Active Constraints Research Articles

A Fully Distributed Robust MPC Approach for Frequency and Voltage Regulation in Smart Grids With Active and Reactive Power Constraints

A Fully Distributed Robust MPC Approach for Frequency and Voltage Regulation in Smart Grids With Active and Reactive Power Constraints

Characterization and utilization of apple peel and grape stems extract constituents as green restraints for aluminum dissolution

Different flavone extracts from apple peel and aldehydes from grape stems were investigated as restraints of the anodic aluminum dissolution procedure in 60% H3PO4:40% H2SO4. The potential-limiting current correlation for Al anode was assessed and associated with regularly improving apple peel and grape stems extract concentration (100 to 1000 ppm range). The limiting current reduces whereas retardation effectiveness (%) increases as the concentrations of apple peel and grape stems extract rise. Apple peel/grape stems mixture extract is pondered to have the most retardation impact. Apple peel and grape stems extract retardation mechanism depends on the adsorption manner at the aluminum metal, which was confirmed via scanning electron microscopy (SEM) and UV-VIS-NIR spectra which reflect that elevated extract concentration (1000 ppm) have a hopeful and positive impact on the Al surface quality. The activation energy and activation constraints (changes in enthalpy, entropy, and Gibbs free energy) were established, and suggestions for powerful interaction between the additives and the aluminum surface were conveyed. The extract items were inspected via Fourier transform infrared spectroscopy and Gc-mass. The apple peel and grape stems extract establish perspective as a natural electro-polishing green restraint. The weight loss data obtained is in excellent conformity with the result obtained by electrochemical measurements. The synergistic influence between apple peel/grape stems (S = 1.64–1.83 ) is noticeable. The lowest Ra and PV estimates are recorded via an apple peel /grape stems mixture, which achieves the greatest reflectance estimate and retardation effectiveness. This is recognized high active site number for apple peel /grape stems mixture extract.

Data-Driven Model-Free Adaptive Containment Control for Uncertain Rehabilitation Exoskeleton Robots with Input Constraints

This paper presents a data-driven model-free adaptive containment control (MFACC) scheme for uncertain rehabilitation exoskeleton robots, where the robotic exoskeleton dynamics are uncertain with saturation constraints. To handle uncertainties of the robotic dynamics, a model-free adaptive control (MFAC) strategy is established by linearizing the robotic exoskeleton dynamics into an equivalent data model. Considering the integral additive effect of the traditional MFAC method, an improved MFAC controller is designed in this paper. Since actuators with saturation constraints constantly affect the safety of patients during rehabilitation training, we construct a new criterion function with active constraints for the critical function of the MFAC algorithm and adopt the Hildreth quadratic programming algorithm to find the constrained optimal solution to overcome this limitation. The proposed MFACC scheme is rigorously proven by the compression mapping method to demonstrate model-free stability. Finally, the proposed control scheme is verified to be effective by simulation studies of the robotic SimMechanics model.

Comparison of barriers to physical activity to levels of physical activity and psychological well-being based on the demographic environment in the vision impairment disability group

Barriers to physical activity in vision impairment are associated with increased inactivity and psychological well-being problems. Previous research has only identified constraints in physical activity without conducting an in-depth analysis of physical activity levels and psychological well-being. This study aims to explore the differences in physical activity barriers based on three different demographic environments regarding physical activity levels and psychological well-being. The method used was quantitative inferential with a cross-sectional design approach involving 90 respondents registered with the Indonesia Association of the Blind. Data were collected using the Barrier Questionnaire for People with Vision Impairment (BPAQ-VI), the Psychological Well-Being Scale (PWBS), and General Practice Physical Activity (GPPAQ). The data was processed using the one-way ANOVA test and the Tukey HSD via SPSS version 26. The study's results stated differences in physical activity barriers, physical activity levels, and psychological well-being in vision impairment groups living in urban centres, suburbs, and rural areas (p<0.05). It was concluded that the visionly impaired disability group living in the city centre had minimal barriers compared to the vision impairment group living in suburban and rural areas. Vision impairment groups living in urban centres have better physical activity and psychological well-being than those living in suburbs and rural areas. The study contributed to an increase in the number of fitness influencers among those with vision impairment. It raised awareness among sports practitioners to design innovative and friendly exercise methods and programs for the group. Keywords: Barrier Physical Activity, health, fitness and wellness, environment, psychological well-being, blind.

