award":["JC12022028"]},{"name":"Nantong social livelihood science and technology project","award":["MS12022015"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"In this article, the issue of joint state and fault estimation is ironed out for delayed state-saturated systems subject to energy harvesting sensors. Under the effect of energy harvesting, the sensors can harvest energy from the external environment and consume an amount of energy when transmitting measurements to the estimator. The occurrence probability of measurement loss is computed at each instant according to the probability distribution of the energy harvesting mechanism. The main objective of the addressed problem is to construct a joint state and fault estimator where the estimation error covariance is ensured in some certain sense and the estimator gain is determined to accommodate energy harvesting sensors, state saturation, as well as time delays. By virtue of a set of matrix difference equations, the derived upper bound is minimized by parameterizing the estimator gain. In addition, the performance evaluation of the designed joint estimator is conducted by analyzing the boundedness of the estimation error in the mean-squared sense. Finally, two experimental examples are employed to illustrate the feasibility of the proposed estimation scheme.<\/jats:p>","DOI":"10.3390\/s24061967","type":"journal-article","created":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T09:04:12Z","timestamp":1710925452000},"page":"1967","source":"Crossref","is-referenced-by-count":1,"title":["A Joint State and Fault Estimation Scheme for State-Saturated System with Energy Harvesting Sensors"],"prefix":"10.3390","volume":"24","author":[{"given":"Li","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4028-2810","authenticated-orcid":false,"given":"Cong","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China"},{"name":"Haian Institute of High-Tech Research, Nanjing University, Nanjing 226600, China"}]},{"given":"Quan","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3596-4120","authenticated-orcid":false,"given":"Ruifeng","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China"}]},{"given":"Peng","family":"Ping","sequence":"additional","affiliation":[{"name":"School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1109\/MAES.2020.3002001","article-title":"State estimation methods in navigation: Overview and application","volume":"35","author":"Biswas","year":"2020","journal-title":"IEEE Aerosp. 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