Switching Policy Research Articles

Non-fragile event-triggered control for switched positive linear systems using state-dependent switching method

This article is concerned with the issues of stability and L1-gain characteristic for switched positive linear systems utilizing bumpless transfer (BT) technique and event-triggered (ET) strategy. Under the state-driven switching policy, a regulatory approach that couples BT and ET is introduced to attenuate the hybrid bumps stemming from switching and triggering moments. Compared with traditional state-driven switching, the proposed hysteresis switching can delay the occurrence of switching. Based on multiple copositive Lyapunov functions, a state feedback controller with an ET mechanism is constructed for positive systems, which reduces the update frequency of the actuator, and this control strategy is extended to the case of actuator faults. It is confirmed that the proposed control scheme can assure the positivity, stability, and L1-gain performance of the system. Additionally, the Zeno phenomenon is addressed via establishing a positive lower bound for the ET interval. Ultimately, simulation examples containing a turbofan engine model are provided to demonstrate the effectiveness of the proposed approach.

Modelling Nigerian residential dwellings: bottom-up approach and scenario analysis

Nigeria’s residential buildings consume a substantial amount of the country’s energy, so achieving a net-zero building sector with a rapidly growing population is a key challenge. To bridge the gap in research at a national level and support Nigeria’s commitment to an unconditional 20% reduction in emissions by 2030, this study develops bottom-up archetype models of different residential building typologies to estimate the energy and material use of Nigerian residential buildings. This creates an overview of the residential stock and how different archetypes perform. The study calculates a baseline energy and material use of Nigeria’s residential building stock using the BuildME tool and converts these data into CO2 emissions using a life-cycle assessment. Scenarios are modelled for 2020. Nigeria’s residential dwellings use approximately 0.3 kt of material per dwelling over a lifetime of 50 years and 2404 kWh/yr of energy per dwelling. Annualised, dwellings emit 2500 kgCO2-eq per dwelling due to material and energy use. Scenarios proposed for meeting Nigeria’s emissions targets will require improved energy efficiency, decarbonising the building envelope through a shift in construction materials and decarbonising grid electricity. Policy relevance This study provides a comprehensive analysis of the energy and material use of residential buildings in Nigeria, focusing on achieving the country’s commitment to a 20% reduction in emissions by 2030. It employs a bottom-up approach to model energy and material use, revealing the peculiarities of the dwelling stock across Nigeria’s four climatic zones. The study explores the implications of different policy scenarios on sustainable housing. The research suggests that meeting Nigeria’s emissions targets requires improved energy efficiency, a shift in construction materials and decarbonisation of grid electricity. It also highlights the potential benefits of a policy switch to materials such as timber, earthen blocks, adobe bricks and clay, which could significantly reduce construction-related emissions. These changes could improve the quality of life of households in Nigeria, combat climate change on a global scale and bring economic advantages to Nigeria.

Configuration and multistep switching of machines in dynamic hybrid MTS/MTO production systems

This study proposes the configuration of MTS-/MTO-dedicated and hybrid (switchable) machines under a multistep switching policy where each hybrid machine can be switched stepwise and compares it to the existing model with MTS-dedicated and hybrid machines under a group switching policy that makes all hybrid machines switch together. Since companies have been required to satisfy wide varieties of customers' needs in recent years, the dynamic hybrid make-to-stock (MTS) / make-to-order (MTO) production system–one of the flexible production strategies with superior efficiency and productivity–is widely adopted in the garment industry. This system contains MTS and MTO streams in a shared facility and holds dedicated and hybrid machines that can be switched between MTS and MTO production. The machine configuration and switching policy are essential factors to increase the effectiveness of this system; hence, the features of such components must be investigated. Numerical experiments demonstrate that the cost and the number of MTO customers waiting can be reduced by appropriately setting the multistep switching policy and the machine configuration. Effective operating rules can also be achieved using our proposed search heuristics. These results contribute to the improvement of the existing dynamic hybrid system and the expansion of its possible applications.

Over fifteen years of chloroquine withdrawal in Nigeria: a qualitative investigation into the execution of this policy by healthcare providers and amongst patients in a rural community.