Active constraint control for the surgical robotic platform with concentric connector joints

Robotic minimally invasive surgery (MIS) has changed numerous surgical techniques in the past few years and enhanced their results. Haptic feedback is integrated into robotic surgical systems to restore the surgeon's perception of forces in response to interaction with objects in the surgical environment. The ideal exact emulation of the robot's interaction with its physical environment in free space is a very challenging problem to solve completely. Previously, we introduced the surgical robotic platform (SRP) with a novel concentric connector joint (CCJ). This study aims to develop a haptic control system that integrates an active constraint controller into a surgical robot platform. We have successfully established haptic feedback control for the surgical robot using constraint control and inverse kinematic relationships integrated into the overall positioning structure. A preliminary feasibility study, modelling, and simulation were presented.

An Economic Analysis of Dairy Sector in India with Special Reference to Milk Dairy Co-Operatives in Karnataka

Dairy activities play a predominate role in the Indian economy. Due to fail in agricultural crops the farmers not only depending upon cropping pattern alone, indeed they depend on other allied agricultural activities like poultry farming, fishing, agro based activities, family enterprises, food products. Among the allied agricultural activities, dairy is one of the prominent activities to the farmers. Dairying is not only cheap but also yield more returns. This is especially where more of woman are engaged in this activity. Due to various constraints in this dairy activity, co operative sector play a very important role in not only protecting the dairy activities but also promote it with various polices and packages of co operative sector. With this background the present study is more relevant as well to identify various issues of the cooperative dairy sector both in Karnataka and Tamilnadu.

Optimal switching of MPC cost function for changing active constraints

Model predictive control (MPC) allows for dealing with multivariable interactions, known future changes and dynamic satisfaction of constraints. Standard MPC has a cost function that aims at keeping selected controlled variables at constant setpoints. This work considers systems where the steady-state optimal active constraints change during operation. This situation is not handled optimally by standard MPC which uses fixed controlled variables for the unconstrained degrees of freedom. We propose a simple framework that detects the constraint changes and updates the controlled variables accordingly. The unconstrained controlled variables are chosen to be the reduced cost gradients, which when controlled to zero minimizes the steady-state economic cost. In this paper, the nullspace method for self-optimizing control is used to estimate the cost gradient using a static combination of the measurements. This estimated gradient is also used for detecting the current set of active constraints, which in particular allows for giving up constraints that were previously active. The proposed framework, here referred to as “region-based MPC”, is shown to be optimal for linear constrained systems with a quadratic economic cost function, and it allows for good economic performance in nonlinear systems in a neighborhood of the considered design points.

Stratospheric Hydration Processes in Tropopause‐Overshooting Convection Revealed by Tracer‐Tracer Correlations From the DCOTSS Field Campaign

AbstractHydration of the stratosphere by tropopause‐overshooting convection has received increasing interest due to the extreme concentrations of water vapor that can result and, ultimately, the climate warming potential such hydration provides. Previous work has recognized the importance of numerous dynamic and physical processes that control stratospheric water vapor delivery by convection. This study leverages recent comprehensive observations from the NASA Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign to determine the frequency at which each process operates during real events. Specifically, a well‐established analysis technique known as tracer‐tracer correlation is applied to DCOTSS observations of ozone, water vapor, and potential temperature to identify the occurrence of known processes. It is found that approximately half of convectively‐driven stratospheric hydration samples show no indication of significant air mass transport and mixing, emphasizing the importance of ice sublimation to stratospheric water vapor delivery. Furthermore, the temperature of the upper troposphere and lower stratosphere environment and/or overshoot appears to be a commonly active constraint, since the approximate maximum possible water vapor concentration that can be reached in an air mass is limited to the saturation mixing ratio when ice is present. Finally, little evidence of relationships between dynamic and physical processes and their spatial distribution was found, implying that stratospheric water vapor delivery by convection is likely facilitated by a complex collection of processes in each overshooting event.

An improved adaptive Kriging method for the possibility-based design optimization and its application to aeroengine turbine disk

Possibility-based design optimization (PBDO) can provide theoretical basis for the structural optimal design of fuzzy uncertainty model in engineering, so as to obtain the optimal design variables. The genetic algorithm (GA) based on adaptive Kriging method for PBDO requires high precision in the whole design space, while the region far from the limit state surface (LSS) of the constraint function has little effect on PBDO, thus greatly affects the computational efficiency. In order to improve the efficiency of PBDO, an improved adaptive Kriging method combined with active possibility constraint (I-AK-AC) is proposed in this paper. In I-AK-AC, the enhanced expected improvement learning function is first put forward to promote the convergence efficiency of Kriging model by reducing the accuracy of the region far from the LSS of the constraint function. Whereafter, the active possibility constraint is identified, and only the boundaries of active possibility constraint need to be approximated precisely by Kriging model. By these ways, the convergence speed of Kriging model is further ameliorated without affecting the computational accuracy, and the efficiency of PBDO is significantly improved. Three test examples and an engineering application of aeroengine turbine disk illustrate the validity and accuracy of the proposed I-AK-AC.

