Event-Driven Observer-Based Smart-Sensors for Output Feedback Control of Linear Systems

Acho, Leonardo

doi:10.3390/s17092028

Cited by 10 publications

(9 citation statements)

References 36 publications

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“…These devices can make decisions based on the data they obtain through instrumental recording. Smart sensors have been used widely in academia and in research, with applications in the transportation and logistics industry [45], manufacturing [46], security [47], and healthcare [48], among many other examples. Toolmakers use machinery and equipment with smart sensors as well, making this class highly applicable to the sector.…”

Section: Digital Technologies For Product and Service Offeringsmentioning

confidence: 99%

A Decision-Making Framework for Implementing Digitalisation in the South African Tooling Industry

Dewa

Matope

2018

SAJIE

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In this paper, a decision-making framework for implementing the concept of digitalisation within the South African tool, die, and mould-making (TDM) industry context is developed and employed. The purpose of this framework is to answer the following question: "Which digital technologies currently available on the market can be employed to improve the efficiency of shop-floor operations in the South African TDM industry?" An exhaustive literature study of existing digital technologies is conducted. Thereafter, TDM processes requiring digitalisation are identified through knowledge engineering. Based on the system requirements analysis, digital technologies relevant to the South African TDM context are then proposed. OPSOMMINGŉ Besluitnemingsraamwerk vir implementering van die konsep van digitalisering binne die Suid-Afrikaanse matrysmaak industrie is ontwikkel en toegepas. Die doel van hierdie raamwerk is om die volgende vraag te beantwoord: "Watter digitale tegnologieë, wat nou beskikbaar is, kan gebruik word om die rendement van werkswinkel bedrywighede in die Suid-Afrikaanse matrysmaak industrie te verbeter?" ŉ Omvattende literatuurstudie van bestaande digitale tegnologieë is van stapel gestuur. Daarna is matrysmaak prosesse wat kan baat by digitalisering identifiseer. Op grond van die sisteemvereistes analise is digitale tegnologieë relevant tot die Suid-Afrikaanse matrysmaak konteks dan voorgestel. INTRODUCTIONThe production of tools, dies, and moulds (TDM) is a complex activity that requires a lot of expert knowledge and sound judgement. Due to the demand for customised and unique products, the process of tool-making requires great innovation, making it highly dependent on the craftsmanship of the toolmaker. The success of a project therefore depends on the experience and skill levels of the workers doing the job. This makes tool-making a skills-or people-driven exercise. The skills required in the TDM value chain include tool designing, project managing, toolmaking, cost estimating, and many more specialised roles. Schuh, Pitsch, Komorek, Schippers and Salmen [1] described the TDM industry as a knowledge-intensive and data-driven sector. During the fabrication of tools, dies, and moulds, many transactions that involve information exchange occur between toolmakers, their downstream customers, and their upstream suppliers, as illustrated in Figure 1. -Component information Design drawings and specifications Order Documents Design and production changes Order progress Toolmakers Raw material Suppliers OEM and Plastics Manufacturers Figure 1: Transactions during order processing in TDM operations [2]Due to the wide range of products it produces, the TDM industry is characterised by a huge variability of requirements and specifications for each final product. Figure 1 represents the nature of communication involved in processing orders in the TDM sector. A lot of production data is exchanged between toolmakers, their raw material suppliers, and their clients (usually overall equipment manufacturers [OEMs]). To a...

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Section: Digital Technologies For Product and Service Offeringsmentioning

confidence: 99%

A Decision-Making Framework for Implementing Digitalisation in the South African Tooling Industry

Dewa

Matope

2018

SAJIE

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“…Two different event conditions for fault-tolerant control are studied in [23] in terms of the system state and the system state error, respectively. A great deal of research progress has been made (see [24][25][26][27][28][29][30] and the references therein). It was shown in [31] that the deception attacks are viewed as the most dangerous attack behaviors and, therefore, some solutions against deception attacks have been proposed.…”

Section: Related Workmentioning

confidence: 99%

An Event-Triggered Fault Detection Approach in Cyber-Physical Systems with Sensor Nonlinearities and Deception Attacks

Liu

2018

Electronics

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In this paper, a general event-triggered framework is constructed to investigate the problem of remote fault detection for stochastic cyber-physical systems subject to the additive disturbances, sensor nonlinearities and deception attacks. Both fault-detection residual generation and evaluation module are fully described. Two energy norm indices are presented so that the fault-detection residual has the best sensitivity to faults and the best robustness to unwanted factors including additive disturbances and false information injected by attacker. Moreover, the filter gain and residual weighting matrix are formulated in terms of stochastic Lyapunov function, which can be conveniently solved via standard numerical software. Finally, an application example is presented to verify the performance of fault detection by comparative simulations. The prolonged battery life is experimentally evaluated and analyzed via a wireless node platform.

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“…The work in [28] proposed optimal and suboptimal consensus filters with event-triggered communication protocols to achieve energy efficiency via reducing unnecessary interactions among the neighboring sensors. More related studies can be found in recent publications [31,32,33,34,35,36,37,38,39,40,41] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Fault Estimation for Stochastic Systems over Multi-Hop Relay Networks with Randomly Occurring Sensor Nonlinearities and Packet Dropouts

2018

Sensors

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Wireless sensors have many new applications where remote estimation is essential. Considering that a remote estimator is located far away from the process and the wireless transmission distance of sensor nodes is limited, sensor nodes always forward data packets to the remote estimator through a series of relays over a multi-hop link. In this paper, we consider a network with sensor nodes and relay nodes where the relay nodes can forward the estimated values to the remote estimator. An event-triggered remote estimator of state and fault with the corresponding data-forwarding scheme is investigated for stochastic systems subject to both randomly occurring nonlinearity and randomly occurring packet dropouts governed by Bernoulli-distributed sequences to achieve a trade-off between estimation accuracy and energy consumption. Recursive Riccati-like matrix equations are established to calculate the estimator gain to minimize an upper bound of the estimator error covariance. Subsequently, a sufficient condition and data-forwarding scheme are presented under which the error covariance is mean-square bounded in the multi-hop links with random packet dropouts. Furthermore, implementation issues of the theoretical results are discussed where a new data-forwarding communication protocol is designed. Finally, the effectiveness of the proposed algorithms and communication protocol are extensively evaluated using an experimental platform that was established for performance evaluation with a sensor and two relay nodes.

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Event-Driven Observer-Based Smart-Sensors for Output Feedback Control of Linear Systems

Cited by 10 publications

References 36 publications

A Decision-Making Framework for Implementing Digitalisation in the South African Tooling Industry

A Decision-Making Framework for Implementing Digitalisation in the South African Tooling Industry

An Event-Triggered Fault Detection Approach in Cyber-Physical Systems with Sensor Nonlinearities and Deception Attacks

Event-Triggered Fault Estimation for Stochastic Systems over Multi-Hop Relay Networks with Randomly Occurring Sensor Nonlinearities and Packet Dropouts

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