Background Chloroquine (CQ) was once an important drug used in malaria treatment especially due to its affordability, ease of use and high anti-malarial efficacy. However, it was withdrawn from clinical practice in Nigeria in 2005 following a widespread of resistance cases reported in the public health domain. This study aims to ascertain the level of compliance with the policy on CQ withdrawal among patients, Patent and proprietary medicine vendors (PPMVs), Pharmacists and Physicians. Method A cross-sectional survey involving both online and offline data collection was carried out. A total of 582 participants were recruited and consisted of patients (N = 300), PMVs (N = 94), Physicians (N = 94), and Pharmacists (N = 94). Patients spanned across health services at primary health centers and hospitals in the Anaocha community. Result Our findings show that the patients were equally aware of what CQ is used for (χ² = 7.071, p = 0.215). However, significant disparities were observed in the knowledge, attitude, and perception of CQ resistance and its continual use among health professionals and PPMVs (χ² = 160.54 and 158.54, p = 0.000). Additionally, despite the chloroquine withdrawal policy in Nigeria, there was evident non-compliance among majorly PPMVs and other healthcare professionals. A few of patients continued to utilize CQ for malaria treatment and PPMVs were mostly likely to prescribe and stock CQ. Conclusion The study revealed that chloroquine use in Nigeria is still sustained notwithstanding the switch in the antimalarial drug policy from chloroquine to ACTs in 2005. Feasible implementation strategy through awareness program and campaign especially in the primary health centers across Nigeria and through associations such as Nigeria Association of Patent and Proprietary Medicine Dealers (NAPPMED), Pharmaceutical Society of Nigeria (PSN) and Nigeria Medical Association (NMA) is recommended.

Accelerating material discovery with a threshold-driven hybrid acquisition policy-based Bayesian optimization

Advancements in materials play a crucial role in technological progress. However, the process of discovering and developing materials with desired properties is often impeded by substantial experimental costs, extensive resource utilization, and lengthy development periods. To address these challenges, modern approaches often employ machine learning (ML) techniques such as Bayesian Optimization (BO), which streamline the search for optimal materials by iteratively selecting experiments that are most likely to yield beneficial results. However, traditional BO methods, while beneficial, often struggle with balancing the trade-off between exploration and exploitation, leading to sub-optimal performance in accelerated material discovery processes. This paper introduces a novel Threshold-Driven UCB-EI Bayesian Optimization (TDUE-BO) method, which dynamically integrates the strengths of Upper Confidence Bound (UCB) and Expected Improvement (EI) acquisition functions to optimize the material discovery process. Unlike the classical BO, our method focuses on efficiently navigating the high-dimensional material design space (MDS). TDUE-BO begins with an exploration-focused UCB approach, ensuring a comprehensive initial sweep of the MDS. As the model gains confidence, indicated by reduced uncertainty, it transitions to the more exploitative EI method, focusing on promising areas identified earlier. The UCB-to-EI switching policy, which is steered by ongoing monitoring of model uncertainty at each stage of sequential sampling, enables more efficient navigation through the MDS while guaranteeing quicker convergence. The effectiveness of TDUE-BO is demonstrated through its application on three different material science datasets, showing significantly better approximation and optimization performance over traditional EI and UCB-based BO methods in terms of the RMSE scores and convergence efficiency, respectively.

Generalizing Determinacy under Monetary and Fiscal Policy Switches: The Case of the Zero Lower Bound

AbstractIn a fixed‐regime context, it has been established since the work of Leeper (1991) that a determinate and unique equilibrium can be achieved under both monetary dominance (characterized by an active monetary policy and a passive fiscal policy) and fiscal dominance (characterized by an active fiscal policy and a passive monetary policy) regimes yield a determinate unique equilibrium. In this paper, we generalize this well‐established policy‐mix taxonomy to regime‐switching models, and show that switches from monetary dominance to fiscal dominance regimes (and vice versa) render the economy indeterminate for standard parameter values. We apply our results to the important case of the exit from the zero lower bound (ZLB), where monetary policy is inherently passive. Contrary to the fixed‐regime prediction, the economy switching between the ZLB in a fiscally led regime and a monetary dominance regime is robustly indeterminate, making the coordination of agents' beliefs hard for anchoring expected inflation. Finally, we propose a direction toward which the perspective of the fiscal theory of the price level can be made consistent with a unique stable equilibrium.