The impact of new millennium crises on the power of Islamic banks in deposit markets

AbstractWe investigate the impact of three crises on the power of Islamic banks in deposit markets: the Global Financial Crisis, 2007–2009 (GFC), the Arab Spring political crisis, 2011–2013, and the COVID‐19 health crisis, 2020–2022. Applying difference‐in‐difference (DID) and GMM techniques to panel data for 2004–2022, we find that the power of Islamic banks increased in countries most affected by the GFC, but only for oil‐exporters, as elevated oil prices inflated deposited liquidity. In contrast to the GFC, the market power of countries highly affected by the Arab Spring decreased as depositors withdrew en masse. For these countries, oil export status was irrelevant, and whilst government integrity is significant, it accounts for a small amount of heterogeneity in the country‐level cross‐section due to widely held public attitudes towards institutions during the crisis. For COVID‐19, the market power of Islamic banks initially increased at the outset of the pandemic due to a surge in precautionary deposits, but later decreased due to economic activity constraints. The stringency of lockdowns had little effect on market power in countries that suffered the highest COVID‐19 death rates. These and other findings specific to each crisis provide a rich array of private and public policy implications relevant to crises of different types for bank liquidity crisis management, financial conduct policies, and state‐backed lending stimulus packages.

Examining the Relationship Between Leisure Time Physical Activity Constraints and Healthy Lifestyle Behaviors Among University Students

Examining the Relationship Between Leisure Time Physical Activity Constraints and Healthy Lifestyle Behaviors Among University Students

Understanding the delay in identifying Sudan Virus Disease: gaps in integrated disease surveillance and response and community-based surveillance to detect viral hemorrhagic fever outbreaks in Uganda, September 2022

BackgroundEarly detection of outbreaks requires robust surveillance and reporting at both community and health facility levels. Uganda implements Integrated Disease Surveillance and Response (IDSR) for priority diseases and uses the national District Health Information System (DHIS2) for reporting. However, investigations after the first case in the 2022 Uganda Sudan virus outbreak was confirmed on September 20, 2022 revealed many community deaths among persons with Ebola-like symptoms as far back as August. Most had sought care at private facilities. We explored possible gaps in surveillance that may have resulted in late detection of the Sudan virus disease (SVD) outbreak in Uganda.MethodsUsing a standardized tool, we evaluated core surveillance capacities at public and private health facilities at the hospital level and below in three sub-counties reporting the earliest SVD cases in the outbreak. Key informant interviews (KIIs) were conducted with 12 purposively-selected participants from the district local government. Focus group discussions (FGDs) were conducted with community members from six villages where early probable SVD cases were identified. KIIs and FGDs focused on experiences with SVD and Viral Hemorrhagic Fever (VHF) surveillance in the district. Thematic data analysis was used for qualitative data.ResultsForty-six (85%) of 54 health facilities surveyed were privately-owned, among which 42 (91%) did not report to DHIS2 and 39 (85%) had no health worker trained on IDSR; both metrics were 100% in the eight public facilities. Weak community-based surveillance, poor private facility engagement, low suspicion index for VHF among health workers, inability of facilities to analyze and utilize surveillance data, lack of knowledge about to whom to report, funding constraints for surveillance activities, lack of IDSR training, and lack of all-cause mortality surveillance were identified as gaps potentially contributing to delayed outbreak detection.ConclusionBoth systemic and knowledge-related gaps in IDSR surveillance in SVD-affected districts contributed to the delayed detection of the 2022 Uganda SVD outbreak. Targeted interventions to address these gaps in both public and private facilities across Uganda could help avert similar situations in the future.

Optimal measurement-based cost gradient estimate for feedback real-time optimization

This work presents a simple and efficient way of estimating the steady-state cost gradient Ju based on available uncertain measurements y. The main motivation is to control Ju to zero in order to minimize the economic cost J. For this purpose, it is shown that the optimal cost gradient estimate for unconstrained operation is simply Jˆu=H(ym−y∗) where H is a constant matrix, ym is the vector of measurements and y∗ is their nominally unconstrained optimal value. The derivation of the optimal H-matrix is based on existing methods for self-optimizing control and therefore the result is exact for a convex quadratic economic cost J with linear constraints and measurements. The optimality holds locally in other cases. For the constrained case, the unconstrained gradient estimate Jˆu should be multiplied by the nullspace of the active constraints and the resulting “reduced gradient” controlled to zero.

