Resilient Monitoring Systems: Architecture, Design, and Application to Boiler/Turbine Plant

García, Humberto E.; Lin, Wen Chiao; Meerkov, Semyon M.; Ravichandran, Maruthi T.

doi:10.1109/tcyb.2014.2316003

Cited by 29 publications

(15 citation statements)

References 20 publications

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“…Our preliminary results on RMS have been reported in conference presentations [25][26][27][28][29] and summarized in article [30]. The current paper, along with reviewing and extending these results, introduces a decentralized RMS based on plant decomposition with knowledge fusion, as a means for combating the curse of dimensionality.…”

Section: Related Literaturementioning

confidence: 83%

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Resilient plant monitoring systems: Techniques, analysis, design, and performance evaluation

García

Meerkov

Ravichandran

2015

Journal of Process Control

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a b s t r a c tResilient monitoring systems (RMS) are sensor networks that degrade gracefully under malicious attacks on their sensors, causing them to project misleading information. This paper develops techniques to ensure resiliency, namely: active data quality acquisition, process variable and plant condition assessments, sensor network adaptation, and plant decomposition with knowledge fusion. Based on these techniques, we design a RMS for power plants and investigate its performance under various cyberphysical attacks. In all scenarios considered, the system offers effective protection against misleading information and identifies the plant condition -normal or anomalous -in a reliable and timely manner.

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Section: Related Literaturementioning

confidence: 83%

“…The proof of almost sure convergence is given in the Appendix. The proof of convergence in probability can be found in [30].…”

Section: Process Variable Pmf Assessment Using a Single Sensormentioning

confidence: 99%

Resilient plant monitoring systems: Techniques, analysis, design, and performance evaluation

García

Meerkov

Ravichandran

2015

Journal of Process Control

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“…While the steady state performance of this system has been shown to be satisfactory (see [1]), the transients have not: the adaptation time grows exponentially as a function of the number of sensors in the network, N S . This phenomenon, which arises in many engineering problems and which Richard Bellman called the "curse of dimensionality", is the main topic addressed in the current paper.…”

Section: Introductionmentioning

confidence: 98%

“…Details of the calculations carried out at each of these layers can be found in [1]- [4]. While the steady state performance of this system has been shown to be satisfactory (see [1]), the transients have not: the adaptation time grows exponentially as a function of the number of sensors in the network, N S .…”

Section: Introductionmentioning

confidence: 99%

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Combating curse of dimensionality in resilient plant monitoring systems: Overlapping decomposition and knowledge fusion

García

Meerkov

Ravichandran

2014

2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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Resilient plant monitoring systems (RPMS) are sensor networks that degrade gracefully under cyber-physical attacks. In the previous work, we have developed an adaptive four-layer RPMS architecture and evaluated its performance under various attack scenarios. While the steady state performance of this system has been shown to be satisfactory, the transients have not: adaptation time grows exponentially as a function of the number of states in the network. The current paper is intended to provide a method for combating this curse of dimensionality. The approach is based on the idea of overlapping plant decomposition and subsequent fusion of knowledge derived in the overlapping subnetworks. In this paper such a monitoring system is developed (five-layer architecture), analyzed, and shown to have desirable steady state and, to a certain extent, transient characteristics.

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An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

Yadegar

Meskin

Haddad

2019

Adaptive Control & Signal

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In this paper, we present a control design framework wherein an adaptive-based corrective signal is augmented to the output of the nominal controller in order to suppress or counteract the effect of malicious actuator attacks. Due to the unavailability of full-state measurements, a nonminimal controllable realization of the nominal closed-loop system is used to design the corrective signal predicated on partial state information. Two illustrative numerical examples are given to demonstrate the efficacy of the proposed adaptive control architecture. KEYWORDSactuator attacks, adaptive control, cyber-physical systems, output feedback INTRODUCTIONCyber-physical systems (CPSs) have different meanings to different researchers and practitioners. The common thread in CPSs is the fact that they involve the integration of computation, communication, and physics working together in order to achieve required control objectives. These systems usually consist of networked agents, which include actuators, sensors, communication devices, and control processing units. 1 Since communication and computation devices are becoming cheaper and smaller, they are extensively used to interact directly with the physical environment, and hence, the use of these devices is becoming ubiquitous. Therefore, sensors and actuators, which collect, exchange, and use data in a CPS, are designed such that they can be interfaced with network and communication devices. The main reason of the advent of CPSs is the tight integration of the physical processes they control and computational resources and communication capabilities that exist in modern engineering systems. 2 The CPS architectures are being used in many different applications such as power systems, transportation systems, process control systems, large-scale manufacturing systems, ecological systems, and health care systems. Many of these applications involve safety-critical systems, and hence, any failures or cyber-attacks can cause catastrophic damage to the physical system being controlled resulting in drastic societal ramifications.Due to the open communication and computation platform architectures of CPS, one of the most important challenges in these systems is their vulnerability to malicious cyber-attacks. Cyber-attacks can severely compromise system stability, performance, and integrity. In particular, malicious attacks in feedback control systems can compromise sensor measurements as well as actuator commands to severely degrade closed-loop system performance and integrity. Cyber-attacks are continuously becoming more sophisticated and intelligent, and hence, it is vital to develop algorithms that can suppress their effects on CPSs. 3 Depending on the a priori system knowledge and the available resources of the attacker, different malicious attacks can be injected into CPSs. 4 The available resources of the attacker can be generally categorized as disclosure and disruption Int J Adapt Control Signal Process. 2019;33:943-955.wileyonlinelibrary.com/journal/acs

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Resilient Monitoring Systems: Architecture, Design, and Application to Boiler/Turbine Plant

Cited by 29 publications

References 20 publications

Resilient plant monitoring systems: Techniques, analysis, design, and performance evaluation

Resilient plant monitoring systems: Techniques, analysis, design, and performance evaluation

Combating curse of dimensionality in resilient plant monitoring systems: Overlapping decomposition and knowledge fusion

An output‐feedback adaptive control architecture for mitigating actuator attacks in cyber‐physical systems

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