Robust System Design Research Articles

Artificial photosynthetic system for diluted CO2 reduction in gas-solid phase

Rational design of robust photocatalytic systems to direct capture and in-situ convert diluted CO2 from flue gas is a promising but challenging way to achieve carbon neutrality. Here, we report a new type of host-guest photocatalysts by integrating CO2-enriching ionic liquids and photoactive metal-organic frameworks PCN-250-Fe2M (M = Fe, Co, Ni, Zn, Mn) for artificial photosynthetic diluted CO2 reduction in gas-solid phase. As a result, [Emim]BF4(39.3 wt%)@PCN-250-Fe2Co exhibits a record high CO2-to-CO reduction rate of 313.34 μmol g−1 h−1 under pure CO2 atmosphere and 153.42 μmol g−1 h−1 under diluted CO2 (15%) with about 100% selectivity. In scaled-up experiments with 1.0 g catalyst and natural sunlight irradiation, the concentration of pure and diluted CO2 (15%) could be significantly decreased to below 85% and 10%, respectively, indicating its industrial application potential. Further experiments and theoretical calculations reveal that ionic liquids not only benefit CO2 enrichment, but also form synergistic effect with Co2+ sites in PCN-250-Fe2Co, resulting in a significant reduction in Gibbs energy barrier during the rate-determining step of CO2-to-CO conversion.

Robust Consensus Design of Uncertain Multiagent Systems With Bounded Gains and Incremental Nonlinear Interactions

Robust Consensus Design of Uncertain Multiagent Systems With Bounded Gains and Incremental Nonlinear Interactions

On the Positive Role of Noise and Error in Complex Systems

Noise and error are usually considered to be disturbances negatively affecting the behavior of a system. Nevertheless, from a systemic perspective, taking into account openness and incompleteness of complex systems, noise and error may assume a creative, constructive, and positive role in that they are a source of novelty that can trigger the reorganization of the system, the growth of complexity, and the emergence of new meaning. Examples of this phenomenon can be found in evolutionary phenomena driven by affordances, the formation of new attractors in dynamic systems responding to external perturbations, and improvisation in music. We argue that it is possible to identify general properties that enable the positive effect of noise and errors in complex systems, namely, multilevel organization, redundancy, incompleteness, and criticality. These properties play a major role in living systems and can guide the design of robust and adaptive artificial systems.

Robust control design of uncertain nonlinear systems: a self-compensating and self-tuning approach

ABSTRACT The problem of robust stabilisation is considered for a class of uncertain nonlinear systems with linear control term. It is not required that the unforced nominal (nonlinear) system has to be stable and/or has to be known, which means that its Lyapunov function need not be known and/or found for designing a stabilising control scheme to compensate the effect of uncertainty on the systems like some traditional control design approaches. For such a class of uncertain nonlinear systems, a design approach, called a self-compensating and self-tuning one, is presented whereby some robust state feedback control schemes can be easily synthesised. The proposed design approach can result in a linear state feedback control scheme with a time-varying control gain for such a class of uncertain nonlinear systems, which implies the simplicity of the design approach and control results. In addition, the system uncertainty is also not required to have to satisfy the matching conditions.

Advancing Healthcare Sustainability: Embracing MACH Architecture for Health IT System Transformation.

The emergence of new collaborative systems, coupled with uncontrolled data accumulation in traditional systems, poses sustainability challenges. This poster advocates the adoption of the MACH architecture as a potential framework to enhance sustainability and credibility within healthcare systems by offering robust system designs and management controls.