Accelerated PMA and its application in reliability-based design optimization

This paper proposes a novel approach based on the performance measure approach (PMA), which is termed accelerated PMA (aPMA) to overcome the non-convergence of the advanced mean value(AMV) and extend it to the reliability-based design optimization (RBDO). In aPMA, a threshold value by using inequality is integrated with the formula of AMV to make the efficiency and robustness of searching for the minimum performance target point (MPTP) better. The threshold value is able to eliminate the unnecessary probabilistic constraint in the inverse reliability analysis, thereby reducing the risk of numerical instability in AMV. Meanwhile, a judgment condition is defined according to the threshold value and reliability index in the design optimization, in which the active deterministic constraints can be quickly identified and updated. In addition, the recommended aPMA is merged into the double loop method (DLM) to consolidate the accuracy, efficiency and robustness of that for the high-dimensional RBDO problem. Since reliability analysis and structural optimization are carried out simultaneously, the convergence rate is enhanced. Besides, both the efficiency and robustness of the proposed aPMA are firstly trialed on six numerical/structural examples along with its performance on RBDO is tested through three RBDO problems quoted, showing significant merits.

Rural planning evaluation and sustainable development potential in rural communes of Rehamna province (Morocco)

The evolution of rural settlement planning has the potential to improve regional sustainability through aligning components of human settlement ecosystems. In this study, we promoted the integration of sustainability in 23 rural communes of Rehamna province (central Morocco). We assessed rural development in four areas: location and infrastructure, resource availability, economic activity, and development constraints. The communes were divided into three categories based on their occupancy levels and planning directions: Vital Planning Area (VPA), Common Planning Area (PPA), and Initial Planning Area (IPA). The rural comprehensive development potential has maximum, minimum, and average values of 0.694, 0.176 and 0.429. The proportion of rural communes in low, medium, and high levels is 13.04%, 60.86%, 26.08%, and correspondingly. Due to their obvious location advantages, high level of integration between urban and rural development, and greater economic development vitality, communes that cross the mobility axe and have proximity to water resources more than make up for the drawback of the scarcity of background resources. As a result, these communes have good development potential. The second main hub of the province of Rehamna's urban development is in the north. The spatial distribution demonstrates the tendency to progressively increase around the center, adopting it as the core. This paper proposes a framework for rural communes to facilitate strategic spatial planning, providing a novel way to maximize rural development potential. Based on these findings, the paper suggests a new spatial framework for rural development that aims to enhance the development status of rural regions by addressing their planning needs. This study presents an analytical framework for government, institutions, stakeholders, and planners to construct effective rural development strategies, focusing on the essential indicators required for rural sustainability.

A sensitivity-based estimation method for investigating control co-design relevance

Abstract. Control co-design is a promising approach for wind turbine design due to the importance of the controller in power production, stability, load alleviation, and the resulting coupled effects on the sizing of the turbine components. However, the high computational effort required to solve optimization problems with added control design variables is a major obstacle to quantifying the benefit of this approach. In this work, we propose a methodology to identify if a design problem can benefit from control co-design. The estimation method, based on post-optimum sensitivity analysis, quantifies how the optimal objective value varies with a change in control tuning. The performance of the method is evaluated on a tower design optimization problem, where fatigue load constraints are a major driver, and using a linear quadratic regulator targeting fatigue load alleviation. We use the gradient-based multi-disciplinary optimization framework Cp-max. Fatigue damage is evaluated with time-domain simulations corresponding to the certification standards. The estimation method applied to the optimal tower mass and optimal cost of energy show good agreement with the results of the control co-design optimization while using only a fraction of the computational effort. Our results additionally show that there may be little benefit to using control co-design in the presence of an active frequency constraint. However, for a soft–soft tower configuration where the resonance can be avoided with active control, using control co-design results in a taller tower with reduced mass.

Green grant-free power allocation for ultra-dense Internet of Things: A mean-field perspective

Grant-free access, in which each Internet-of-Things (IoT) device delivers its packets through a randomly selected resource without spending time on handshaking procedures, is a promising solution for supporting the massive connectivity required for IoT systems. In this paper, we explore grant-free access with multi-packet reception capabilities, with an emphasis on ultra-low-end IoT applications with small data sizes, sporadic activity, and energy usage constraints. We propose a power allocation scheme aimed at maximizing throughput while minimizing power consumption by considering the traffic and energy constraints of IoT devices. Our approach employs a stochastic geometry framework and mean-field game theory to model and analyze the mutual interference among active IoT devices. Additionally, we utilize a Markov chain model to capture and track the queue length of IoT devices, enabling the derivation of the transmission success probability at steady-state. The simulation results illustrate the optimal power allocation strategy and evaluate the proposed approach’s performance in terms of packet transmission success probability and average delay.