Asset prices, regime switches, and monetary policy: evidence from China

ABSTRACT This paper develops a regime-switching DSGE model that can capture time-varying volatilities in economic activity and monetary policy. The model is then used to study regime switches in macroeconomic dynamics and monetary policy in China. The results suggest a better fitness of the regime-switching model than conventional constant-parameter models. We also find notable differences in macroeconomic dynamics and monetary policy reactions between high and low volatility regimes. Further counterfactual analysis suggests that, at least in an environment with regime-switching volatilities, the optimal reaction of monetary policy involves responses to asset price variations. The findings of the paper shed new light on the regime-switching properties of the economy and the optimal choice of monetary policy within this context.

How the brain can be trained to achieve an intermittent control strategy for stabilizing quiet stance by means of reinforcement learning

The stabilization of human quiet stance is achieved by a combination of the intrinsic elastic properties of ankle muscles and an active closed-loop activation of the ankle muscles, driven by the delayed feedback of the ongoing sway angle and the corresponding angular velocity in a way of a delayed proportional (P) and derivative (D) feedback controller. It has been shown that the active component of the stabilization process is likely to operate in an intermittent manner rather than as a continuous controller: the switching policy is defined in the phase-plane, which is divided in dangerous and safe regions, separated by appropriate switching boundaries. When the state enters a dangerous region, the delayed PD control is activated, and it is switched off when it enters a safe region, leaving the system to evolve freely. In comparison with continuous feedback control, the intermittent mechanism is more robust and capable to better reproduce postural sway patterns in healthy people. However, the superior performance of the intermittent control paradigm as well as its biological plausibility, suggested by experimental evidence of the intermittent activation of the ankle muscles, leaves open the quest of a feasible learning process, by which the brain can identify the appropriate state-dependent switching policy and tune accordingly the P and D parameters. In this work, it is shown how such a goal can be achieved with a reinforcement motor learning paradigm, building upon the evidence that, in general, the basal ganglia are known to play a central role in reinforcement learning for action selection and, in particular, were found to be specifically involved in postural stabilization.

Agricultural policy and crop location: Long‐run output and spatial climate risk consequences

AbstractChoices by farmers—notably what crop to grow, where—are not only influenced by spatially sensitive environmental attributes but also economic factors that respond to changes in government policies. In South Africa, the policy stance toward agriculture swung toward an extended period of support spanning the middle of the 20th century. Subsequently, the agricultural support policies were eliminated in the post‐Apartheid period beginning in the 1990s. Using a purpose‐built, spatially explicit data set for South African agriculture spanning the period 1918–2015, we show these structural shifts in agricultural policy regimes concord with major shifts in national corn price trends and variability, and the area planted to corn (accounting for half the country's cropped area). More subtly, and much less studied, we reveal that these switching policy regimes also aligned with changes in the location of crop production, with pronounced consequences for crop output and climate risk. At its peak, policy‐aligned crop movement in South Africa reduced corn output by between 7.9% and 15.3%, and placed production in areas with reduced and riskier rainfall patterns. Upon removal of the policy distortions, the decline in total corn area continued, and the crop largely reverted to its predistorted, less climate‐risky geographical locations. The geographical sensitivities of the agricultural policy–production–climate risk nexus we reveal suggest these locational aspects deserve more concerted analytical and policy design attention, especially in light of the longer run, spatially sensitive production and food security risk implications of the changing climate realities facing agriculture the world over.