QACDes: QoS-aware context-sensitive design of cyber-physical systems

There is a lot of confusion and ambiguity regarding the quantification of the Quality of Service (QoS) of a system, especially for cyber-physical systems (CPS) involved in automating or controlling the operations in built environments and critical urban infrastructures, such as office buildings, factories, transportation systems, smart cities, etc. In these cases, the QoS, as experienced by human users, depends on the context in which they (i.e., humans) interact with these systems. Traditionally, the QoS of a CPS has been defined in terms of absolute metrics. Such measures are unable to take into account the variations in performance due to contextual factors arising out of different kinds of human interactions. Further, the QoS of a CPS has typically been evaluated by comparing the performance of the actual, fully realized system with the given QoS constraints only after the actual system has been completely developed. In the case of faults in the design exposed by observed deviations from the QoS constraints due to unpredicted variations in the contextual factors, the system needs to be re-designed and re-developed from scratch. Due to the above-mentioned reason, the validation approach associated with the traditional QoS makes the design of CPS systems prohibitively expensive, impractical, as well as infeasible in numerous application areas, such as civil and engineering works, since it may not be possible to modify the system once developed beyond a certain extent. To that end, we propose a context-aware definition of QoS of a CPS which facilitates the design of robust systems as elaborated below. In this paper, we define QoS as a function of contextual factors. A CPS designed according to our QoS specifications would always satisfy the QoS irrespective of any possible changes in contextual factors resulting from many different human interactions that may occur during operation of the system. We also present QACDes - a novel framework that provides a formal mechanism for validating the design of a CPS with respect to the specified QoS constraints at the design phase as well as after the realization of the actual system. QACDes can validate any given CPS, irrespective of its application domain, against a QoS guarantee: (A) as early as even before the design phase by comparing the proposed model with a baseline model, or (B) after the realization of the actual system based on logs collected from running the actual system. We consider a lighting control system that manages the light switches - switching it on/off depending on contextual factors, such as the presence of occupants and time of the day. Using the lighting control system in a building as a use case, we analyze and demonstrate the effectiveness of our QoS definition as well as the QACDes framework against the performance metric measured in an actual fully-realized CPS.

(Invited) Theoretical Insights in the Design of Active Sites and Environments to Guide Electrocatalytic Transformations for Sustainable Energy and Chemicals Production

Future strategies for sustainable energy and chemicals production will undoubtedly require the design of electrocatalytic systems that actively and selectively convert wastes such as CO2 emissions and biomass into chemicals and fuels. While enzymes elegantly integrate highly active centers together with adaptive nanoscale environments to selectively control catalytic transformations, they are limited industrially by their durability. The design of robust electrocatalytic materials and systems that can mimic the activity and selectivity of enzymes, however, has been hindered by our understanding of how such transformations proceed over inorganic materials and complex environments. Advances in theory, simulations, spectroscopy and characterization begin to allow us to track the molecular transformations and how they proceed in electrocatalytic systems at specific sites and within particular environments. This information can enable the design of unique surface ensembles and nanoscale environments that can efficiently catalyze specific molecular transformations. Herein we develop and use ab initio methods to examine the influence of anions, cations and solvents in complex electrochemical environments to carry out selective molecular transformations. More specifically, we discuss the electrocatalytic reduction of CO2 and aromatics to valuable chemical and pharmaceutical intermediates. We draw direct analogies between the elementary processes that govern these seemingly different systems. We explore the manipulation of different solvents (ionic liquids and water), electrolytes (effects of anions and cations), pH as well as different metals and electrochemical potential to drive the formation of 3D environments that aid in controlling these transformations. We expand the discussion to selective oxidation reactions and examine the design of mediators to enable the selective C-H bond activation.

Robust Electrocatalytic CO2 Reduction in Acid Enabled by "Molecularly Charged" Cobalt Phthalocyanine: A Profound Understanding from Electric Double Layer.

Electrocatalytic CO2 reduction (eCO2R) in acid holds promise in renewable electricity-powered CO2 utilization with high efficiency, but the hydrogen evolution reaction (HER) often prevails and results in a low eCO2R selectivity. Here, using cobalt phthalocyanine/Ketjen black (CoPc/KB) as the model catalysts, we systematically study the effect of active site density, operational current density, and hydrated cations on the acidic eCO2R selectivity and decipher it through the componential dynamics of electric double layer (EDL). The optimal CoPc-4/KB demonstrates a near-unity CO Faradaic efficiency from 50 to 400 mA cm-2 and superb operational stability (>120 h) at 100 mA cm-2. Aided by in situ Raman and infrared spectroscopies, we reveal that the proper cations establish an electrostatic shield for mitigating bulk H+ penetration and mediate the interfacial water structure for suppressing HER. This study should elicit further profound thinking on robust eCO2R system design from the perspective of multiphasic and dynamic EDL.

Enhanced Medical Image Segmentation using Transfer Learning with Res101_UNet: Experimental Insights and Comparative Performance Analysis

Throughout the past few decades, artificial intelligence and machine learning have seen a lot of active research in areas such as computer vision, natural language processing, and speech processing. As a result, deep learning models became state-of-the-art for computer vision tasks such as object detection, classification, segmentation, and other allied tasks. Of course, the fruits of this research are extended to the design of robust and reliable digital health systems as well as other applications in the healthcare sector. Many clinical applications require the automatic segmentation of medical images. Recent deep learning-based approaches have demonstrated state-of-the-art performance in medical image segmentation tasks. In addition to their ability to automatically extract features and generalize over large amounts of data, transfer learning based deep learning models have proven to be handy for data scared areas like medical domains. In this research, we investigate and demonstrate the efficacy of a DCNN-based transfer learning model -Res101_Unet, which has been trained and/or fine-tuned to execute tumor tissue segmentation tasks in MRI, CT, PET, and X-RAY pictures of medical organ scans with little data. For our experimental study, we employed two image datasets: 'Liver Tumor' and 'Gland Colon Cancer', both obtained from the Kaggle portal. This experimental setup includes an Open-Source segmentation model API. Our findings indicate that domain similarity-based transfer learning can be used to data-scarce sectors. We achieved 98.47% accuracy and a IoU score of 0.9891 on Liver Tumor data and 0.6956 accuracy and a IoU score of 0.7043 on gland colon dataset.