The Art of Promotion in the Age of Social Media: A Study of Online Marketing by Daniel Asham

The subject of this research is the analysis of Daniel Arsham's marketing strategies in the field of art. The object of the research is the promotion of art in the context of social media. This paper deeply examines various aspects of the topic, including how Arsham overcomes the traditional time and space constraints of exhibition activities, using a combined online and offline approach to expand the audience and increase the visibility of his works. Special attention is paid to the use of social networks to interact with the public, whose impressions are enhanced by creating a unique experience of art perception. The study also analyzes Arsham's strategies for establishing links with business media, contributing to the promotion and increase of the commercial value of his works. The author notes the innovation and practical applicability of these marketing strategies in the art market, emphasizing their positive contribution to the formation of Daniel Arsham's art brand. The research methodology is based on an integrated approach that includes case study, observation, content analysis and interdisciplinary research methods, which allows for a comprehensive analysis of art and its marketing aspects. The results of the study show that Arsham has successfully increased the recognition and commercial value of his art through innovative marketing strategies, harmoniously combining art and business. The contribution of this research consists in an in-depth analysis of Daniel Arsham's marketing approaches and their impact on the branding of his works. In addition, the work illustrates the effectiveness and innovation of these strategies with concrete examples. The novelty of the research lies in the emphasis not only on Arsham's artistic work, but also on his use of marketing strategies to promote his work and form a personal brand. This interdisciplinary perspective provides a new theoretical framework and practical guidance for the art market and represents a significant revelation for artists and art professionals.

Carbon Neutrality Computational Cost Optimization for Economic Dispatch With Carbon Capture Power Plants in Smart Grid

To achieve carbon neutrality, reducing carbon emissions is crucial in dispatching problems in smart grid. Though renewable energy such as wind power has low carbon emissions, it suffers from random generation, which makes the thermal power necessary for a stable supply power system. To reduce carbon emissions, the thermal power plants are transformed into carbon capture power plants, which brings new challenges to economic dispatch algorithms. Besides, there are usually many constraints to keep the security operation of power systems, which incurs a large problem scale and high computational cost. Most existing methods either do not consider reducing carbon emissions, or suffer from high computational costs. In this paper, a framework for the carbon capture plants with wind power to reduce both running costs and carbon emissions is designed to support carbon neutrality. To reduce computational cost, initial-training and fine-tuning are used. A deep neural network is employed to describe the relationship between users' load and the constraints, which provides guides for finding the active constraints. Therefore, the problem scale can be significantly decreased, making the optimal dispatching strategy obtained quickly. The experimental results on real-world data show that the proposed framework can obtain the optimal strategy efficiently.

Lithologic Relationship and Structural Features of Crystalline Rocks in Ekiti, Southwestern Nigeria: A Geological Report on the Basement Complex

This paper investigates and report field relationship and structural features of the basement rocks in Ekiti, southwestern Nigeria. Systematic geological mapping reveals that Ekiti is underlain by migmatite-gneiss, quartz schist, quartzite, granite, and charnockite. These lithologies were intruded by series of aplite, dolerite, and pegmatite dykes. Structural deformations attributable to polycyclic orogenic activities manifested in all the basement rocks. Migmatite and its gneissic subunits form the country rock and exhibits complex folds, abundant quartz veins and haphazardly emplaced dykes. Foliation and lineament are oriented N-S, strike values range between N5oE -N18oE with westerly dip of 72º to 84º. Quartzite and quartz schist exhibits distinctive joint and fracture system which runs parallel to one another while minor ones are oblique. The polymetamorphic terrain has older tectonic fabrics massively overprinted by younger ones. The gneiss units are porphyroblastic to granoblastic, xenoliths of varying sizes are embedded within the granite bodies indicating the magmatic liquid was forcefully injected into the country rock. The presence of parallel fractures in fine-grained granite indicate Ekiti area is a shear zone. The occurrence of dykes of heterogenous lithologies on single granite outcrop suggests pluton assemblage occur as discrete pulses during the intrusive phases. Contact relationship indicate age decreases from migmatite to granite-charnockite to microgranite while dykes are the youngest. Deformation, metamorphism, and intrusive phases are the dominant geodynamic features of Ekiti area while the regional and local changes in rocks resulted from environmental constraints of pressure, temperature, and fluid activity. The plutonic activities which accompanied orogenic events resulted in deformation which is genetically related to evolution and geodynamic setting of Ekiti area.