Association of institutional masking policies with healthcare-associated SARS-CoV-2 infections in Swiss acute care hospitals during the BA.4/5 wave (CH-SUR study): a retrospective observational study

BackgroundIn the initial phase of the SARS-CoV-2 pandemic, masking has been widely accepted in healthcare institutions to mitigate the risk of healthcare-associated infection. Evidence, however, is still scant and the role of masks in preventing healthcare-associated SARS-CoV-2 acquisition remains unclear.We investigated the association of variation in institutional mask policies with healthcare-associated SARS-CoV-2 infections in acute care hospitals in Switzerland during the BA.4/5 2022 wave.MethodsSARS-CoV-2 infections in hospitalized patients between June 1 and September 5, 2022, were obtained from the “Hospital-based surveillance of COVID-19 in Switzerland”-database and classified as healthcare- or community-associated based on time of disease onset. Institutions provided information regarding institutional masking policies for healthcare workers and other prevention policies. The percentage of healthcare-associated SARS-CoV-2 infections was calculated per institution and per type of mask policy. The association of healthcare-associated SARS-CoV-2 infections with mask policies was tested using a negative binominal mixed-effect model.ResultsWe included 2’980 SARS-CoV-2 infections from 13 institutions, 444 (15%) were classified as healthcare-associated. Between June 20 and June 30, 2022, six (46%) institutions switched to a more stringent mask policy. The percentage of healthcare-associated infections subsequently declined in institutions with policy switch but not in the others. In particular, the switch from situative masking (standard precautions) to general masking of HCW in contact with patients was followed by a strong reduction of healthcare-associated infections (rate ratio 0.39, 95% CI 0.30–0.49). In contrast, when compared across hospitals, the percentage of health-care associated infections was not related to mask policies.ConclusionsOur findings suggest switching to a more stringent mask policy may be beneficial during increases of healthcare-associated SARS-CoV-2 infections at an institutional level.

Socio-Economic Dynamics and Policy Implications for Electric Vehicle Adoption: A Micro-Level Study in NCR

Electric vehicles reduce pollution only if a high percentage of the electricity mix comes from renewable sources and if the battery manufacturing takes place at a site far from the vehicle use region. Industries developed due to increased electric vehicle adoption may also cause additional air pollution. The Indian government has committed to solving New Delhi’s air pollution issues through an ambitious policy of switching 100% of the light duty consumer vehicles to electric vehicles by 2030. This policy is based on vehicle grid interaction and relies on shared mobility through the electric vehicle fleet.

Does the introduction of an infliximab biosimilar always result in savings for hospitals? A descriptive study using real-world data

BackgroundBiosimilars are biologic drugs that have the potential to increase the efficiency of healthcare spending and curb drug-related cost increases. However, their introduction into hospital formularies through initiatives such as non-medical switching must be carefully orchestrated so as not to cause treatment discontinuation or result in increased health resource utilization, such as additional visits or laboratory tests, among others. This retrospective cohort study aims to assess the impact of the introduction of CT-P13 on the healthcare expenditures of patients who were treated with originator infliximab or CT-P13.MethodsGastroenterology, immunoallergology and rheumatology patients treated between September 2017 and December 2020 at a university hospital in Western Switzerland were included and divided into seven cohorts, based on their treatment pathway (i.e., use and discontinuation of CT-P13 and/or originator infliximab). Costs in Swiss francs were obtained from the hospital's cost accounting department and length of stay was extracted from inpatient records. Comparisons of costs and length of stay between cohorts were calculated by bootstrapping.ResultsSixty immunoallergology, 84 rheumatology and 114 gastroenterology patients were included. Inpatient and outpatient costs averaged (sd) CHF 1,611 (1,020) per hospital day and CHF 4,991 (6,931) per infusion, respectively. The mean (sd) length of stay was 20 (28) days. Although immunoallergology and rheumatology patients had higher average costs than gastroenterology patients, differences in costs and length of stay were not formally explained by treatment pathway. Differences in health resource utilization were marginal.ConclusionsThe introduction of CT-P13 and the disruption of patient treatment management were not associated with differences in average outpatient and inpatient costs and length of stay, in contrast to the results reported in the rest of the literature. Future research should focus on the cost-effectiveness of non-medical switching policies and the potential benefits for patients.

