Distributed Recursive State Estimation for a Class of Multi-Rate Nonlinear Systems Over Wireless Sensor Networks Under FlexRay Protocols

Shen, Yuxuan; Wang, Zidong; Dong, Hongli; Li, Guoping; Alsaadi, Fawaz E.

doi:10.1109/tnse.2022.3229889

Cited by 8 publications

(4 citation statements)

References 52 publications

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“…The fault involved in this article is a sudden and random fault, which is very common in industrial processes. Its dynamic model is represented by Equation (5). When a fault signal occurs, it will be detected by the system in a timely manner, and then the fault estimation scheme will be used to estimate it.…”

Section: Energy Harvestermentioning

confidence: 99%

“…It should be pointed out that both the above-mentioned estimation schemes exhibit significant deviation when it comes to the nonlinearities/uncertainties. As a suboptimal Kalman-type estimation scheme, recursive state estimation is applied to accommodate the nonlinearities/uncertainties in the sense of the upper bound on estimation error covariances being minimized [ 4 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

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A Joint State and Fault Estimation Scheme for State-Saturated System with Energy Harvesting Sensors

Zhu,

Huang,

Shi

et al. 2024

Sensors

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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.

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Section: Energy Harvestermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Joint State and Fault Estimation Scheme for State-Saturated System with Energy Harvesting Sensors

Zhu,

Huang,

Shi

et al. 2024

Sensors

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show abstract

“…To be more specific, following the idea of intuitive CPC, a knowledge-based intelligent cost model has been built in [30] to estimate the manufacturing cost at the conceptual design stage, where both material cost and operation costs (of machines) have been considered. Using the analogical CPC approach, a novel cost model has been given in [40] to estimate the operational machining costs of the microelectronic discharge. However, in such a model, the variation of workpiece/electrode parameters would lead to the change of machining time, limiting its wide applications to broader industrial scenarios.…”

Section: Literature Reviewmentioning

confidence: 99%

Reliable Cost Prediction and Control for Intelligent Manufacture: A Key Performance Indicator Perspective

Geng,

Mousavi,

Markatos

et al. 2024

IJNDI

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Article Reliable Cost Prediction and Control for Intelligent Manufacture: A Key Performance Indicator Perspective Hang Geng 1,*, Alireza Mousavi 2, Nikolaos Grigorios Markatos 2, Kai Chen 1, and Xuan Gou 1 1 School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China 2 Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB8 3PH, United Kingdom * Correspondence: Hang.Geng@uestc.edu.cn Received: 10 July 2023 Accepted: 11 October 2023 Published: 26 March 2024 Abstract: Intelligent manufacturing is facing significant challenges in adapting to the ever-changing equipment, instrumentation, process and economics. Such a trend together with the pressure to reliably control and contain production costs means that frequent adjusting decisions are required to adapt to incessant volatility imposed on manufacturing systems. Under this circumstance, cost-effective and quality-guaranteed manufacturing strategies would be the most logical route to reducing production costs. In this paper, a novel dynamical cost prediction and control (CPC) model is proposed to support collective decision-making in intelligent manufacturing, where the model output is the real-time prediction of possible manufacturing costs, while the inputs are generic manufacturing key performance indicators covering inventory, product quality, production efficiency, resource utilisation and environmental impact. This proposed CPC model distinguishes itself from existing ones for its capability to translate manufacturing data (at both the physical level and operation management level) into financial metrics that contribute to forming a common language between engineering, financial and administrative departments of an enterprise. The case study about the assembly line of optoelectronic devices demonstrates that, although different enterprise departments have different priorities, our CPC model helps them to achieve certain consensus on intended production that finally creates satisfactory profitability for the company at controlled manufacturing costs.

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“…On another scientific frontier, scheduling protocols are perceived as a positive and effective approach to decreasing the communication burden. At present, in the industrial field, the round robin (RR) protocol, 17 random access (RA) protocol, 18 WTOD protocol 19 and FlexRay protocol 20 are extensively introduced. Additionally, the recursive filtering issue of multisensor networks with WTOD protocol has been discussed in Reference 21.…”

Section: Introductionmentioning

confidence: 99%

Non‐fragile observer‐based security control for networked systems via event‐triggered WTOD protocol

Liu,

Wang,

et al. 2024

Intl J Robust & Nonlinear

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This paper investigates the security control issue for fuzzy networked systems with uncertainty under false data injection (FDI) and aperiodic denial‐of‐service (ADoS) attacks via sliding mode approach. To mitigate the communication burden, a novel mechanism compromising the advantages of the adaptive event‐triggered (AET) scheme and weighted try‐once‐discard (WTOD) protocol is proposed. In particular, the triggered threshold with real‐time characteristics varies with the measurement outputs. To be specific, the shared insecure communication network can be subjected to hybrid attacks including the stochastic FDI attacks and ADoS attacks limited by duration and frequency. Moreover, the token‐dependent fuzzy non‐fragile observer (NFO) with norm‐bounded uncertainty and corresponding fuzzy control law are constructed by virtue of the Zero‐Order‐Hold (ZOH) strategy. Then, several sufficient criteria that guarantee the exponential stability of the system and the reachability of the specified sliding surface are given. Eventually, a numerical example is presented to verify the applicability of the proposed security control strategy.

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Distributed Recursive State Estimation for a Class of Multi-Rate Nonlinear Systems Over Wireless Sensor Networks Under FlexRay Protocols

Cited by 8 publications

References 52 publications

A Joint State and Fault Estimation Scheme for State-Saturated System with Energy Harvesting Sensors

A Joint State and Fault Estimation Scheme for State-Saturated System with Energy Harvesting Sensors

Reliable Cost Prediction and Control for Intelligent Manufacture: A Key Performance Indicator Perspective

Non‐fragile observer‐based security control for networked systems via event‐triggered WTOD protocol

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