Bi-level game theoretic approach for robust design: A case study of path-generating four-bar

This study addresses the bi-level multi-objective optimization problems (MOP) that raise in robust design and optimization of engineering systems through establishing a state-of-the-art game theoretic scenario. A novel leader-follower decentralized decision-making scenario is proposed, leveraging the synergy of game theory, Robust Design Optimization (RDO), Monte Carlo Simulation (MCS), and Artificial Intelligence (AI). The proposed algorithm can be employed for optimum robust Pareto design of a wide range of dynamical systems. In order to achieve a robust design, both the mean and variance of each objective function are considered as players in a multi-agent game setting. In this approach, both Stackelberg and cooperative games are utilized to model the behaviors of the players. Genetic Programming (GP) meta-models are employed to capture the Stackelberg protocol between two levels specifically for constructing the follower's rational reaction set (RRS). Additionally, the Nash bargaining function is -utilize to model the cooperative behaviors among players in each level. The proposed approach is applied and demonstrated through a case study involving multi-objective robust design of planar four-bar linkages. In this manner, four objective functions are assigned to four players within the system. Each player is responsible for optimizing a specific objective criterion, namely the mean of tracking error (TE), variance of tracking error, mean of transmission angle and variance of transmission angle (TA) of the linkage. As a result, the four-objective optimization problem of mechanism is transformed into a single-objective robust synthesis problem. The comparisons of the results show a significant enhancement in the robust behavior of the linkage, while ensuring that deterministic criteria such as quality of motion and precision are preserved.

Seismic mitigation analysis of base-isolated structure with sliding magnetic bearings considering local-site conditions

Base-isolation systems applied in building structures and infrastructures often suffer from damage even failure during strong earthquakes. The adaptability of isolators to local sites is a main concern for the robust design of base-isolation systems. In this study, seismic mitigation analysis of base-isolated structure with newly-developed sliding hydro-magnetic bearing (HMB) and sliding implant-magnetic bearing (IMB) considering local-site conditions is carried out. Extension of modeling of sliding magnetic bearings is first conducted based on the data of shaking-table tests of a reduced-scale base-isolated structure. To assess the instantaneous frequency for quantifying sliding magnetic bearings’ resisting force, the Hilbert–Huang transform (HHT) is applied. The influences of local-site conditions upon mitigation performance of the sliding magnetic bearings are then addressed, including far-field and near-field, ground motions with and without velocity pulses, and hard-soil and soft-soil. For comparison purposes, the seismic mitigation analysis of the base-isolated structure attached with lead rubber bearing (LRB) and curved surface slider (CSS) is carried out as well. Numerical results show that the sliding magnetic bearings outperform the state-of-the-art seismic isolators in both seismic mitigation and deformation constraint, and the IMB has excellent applicability for engineering since its perfect adaptability to local sites. However, the LRB cannot achieve the desired seismic mitigation under near-field pulse-like ground motions.

Iterative algorithm to the generalized coupled Sylvester‐transpose matrix equations with application in robust and minimum norm observer design of linear systems

AbstractThis article consider a class of generalized coupled Sylvester‐transpose matrix equations which play an important role in control and systems theory. Based on the Jacobi iterative algorithm, the full‐row rank accelerated Jacobi gradient based iterative (RRAJGI) algorithm and the full‐column rank accelerated Jacobi gradient based iterative (CRAJGI) algorithm are proposed. By using the Frobenius norm of matrix and the trace function of matrix, the convergence of the algorithms are proved. The results show that the new algorithms are convergent for arbitrary initial matrices under the convergence number satisfies appropriate conditions. Numerical examples show that RRAJGI algorithm and CRAJGI algorithm have the advantages of faster convergence speed and higher convergence accuracy than other existing algorithms. Finally, an application example for robust and minimum norm observer design of linear systems is given.