Full-Envelope Flight Control for Compound Vertical Takeoff and Landing Aircraft

This paper presents a flight control design for compound vertical takeoff and landing (VTOL) vehicles. With their multitude of degrees of controllability as well as the significant variations in their flight characteristics, VTOL vehicles present challenges when it comes to designing their flight control system, especially for the transition phase where the vehicle transitions between near-hovering and high-speed wing-borne flights. This work extends previous research on the design of unified and generic control laws that can be applied to a broad class of vehicles such as hovering vehicles and fixed-wing aircraft. This paper exploits this unifying property and presents an extension for the case of compound VTOL vehicles. The proposed control approach consists of nonlinear geometric control laws that are continuously applicable over the entire flight envelope, excluding the use of switching policies between different control algorithms. A transition strategy consisting of a sequence of high-level set points is associated with the flight control laws; it is defined with respect to flight envelope limitations and is applied in this work to a commercially available compound unmanned aerial vehicle. The control algorithms are implemented on a Pixhawk controller; they are evaluated via hardware-in-the-loop simulations and finally validated in a flight experiment.

Multi-objective optimization of production system with staggered production

In the manufacturing industry, timely order fulfilment from diverse customers is important for operational profitability, given the constraints of limited production capacity. This paper proposes a novel queueing system for a production system, in which order processing times are categorised as regular or rush based on customer preference. The proposed queueing system employs variable service rates and service strategies in conjunction with staggered production to deal with heterogeneous arrivals. We compute the steady-state probability distribution and develop system performance indicators. The lower and upper bounds of the expected sojourn time for rush and regular orders are derived. Numerical results show that an appropriate switching policy can reduce rush orders by approximately 35% while regular orders increase by less than 10%, demonstrating significant improvement in order fulfilment management. We formulate a multi-objective optimisation problem and implement the NSGA-II algorithm to obtain Pareto optimal solutions. Finally, three regression models are proposed to determine the minimum cost and the associated optimal service rates, given the maximum acceptable value of the expected number of rush orders. The established models can explain at least 80% of the dataset of the optimal solutions and thus our numerical findings provide useful guidance for decision-makers and production managers.

The nonlinear dynamic effect of government expenditure on income inequality: The case of macroprudential policy switching

A panel data analysis of nonlinear government expenditure and income inequality dynamics in a macroprudential policy regime was conducted on a panel of 15 emerging countries from 1985–2019, where there had been a non-prudential regime from 1985–1999 and a prudential regime from 2000–2019. The paper explored the validity of the nonlinearity between government expenditure and income inequality in the macroprudential policy regime as well as the threshold level at which excessive spending reduces income inequality using the Bayesian spatial lag panel smooth transition regression (BSPSTR) and fix effect models. The BSPSTR model was adopted due to its ability to address the problems of heterogeneity, endogeneity, and cross-section correlation in a nonlinear framework. Moreover, as the transition variable often varies across time and space, the effect of the independent variables can also be time- and space-varying. The results reveal evidence of a nonlinear effect between government spending and income inequality, where the minimum level of government spending is found to be 29.89 percent of GDP, above which expenditure reduces inequality in emerging countries. The findings confirmed an inverted U-shaped relationship. The focal policy recommendation is that fiscal policy decisions that will reinforce the need for more emphasis on education and public expenditure on education and health, as important tools for improving income inequality, are crucial for these economies. Caution is needed when introducing macroprudential policies, especially at a low level of government expenditure.

Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation

Ensuring the safety of Reinforcement Learning (RL) is crucial for its deployment in real-world applications. Nevertheless, managing the trade-off between reward and safety during exploration presents a significant challenge. Improving reward performance through policy adjustments may adversely affect safety performance. In this study, we aim to address this conflicting relation by leveraging the theory of gradient manipulation. Initially, we analyze the conflict between reward and safety gradients. Subsequently, we tackle the balance between reward and safety optimization by proposing a soft switching policy optimization method, for which we provide convergence analysis. Based on our theoretical examination, we provide a safe RL framework to overcome the aforementioned challenge, and we develop a Safety-MuJoCo Benchmark to assess the performance of safe RL algorithms. Finally, we evaluate the effectiveness of our method on the Safety-MuJoCo Benchmark and a popular safe benchmark, Omnisafe. Experimental results demonstrate that our algorithms outperform several state-of-the-art baselines in terms of balancing reward and safety optimization.

