The Borea project: a quadrotor uav cradle-to-grave design for space gnc prototyping and testing

Unmanned Aerial Vehicles (UAVs) and, more specifically, n-copters have come to prominence in the last decade due to their several applications. Also, in the automatic control research community UAVs have drawn great attention, since their non-linear and under-actuated nature making them suitable for testing a wide range of control architectures and algorithms. In this paper, prominent theoretical aspects, simulations, and experimental results of the Borea project are presented. The Borea project aims at testing space guidance, navigation, and control (GNC) algorithms leveraging a simplified, rapidly prototypable, low-cost, and easy-to-test quadrotor platform. More precisely, one of the main project objectives consists in testing Moon and Mars planetary landing algorithms, thanks to the similitude, in the command authority and the landing approach, between n-copters and spacecraft; during the propulsive landing phase. Indeed, both n-copters and spacecraft can provide a thrust vector characterized by constant direction and adjustable magnitude. This similitude approach makes it possible to anticipate issues and avoid failures such as those that occurred in the Schiaparelli Mars Lander. To this aim, the complete control unit design, and the UAV plant electro-mechanical prototyping were addressed; so far. Specifically, the control unit was designed within the framework of the Embedded Model Control (EMC) methodology. The EMC design, based on an internal model, also includes the uncertainties as disturbances to be estimated and actively rejected. The Borea UAV has been endowed with a control system leveraging a wide range of automatic control concepts, ranging from modelling, identification, and linear and non-linear control laws, to deal with its position, velocity, and attitude regulation. To sum up, all these results were achieved by means of a properly structured cradle-to-grave design process which, starting from the simultaneous plant modelling and prototyping, ended up with a complete flight tests campaign. Most notably, the testing process involved intensive numerical simulations as well as multi-stage hardware/plant tests and models validation. From the control perspective, the several developed controllers were tuned and tested, via proper simulations and on-purpose flight tests, aiming at validating, from time to time, specific functionalities and control performances. Finally, some results coming from high-fidelity simulations, the hardware and model testing, and in-flight operations are provided to underline the most relevant aspects of the Borea plant and the control unit performance

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Embedded Model Control for UAVs: theoretical aspects, simulations and experimental results

Unmanned Aerial Vehicles (UAVs) and, more specifically, n-copters have come to prominence in the last decade. Indeed, unmanned vehicles may have several applications in society, spanning from complex operations, also in potentially hazardous environments for humans to more entertaining purposes. Furthermore, UAVs have drawn great attention in the automatic control research community. This is mainly due to two reasons. First of all, designing a control for this non-linear and underactuated system can represent a stimulating challenge for control researchers. Secondly, n-copters, being typically mechanically simple and fast-prototyping devices, are widely considered as a good technology for testing a wide range of control algorithms and designs, also employing a wide range of sensors. In fact, the possibility of having several low cost sensors on-board enables the implementation of many navigation solutions as well as sensor calibration algorithms. In this work, the control unit design for a quadrotor was addressed. In particular, the study regards the Borea quadrotor which is part of an internal project (Borea) of the former Space and Precision Automatics research, now Systems and Data Science group, at Politecnico di Torino. The Borea project aims to test Guidance, Navigation and Control (GNC) algorithms designed within the framework of the Embedded Model Control (EMC) methodology. In particular, one of the main project objectives regards the testing of planetary landing algorithms because of the similitude in the command authority between n-copters and spacecrafts during the landing phase. In fact, both n-copters and spacecrafts can provides a thrust vector which is constant in direction whereas its intensity can be regulated. The EMC framework matches the GNC architecture perfectly. More important, EMC is a methodology based on an internal model which includes the uncertainties, in the form of disturbances, that have to be rejected. Indeed, the main design effort is focused on the internal model design, which is the core of the whole control unit. The Borea UAV has been endowed with a control system in order to control its position, velocity, and attitude. These results has been achieved by means of a well structured design process which started from the plant modelling and arrived to the flight test. Indeed, the process has involved intensive numerical simulation and control refinements as well as multi-staged tests and model validations. During the design process some neglected dynamics has turned out to be very important for the control design and their identification was revealed mandatory. On the other hand, the control problem was separated into two independent controllers in order to have a more simple controller which makes the quadrotor able to fly allowing to test all the subsystems, improve the simulator fidelity and support the design and validation of the second controller. Each controller has required specifics flight tests aimed to validates particular functionalities and control performance. Testing has included the design and building of a single axis test-bench in order to perform the very first control tuning in a safety way. The objective of the first controller was the attitude stabilization of the quadrotor in order to perform a hovering flight initially and the attitude tracking later. The design of the attitude controller has required the identification of the actuator dynamics as well as the sensors calibration. The attitude control unit has been implemented in all its parts and successfully tested in real flight. As mentioned before, the next step has been focused on controlling the quadrotor position within a limited flight area. In particular, this study investigates the use of the feedback linearization approach as a novel way to design the internal model for EMC. The feedback linearization allows us to collect all the non-linearities at the command level. EMC, by means of a disturbance dynamics model, makes possible to estimate and then reject the non-linear terms through the control law. The control solution has been validated by means of intensive numerical simulations and real-flight tests. As a final result, the control units developed in this work enhance the EMC applicability to non-linear systems, such as quadrotor UAVs, and evidence the EMC disturbance rejection capabilities

The feedback linearisation method for Embedded Model Control: The Borea project case-study

Feedback linearisation has been proved to be a powerful tool for making non-linear system dynamics fully or partially linear. This study investigates the use of the feedback linearisation approach as a novel way to design the internal model for Embedded Model Control, when applied to non-linear systems. This idea is applied to the control of an Unmanned Aerial Vehicle: the Borea project quadrotor. Embedded Model Control methodology implies the design of an internal model (Embedded Model) coded into the control unit and running in parallel with the plant. The difference between the internal model output and the plant output is used to estimate the unknown disturbances. These unknown disturbances include all the non-linearities that can be rejected by means of the control law. Using a numerical simulator, we demonstrate the feasibility of this methodology for accurate design of the internal model, starting from the non-linear system. This indicates that a feedback linearisation approach allows the extension of embedded model control techniques to non-linear systems control. What is more, the EMC is successfully applied to the control of the Borea quadrotor