Resilient Control Systems—Basis, Benchmarking and Benefit

Rieger, Craig; Schultz, Kevin; Carroll, Thomas E.; McJunkin, Timothy R.

doi:10.1109/access.2021.3071874

Cited by 3 publications

(6 citation statements)

References 44 publications

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“…Such instances are frequently found in various time and geographic scales of power systems, autonomous driving, robotics, process engineering, civil security, etc. [7], [8]. From the perspective of control theory, a formal definition of resilience and its distinctive features to the established concepts of robustness and fault-tolerance need to be found.…”

Section: C: Controlmentioning

confidence: 99%

Toward Resilience in Mixed Critical Industrial Control Systems: A Multi-Disciplinary View

et al. 2022

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Future industrial control systems face the need for being highly adaptive, productive, and efficient, yet providing a high level of safety towards operating staff, environment, and machinery. These demands call for the joint consideration of resilience and mixed criticality to exploit previously untapped redundancy potentials. Hereby, resilience combines detection, decision-making, adaption to, and recovery from unforeseeable or malicious events in an autonomous manner. Enabling the consideration of functionalities with different criticalities, mixed criticality allows prioritizing safety-relevant over uncritical functions. While both concepts on their own feature a huge research branch throughout various disciplines of engineering-related fields, the synergies of both paradigms in a multi-disciplinary context are commonly overlooked. In industrial control, consolidating these mechanisms while preserving functional safety requirements under limited resources is a significant challenge. In this contribution, we provide a multidisciplinary perspective of the concepts and mechanisms that enable criticality-aware resilience, in particular with respect to system design, communication, control, and security. Thereby, we envision a highly flexible, autonomous, and scalable paradigm for industrial control systems, identify potentials along the different domains, and identify future research directions. Our results indicate that jointly employing mixed criticality and resilience has the potential to increase the overall systems efficiency, reliability, and flexibility, even against unanticipated or malicious events. Thus, for future industrial systems, mixed criticality-aware resilience is a crucial factor towards autonomy and increasing the overall system performance.

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Section: C: Controlmentioning

confidence: 99%

Toward Resilience in Mixed Critical Industrial Control Systems: A Multi-Disciplinary View

et al. 2022

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“…Considering time and data in the form of Fig. 2, the resilience impact on the system can be illustrated [4]. The resilience of a system can be understood by its ability to initially reduce the impact of a disturbance (resist stage) and recover from it in both the short-(respond) and long term (restore).…”

Section: Ot Architectural Interactionsmentioning

confidence: 99%

“…In our case, the proposed methods are distributed, building upon prior considerations for cyber resilience through multiagent architectures [2]. In this context, while practical metrics have been defined in the past [3], the ability to adapt [4] to what may be unexpected failures such as cyber-attack are at the heart of the definition to resilience [5]. Therefore, in this work, as a means to evaluate the resilience to the proposed cyber and physical mitigations, the concept of an OT, systemic fuzzer is introduced.…”

Section: Introductionmentioning

confidence: 99%

Trade-off Analysis of Operational Technologies to Advance Cyber Resilience through Automated and Autonomous Response to Threats

Rieger

Kolias

Ivans

et al. 2022

2022 Resilience Week (RWS)

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The advancement of cyber resilience requires a preliminary stage of characterizing the trade-off space of mitigation options and how these might affect the stability and determinism of an operational technology (OT). This first step will set the stage for the proper cyber-secure and cyber-resilient design and confirm the affects that can be considered and approved by the OT and the security groups. To provide a baseline for this discussion, this paper provides a consideration of the cyberphysical interactions, possible mitigation steps against certain attacks and their corresponding affects that lend to the security design planning and evaluation process. As an integral part of the proposed scheme this work introduces the concept of systemwide fuzzer, i.e., a tool that manipulates the system state in an effort to determine mitigation response sequences that minimize detriments and maximize benefit in accordance with specified operational requirements.

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“…Further considering that the gain in the controller will also be affected by uncertain factors and change, in the process of signal transmission between the factory and the controller, there are disturbances that will affect the gain of the controller, so the traditional control method will appear high vulnerability. The resilient control research based on the above uncertain system has stronger robustness and applicability, there have been some studies in this area 19‐23 . Chang et al 20 studies the state‐feedback resilient control problem for lateral motion regulation of an intelligent vehicle in the presence of randomly occurring uncertainties.…”

Section: Introductionmentioning

confidence: 99%

“…The resilient control research based on the above uncertain system has stronger robustness and applicability, there have been some studies in this area. [19][20][21][22][23] Chang et al 20 studies the state-feedback resilient control problem for lateral motion regulation of an intelligent vehicle in the presence of randomly occurring uncertainties. In Reference 21, the sampled-data resilient control problem was solved for hybrid nonlinear stochastic systems under periodic DoS attacks.…”

Section: Introductionmentioning

confidence: 99%

Quantized output feedback resilient control of uncertain systems under hybrid cyber attacks

Chang

2022

Adaptive Control & Signal

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This article investigates the output feedback resilient control problem of an uncertain system with two quantized signals under hybrid cyber attacks. First, for uncertain systems, the output signal of the system and the output signal of the controller are quantized once by the quantizers before they are passed to the controller and the system respectively, thus affecting the signal with quantization error terms. At the same time, The adverse effects of hybrid cyber attacks, including denial-of-service attacks and deception attacks, are also taken into account during the signaling process. In this article, a guaranteed cost resilient controller design method is proposed for the above situation so that the closed-loop system can be guaranteed to be stable or to meet the given performance index. In addition, by solving the given set of linear matrix inequalities, the design conditions for the relevant parameters required for the resilient controller can be obtained.Finally, the validity of the design method can be verified by simulation.

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Resilient Control Systems—Basis, Benchmarking and Benefit

Cited by 3 publications

References 44 publications

Toward Resilience in Mixed Critical Industrial Control Systems: A Multi-Disciplinary View

Toward Resilience in Mixed Critical Industrial Control Systems: A Multi-Disciplinary View

Trade-off Analysis of Operational Technologies to Advance Cyber Resilience through Automated and Autonomous Response to Threats

Quantized output feedback resilient control of uncertain systems under hybrid cyber attacks

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