EU-Bioenergies: Status and Future Prospects

For climate protection and a sustainable economy, the European Union is pursuing a policy of switching from fossil to renewable energies, which should lead to a reduction in greenhouse gases (GHG) and a reduction in dependence on energy imports. This report uses publicly available databases and analyses to examine the extent to which these goals are achieved or are achievable by means of bioenergy (fuel, heat, electricity). In addition, EU regulations and databases relevant to bioenergy are critically scrutinised. Today, bioenergy accounts for around 10% of Europe's energy supply, making up more than half (59%) of renewable energies. There is potential to further increase bioenergy, but the future contribution to energy supply and independence from imports is rather to be estimated as moderate. The evaluation of GHG suffers from the fact that the official databases do not meet the requirements for a scientific evaluation. In order to make a sustainable contribution to the EU targets, besides energy, all other options for the use of biomass, the use of biogenic CO2 through carbon capture and utilisation (CCU) and the combination of bioenergy and carbon capture and sequestration (CCS) should be integrated. To promote the implementation of such an integrated approach, the pricing of GHG should be combined with incentives for the upscaling of sustainable bioenergy, CCU and CCS.

Price switching policies under advertising effect and dynamic environment in supply chain: Product life-cycle approach

When should manufacturers and retailers change their prices? Should they change prices based on the phases of the product life cycle (PLC) that are affected by advertising or without its effect? To answer these questions, we develop dynamic models for analyzing market demand, pricing decisions, and advertising cost according to the properties of PLC phases. Our contributions extend beyond conventional analyses. For the first time, we introduce dynamic mathematical models that capture market demand, pricing decisions, and advertising costs, intricately aligning them with the unique attributes of each PLC phase. Furthermore, this study pioneers the consideration of the effect of advertising on demand but also examining its influence on the duration of PLC phases, shedding light on a previously unexplored facet of market behavior. Furthermore, our research presents a groundbreaking perspective on the relationship between advertising, pricing, and the PLC phases. Based on the PLC perspective, product prices, especially for electronic products, decrease over time. Therefore, manufacturers and retailers should adopt appropriate price-switching policies to remain competitive. This paper examines a dynamic supply chain consisting of one manufacturer and one retailer, that demand changes over time. The price switching policies including: 1) the first policy: at the beginning of the advertising-influenced PLC phases, and 2) the second policy: at the beginning of without advertising-influenced PLC phases, are investigated. The results indicate that the wholesale and retail prices under the second policy are always lower than the first policy. In the second policy, the retailer's profit is higher, if the price reduction rate is not too low, and the other hand the manufacturer's profit is higher than other policy.

On Supervised Online Rolling-Horizon Control for Infinite-Horizon Discounted Markov Decision Processes

This note re-visits the rolling-horizon control approach to the problem of Markov decision process (MDP) with infinite-horizon discounted expected reward criterion. Distinguished from the classical value-iteration approaches, we develop an asynchronous on-line algorithm based on policy iteration integrated with a multi-policy improvement method of policy switching. A sequence of monotonically improving solutions to the forecast-horizon sub-MDP is generated by updating the current solution only at the currently visited state, building in effect a rolling-horizon control policy for the MDP over infinite horizon. Feedbacks from “supervisors,” if available, can be also incorporated while updating. We focus on the convergence issue with a relation to the transition structure of the MDP. Either a global convergence to an optimal forecast-horizon policy or a local convergence to a “locally-optimal” fixed-policy in a finite time is achieved by the algorithm depending on the structure.

On Single-Input Dual-Output (SIDO) DC/DC Multi-Port Converters for DC Microgrid Applications

This paper proposes the use of linear-assisted switching power converters in the context of single-inductor dual-output (SIDO) for microgrids (MG) applications. By combining a DC/DC ripple-controlled switching power converter with the respective voltage linear regulators at each output, improved performance in terms of load and line regulations is obtained. To achieve that aim, a current-steering switching policy is proposed, together with a resource-aware circuit implementation. The ripple-based hysteretic control results in variable switching frequency to guarantee critical conduction mode (boundary of CCM and DCM).