Non-Fragile Estimation for Nonlinear Delayed Complex Networks with Random Couplings Using Binary Encoding Schemes
This paper is dedicated to dealing with the design issue of a non-fragile state estimator for a type of nonlinear complex network subject to random couplings and random multiple time delays under binary encoding schemes (BESs). The BESs are put into use in the transmission of data from the sensor to...
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| Published in | Sensors (Basel, Switzerland) Vol. 25; no. 9; p. 2880 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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02.05.2025
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| Online Access | Get full text |
| ISSN | 1424-8220 1424-8220 |
| DOI | 10.3390/s25092880 |
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| Abstract | This paper is dedicated to dealing with the design issue of a non-fragile state estimator for a type of nonlinear complex network subject to random couplings and random multiple time delays under binary encoding schemes (BESs). The BESs are put into use in the transmission of data from the sensor to the remote estimator. The phenomenon of bit errors is considered in the process of signal transmission, whose description utilizes a Bernoulli-distributed random sequence. The random couplings are represented by using the Kronecker delta function as well as a Markov chain. This paper aims to conduct a non-fragile state estimation such that, in the presence of some variations/perturbations in the gain parameter of the estimator, the estimation error dynamics will reach exponential ultimate boundedness in mean square and the ultimate bound will be minimized. Utilizing both stochastic analysis and matrix inequality processing, a sufficient condition is provided to guarantee that the constructed estimator satisfies the expected estimation performance, and the estimator gains are acquired by tackling an optimization issue constrained by some linear matrix inequalities. Eventually, two simulation examples are conducted, whose results verify that the approach to the design of a non-fragile estimator in this paper is effective. |
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| AbstractList | This paper is dedicated to dealing with the design issue of a non-fragile state estimator for a type of nonlinear complex network subject to random couplings and random multiple time delays under binary encoding schemes (BESs). The BESs are put into use in the transmission of data from the sensor to the remote estimator. The phenomenon of bit errors is considered in the process of signal transmission, whose description utilizes a Bernoulli-distributed random sequence. The random couplings are represented by using the Kronecker delta function as well as a Markov chain. This paper aims to conduct a non-fragile state estimation such that, in the presence of some variations/perturbations in the gain parameter of the estimator, the estimation error dynamics will reach exponential ultimate boundedness in mean square and the ultimate bound will be minimized. Utilizing both stochastic analysis and matrix inequality processing, a sufficient condition is provided to guarantee that the constructed estimator satisfies the expected estimation performance, and the estimator gains are acquired by tackling an optimization issue constrained by some linear matrix inequalities. Eventually, two simulation examples are conducted, whose results verify that the approach to the design of a non-fragile estimator in this paper is effective. This paper is dedicated to dealing with the design issue of a non-fragile state estimator for a type of nonlinear complex network subject to random couplings and random multiple time delays under binary encoding schemes (BESs). The BESs are put into use in the transmission of data from the sensor to the remote estimator. The phenomenon of bit errors is considered in the process of signal transmission, whose description utilizes a Bernoulli-distributed random sequence. The random couplings are represented by using the Kronecker delta function as well as a Markov chain. This paper aims to conduct a non-fragile state estimation such that, in the presence of some variations/perturbations in the gain parameter of the estimator, the estimation error dynamics will reach exponential ultimate boundedness in mean square and the ultimate bound will be minimized. Utilizing both stochastic analysis and matrix inequality processing, a sufficient condition is provided to guarantee that the constructed estimator satisfies the expected estimation performance, and the estimator gains are acquired by tackling an optimization issue constrained by some linear matrix inequalities. Eventually, two simulation examples are conducted, whose results verify that the approach to the design of a non-fragile estimator in this paper is effective.This paper is dedicated to dealing with the design issue of a non-fragile state estimator for a type of nonlinear complex network subject to random couplings and random multiple time delays under binary encoding schemes (BESs). The BESs are put into use in the transmission of data from the sensor to the remote estimator. The phenomenon of bit errors is considered in the process of signal transmission, whose description utilizes a Bernoulli-distributed random sequence. The random couplings are represented by using the Kronecker delta function as well as a Markov chain. This paper aims to conduct a non-fragile state estimation such that, in the presence of some variations/perturbations in the gain parameter of the estimator, the estimation error dynamics will reach exponential ultimate boundedness in mean square and the ultimate bound will be minimized. Utilizing both stochastic analysis and matrix inequality processing, a sufficient condition is provided to guarantee that the constructed estimator satisfies the expected estimation performance, and the estimator gains are acquired by tackling an optimization issue constrained by some linear matrix inequalities. Eventually, two simulation examples are conducted, whose results verify that the approach to the design of a non-fragile estimator in this paper is effective. |
| Audience | Academic |
| Author | Li, Weijian Chang, Mengdi Bu, Xianye Song, Yanhua Hou, Nan |
| AuthorAffiliation | 4 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing 163318, China 6 Sinopec Qilu Petrochemical Company, Zibo 255400, China; lwjyeokrin@163.com 7 School of Electrical & Information Engineering, Northeast Petroleum University, Daqing 163318, China 1 Sanya Offshore Oil & Gas Research Institute, Northeast Petroleum University, Sanya 572025, China; nanhou@nepu.edu.cn 3 National Key Laboratory of Continental Shale Oil, Northeast Petroleum University, Daqing 163318, China 5 Research Center for Mathematics and Interdisciplinary Sciences, Northeast Petroleum University, Daqing 163318, China 2 Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing 163318, China; hytsyh@126.com (Y.S.); cmd_1230@163.com (M.C.) |
| AuthorAffiliation_xml | – name: 2 Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing 163318, China; hytsyh@126.com (Y.S.); cmd_1230@163.com (M.C.) – name: 3 National Key Laboratory of Continental Shale Oil, Northeast Petroleum University, Daqing 163318, China – name: 6 Sinopec Qilu Petrochemical Company, Zibo 255400, China; lwjyeokrin@163.com – name: 5 Research Center for Mathematics and Interdisciplinary Sciences, Northeast Petroleum University, Daqing 163318, China – name: 7 School of Electrical & Information Engineering, Northeast Petroleum University, Daqing 163318, China – name: 4 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control, Northeast Petroleum University, Daqing 163318, China – name: 1 Sanya Offshore Oil & Gas Research Institute, Northeast Petroleum University, Sanya 572025, China; nanhou@nepu.edu.cn |
| Author_xml | – sequence: 1 givenname: Nan orcidid: 0000-0002-3827-2357 surname: Hou fullname: Hou, Nan – sequence: 2 givenname: Weijian orcidid: 0009-0001-2134-0325 surname: Li fullname: Li, Weijian – sequence: 3 givenname: Yanhua orcidid: 0000-0002-3649-9160 surname: Song fullname: Song, Yanhua – sequence: 4 givenname: Mengdi orcidid: 0009-0002-1840-5711 surname: Chang fullname: Chang, Mengdi – sequence: 5 givenname: Xianye orcidid: 0000-0003-4094-8915 surname: Bu fullname: Bu, Xianye |
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| Keywords | complex network state estimation randomly occurring multiple delays random couplings binary encoding schemes |
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| SubjectTerms | binary encoding schemes Communication complex network Data compression Data transmission Design Markov processes random couplings Random variables randomly occurring multiple delays Sensors state estimation |
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| Title | Non-Fragile Estimation for Nonlinear Delayed Complex Networks with Random Couplings Using Binary Encoding Schemes |
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