High‐fidelity finite element modeling of the seismic response of prefabricated steel stairs

AbstractAdvancing the seismic resilience of building systems is an active area of research in earthquake engineering. Ensuring safe egress in and out of buildings during extreme events, such as an earthquake, is essential to supporting this effort. To this end, understanding the seismic response of stairs facilitates the robust design of egress systems to ensure they can remain operable after an earthquake. From prior earthquake events and physical experiments, it is understood that stairs with a flight to landing fixed connection at multiple levels within a building are prone to damage. In addition, the stair system with flight to landing fixed attachments may affect the dynamic behavior of the building. To accommodate seismic inter‐story drifts, a kinematically free connection between the stairs and landing has been proposed. Herein this connection is referred to as a drift‐compatible stair connection. To investigate and aid in the design of such a connection, a unique set of shake table experiments were conducted at the University of Nevada, Reno. In this paper, an overview of these tests is presented, and a high‐fidelity finite element model of the tested stair system is used to predict the responses measured during these experiments. Developed in Abaqus, the robustness of the modeled stair unit is investigated considering a variety of contrasting connections, namely, drift‐compatible connections, fixed ends and one end fixed and the other free. Results from these numerical simulations offer guidance towards development of simplified models of multi‐level stair subsystems. Such models are needed when investigating seismic resilience of building systems across a wider range of hazard levels. Furthermore, best practices observed utilizing the models developed and evaluated herein against experimental data will be useful for subsequent analysis of larger stair tower models, such as the 10‐story stair system implemented in the NHERI Tall Wood mass timber building with post‐tensioned rocking walls, conducted in 2023 at the UC San Diego Large High‐Performance Outdoor Shake Table.

A robust ultrasensitive transcriptional switch in noisy cellular environments

Ultrasensitive transcriptional switches enable sharp transitions between transcriptional on and off states and are essential for cells to respond to environmental cues with high fidelity. However, conventional switches, which rely on direct repressor-DNA binding, are extremely noise-sensitive, leading to unintended changes in gene expression. Here, through model simulations and analysis, we discovered that an alternative design combining three indirect transcriptional repression mechanisms, sequestration, blocking, and displacement, can generate a noise-resilient ultrasensitive switch. Although sequestration alone can generate an ultrasensitive switch, it remains sensitive to noise because the unintended transcriptional state induced by noise persists for long periods. However, by jointly utilizing blocking and displacement, these noise-induced transitions can be rapidly restored to the original transcriptional state. Because this transcriptional switch is effective in noisy cellular contexts, it goes beyond previous synthetic transcriptional switches, making it particularly valuable for robust synthetic system design. Our findings also provide insights into the evolution of robust ultrasensitive switches in cells. Specifically, the concurrent use of seemingly redundant indirect repression mechanisms in diverse biological systems appears to be a strategy to achieve noise-resilience of ultrasensitive switches.

Adaptive robust control for fuzzy underactuated mechanical systems: A Stackelberg game-theoretic optimization approach

This article proposes a Stackelberg game-theoretic optimization approach for adaptive robust controller design of fuzzy underactuated mechanical systems (UMSs). As a commonly encountered challenge, several factors render it difficult to further improve the control performance of these UMSs, such as the coupling effects and nonlinearities resulting from the underactuated structure. Meanwhile, various sources of unexpected time-varying uncertainties can further add to the difficulty in the controller design procedure pipeline. To overcome the above-mentioned issues and further enhance the system performance, a dual-parameter optimization framework is presented here for adaptive robust controller design, leveraging fuzzy set theory and Stackelberg game. In this development, the time-varying uncertainty is characterized via suitable membership functions; and thus the appropriate fuzzy UMS is established. Then, an adaptive robust controller with a leakage-type adaptation law is presented to tackle the uncertainty appropriately. To further improve the system performance considering the trade-off among the transient performance; the steady-state performance; and the control cost; a Stackelberg game-based dual-parameter optimization method is proposed to determine the Stackelberg strategy. It is rigorously proved in the developments here that the proposed controller design and parameters optimization method guarantees the desired deterministic system performance, i.e., uniform boundedness (UB) and uniform ultimate boundedness (UUB). Moreover, a series of numerical simulations based on a flywheel inverted pendulum (FIP) are performed, which illustrate the effectiveness and superiority of the proposed method.

