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Robustness and evolvability of biological systems
Published in Karthik Raman, An Introduction to Computational Systems Biology, 2021
A common and important device for robustness is redundancy, or the existence of multiple alternate components/fail-safe mechanisms to achieve a particular end. For instance, there could be a pair of isozymes in a cell, which can compensate for one another in the event of the loss of a single enzyme. In this case, the alternate components may be nearly identical. On the other hand, systems may also have diverse mechanisms, where components very different from one another can compensate for losses. Such “distributed robustness” [6] is a common occurrence in evolved biological systems, where there exist multiple heterogeneous components and modules with overlapping functions. This is also a consequence of events such as gene duplications in the evolutionary history of the organism.
Fault detection scheme for a road vehicle with four independent single-wheel electric motors and steer-by-wire system
Published in Johannes Edelmann, Manfred Plöchl, Peter E. Pfeffer, Advanced Vehicle Control AVEC’16, 2017
Bruno dos Santos, António Lopes, Rui Esteves Araújo
System redundancy could be explored in order to achieve high safety and robustness requirements. The redundancy available in multi-motor electric vehicles should be exploited, in the event of an actuator failure, to redistribute the control effort among the remaining working actuators such that stability is retained and recover to a safe state. Also (Zhang, Cocquempot, Jiang, & Yang 2013) and (Rongrong & Junmin 2011) points the importance of using fault detection and identification (FDI) scheme with fault tolerant control (FTC) systems in order to actively reconfigure the system in order to mitigate the faults effects. Several works have been presented related to the detection of fault in electric vehicles. In (Ho & Ossmann 2014) it is used structured residuals in order to detect and isolate fault in sensors and actuators. In this work the linear track-model with side slip state is extended to the new type of powertrain is used.
Communication systems and network technologies
Published in Kennis Chan, Future Communication Technology and Engineering, 2015
Traditional software testing methods are mostly used to validate whether the software’s behaviour accords with its demands, namely function testing or not. The abnormal test is often not paid enough attention. With the software used in the important fields of politics, military and finance, the robustness of software has been paid more and more attention. Robustness describes the degree of correctly running its functions of a system or a component in high intensity input environment or in an invalid data input. As the input data from different systems are different, the abnormal input of robustness is different too. Therefore it leads to the low reliability of the robustness test case. At the same time, robustness testing needs the test case which must cover all possible abnormalities or attack modes. The number of test cases is usually very high, which makes the development of robustness test cases more difficult.
A network science-based assessment methodology for robust modular system architectures during early conceptual design
Published in Journal of Engineering Design, 2020
Giota Paparistodimou, Alex Duffy, Robert Ian Whitfield, Philip Knight, Malcolm Robb
Robustness is an essential attribute for engineering systems as it is an architectural aspect of resilience (Department of Defense 2011), thus constitutes a vital design objective when developing large-scale engineering systems. Robustness reflects on both the resilience and survivability of the complex system in the architectural level (Department of Defense 2011; Kott and Abdelzaher 2016). The USA Office of the Assistant Secretary of Defense for Homeland Defense and Global Security (2015) acknowledged that ‘today’s space architectures designed and deployed under conditions more reflective of nuclear war-fighting deterrence than conventional war-fighting sustainability, lack, in general, the robustness that would normally be considered mandatory in such vital war-fighting services’. Redundancy is a key design approach that promotes the robustness of systems. Modularity and redundancy are inherently conflicting concepts, as redundancy typically introduces connectivity in systems, whereas modularity intends to minimise connectivity between modules.
Evaluation criteria for holonic control implementations in manufacturing systems
Published in International Journal of Computer Integrated Manufacturing, 2019
It is inevitable that faults will occur within a manufacturing system. These faults might be the result of programming errors, machine or controller breakdowns, or communication failures. Fault tolerance refers to the ability to remain operational with a useful degree of system stability, and is a critical indicator of system robustness. The evaluation criteria for fault tolerance are based on the following: Fault isolation – it is critical for control implementations to limit the propagation of errors, i.e. to minimize the effects of an error on other components of the system. The isolation of the fault minimizes the impact of the disturbance on the system.Fault detection – for a system to be tolerant of faults, it is essential that faults are identified when they occur. Only when a fault is detected is it possible for the system to react.Fault handling – it is desired for the system to react in the event of a detected fault in order to ensure system stability and reduce the effect on the overall performance.
Structural complexity and robustness of supply chain networks based on product architecture
Published in International Journal of Production Research, 2018
Jessica Olivares Aguila, Waguih ElMaraghy
Robustness, resilience and reliability have been used in the SC context as a characteristic of SC resistance against disruptions (Ivanov 2018). Generally, robustness is defined as the ability to cope with errors during execution. In contrast, resilience is referred to as the ability to return to the original state or a better state after disruption (Christopher and Peck 2004). Some authors consider that robustness comes back to an inferior level after disruption (Asbjørnslett 2009; Spiegler, Naim, and Wikner 2012). According to Ivanov (2018), robustness is related to the creation of resource excessiveness in order to prevent failures and deviations in the process. This redundancy of resources will allow flexibility of decisions in future scenarios. Similarly, resilience is related to flexibility. But, the flexibility in terms of resilience will allow adaptation of the SC to change structurally and functionally in a quick manner. For that reason, these concepts are interconnected. Hence the discussion of their differences and similarities, whether they are trying to reduce vulnerabilities or remain robust in order to maintain value creation.