Robust design of hybrid solar power systems: Sustainable integration of concentrated solar power and photovoltaic technologies

The global energy sector is now transitioning its structure towards carbon neutrality aided by renewable resource use. Despite its immense potential, solar energy contributes minimally to the global energy mix due to its intermittent nature and challenges with power demand fluctuations. Increased use of distributed solar sources alters market dynamics, necessitating conventional power plants to ramp up output during lower renewable energy production times and manage oversupply risks. Concentrated solar power (CSP) can contribute to grid decarbonization, but its high levelized cost of electricity (LCOE) impedes widespread adoption. This study proposes hybridizing CSP and photovoltaic (PV) technologies, aiming to leverage their synergy to maximize economic benefits. We develop a comprehensive process design framework that utilizes a robust multi-objective optimization (MOO) approach, which factors in techno-economic and environmental objectives while accounting for model uncertainty from resource prices and life cycle assessment indicators. Optimization results reveal that in Ivanpah, California, hybrid CSP + PV can reduce 41 % of LCOE and limit environmental impacts compared to standalone CSP plants. This robust framework also identifies design trends, such as a constant dependence on the PV field, and a trade-off between the installed area of the solar concentrators and the backup boiler operation. The optimal unit sizes, less susceptible to future market fluctuations and potential changes in the global warming potential (GWP) of technologies, contribute significantly to robust and sustainable energy planning decisions.

Reaching Consensus in the Byzantine Empire: A Comprehensive Review of BFT Consensus Algorithms

Byzantine fault-tolerant (BFT) consensus algorithms are at the core of providing safety and liveness guarantees for distributed systems that must operate in the presence of arbitrary failures. Recently, numerous new BFT algorithms have been proposed, not least due to the traction blockchain technologies have garnered in the search for consensus solutions that offer high throughput, low latency, and robust system designs. In this article, we conduct a systematic survey of selected and distinguished BFT algorithms that have received extensive attention in academia and industry alike. We perform a qualitative comparison among all algorithms we review considering message and time complexities. Furthermore, we provide a comprehensive, step-by-step description of each surveyed algorithm by decomposing them into constituent subprotocols with intuitive figures to illustrate the message-passing pattern. We also elaborate on the strengths and weaknesses of each algorithm compared to the other state-of-the-art approaches.

Performance Analysis of SNR in MIMO OFDM Downlink System

The goal of future wireless communications systems is to provide a wide variety of high quality high-rate services with minimum requirements on spectrum, power consumption and hardware complexity. Toward this end, proper system structures as well as robust system designs are required to meet the challenges in wireless transmissions, such as multipath fading, limited spectrum resource, and interference. Recent research results have unveiled the multiple-input multiple-output (MIMO) system as a potential candidate to play a key role in future wireless. A MIMO wireless system is commonly deployed by using multiple transmit and receive antennas. Early work on multi-antenna systems involves the use of antenna arrays at the receiver to provide spatial diversity against the random destructive effect of fading. There is a recent rich literature on employing multiple antennas at the transmitter and achieving diversity through space-time coding when there is no channel state information at the transmitter (CSIT), or through transmit beam forming when there is perfect CSIT.

A Comprehensive Review of Interactive System Architecture

This paper presents a detailed review of interactive software architecture (ISA). ISA has emerged as an important aspect in software engineering offering a framework that prioritizes user interaction, real-time responsiveness and adaptability. The paper explores various aspects crucial for the design, development, and maintenance of robust and scalable software systems. The review encompasses architectural patterns, design principles, scalability, maintainability, security, and emerging trends. The paper also examines the significance of ISA and challenges for the same. Objective: The objective of the paper is to provide a comprehensive understanding of the key considerations in interactive system architecture and how they impact the overall success of a software project. The paper also goes on to discuss the challenges and benefits of implementation of ISA Methodology: the study adopted a desktop approach by reviewing existing literature on the topic at hand so as to provide a simplified understanding of the interactive system architecture. Recommendations: at the end of the paper it provides recommendation on future developments in this field.

Tunable all-optical microwave logic gates based on nonreciprocal topologically protected edge modes

All-optical logic gates have been studied intensively owing to their potential to enable broadband, low-loss and high-speed communications. However, poor tunability has remained a key challenge in this field. In this work, we propose a Y-shaped structure composed of Yttrium Iron Garnet (YIG) layers that can serve as tunable all-optical logic gates, including, but not limited to, OR, AND and NOT gates, by applying external magnetic fields to magnetize the YIG layers. Our findings reveal that these logic gates are founded on protected one-way edge modes, where by tuning the wavenumber k of the operating mode to a sufficiently small (or even zero) value, the gates can become nearly immune to nonlocal effects. This not only enhances their reliability but also allows for maintaining extremely high precision in their operations. Furthermore, the operating band itself of the logic gates is also shown to be tunable. We introduce a straightforward and practical method for controlling and switching these gates between "work", "skip", and "stop" modes. These findings have potentially significant implications for the design of high-performance and robust all-optical microwave communication systems.