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Solar energy harvesting using Photovoltaic (PV) systems is one of the most popular sources of renewable energy, however the main drawback of PV systems is their low conversion efficiency. An optimal system operation requires an efficient tracking of the Maximum Power Point (MPP), which represents the maximum energy that can be extracted from the PV panel. This paper presents a novel control approach for the Maximum Power Point Tracking (MPPT) based on the differential flatness property of the Boost converter, which is one of the most used converters in PV systems. The underlying idea of the proposed control approach is to use the classical flatness-based trajectory tracking control where a reference voltage will be defined in terms of the maximum power provided by the PV panel. The effectiveness of the proposed controller is assessed through numerical simulations and experimental tests. The results show that the controller based on differential flatness is capable of converging in less than 0.15 s and, compared with other MPPT techniques, such as Incremental Conductance and Perturb and Observe, it improves the response against sudden changes in load or weather conditions, reducing the ringing in the output of the system. Based on the results, it can be inferred that the new flatness-based controller represents an alternative to improve the MPPT in PV systems, especially when they are subject to sudden load or weather changes.

Background The timely detection of fall risk or balance impairment in older adults is transcendental because, based on a reliable diagnosis, clinical actions can be taken to prevent accidents. This study presents a statistical model to estimate the fall risk from the center of pressure (CoP) data. Methods This study is a cross-sectional analysis from a cohort of community-dwelling older adults aged 60 and over living in Mexico City. CoP balance assessments were conducted in 414 older adults (72.2% females) with a mean age of 70.23 ± 6.68, using a modified and previously validated Wii Balance Board (MWBB) platform. From this information, 78 CoP indexes were calculated and analyzed. Multiple logistic regression models were fitted in order to estimate the relationship between balance alteration and the CoP indexes and other covariables. Results The CoP velocity index in the Antero-Posterior direction with open eyes (MVELAPOE) had the best value of area under the curve (AUC) to identify a balance alteration (0.714), and in the adjusted model, AUC was increased to 0.827. Older adults with their mean velocity higher than 14.24 mm/s had more risk of presenting a balance alteration than those below this value (OR (Odd Ratio) = 2.94, p<0.001, 95% C.I.(Confidence Interval) 1.68–5.15). Individuals with increased age and BMI were more likely to present a balance alteration (OR 1.17, p<0.001, 95% C.I. 1.12–1.23; OR 1.17, p<0.001, 95% C.I. 1.10–1.25). Contrary to what is reported in the literature, sex was not associated with presenting a balance alteration (p = 0.441, 95% C.I. 0.70–2.27). Significance The proposed model had a discriminatory capacity higher than those estimated by similar means and resources to this research and was implemented in an embedded standalone system which is low-cost, portable, and easy-to-use, ideal for non-laboratory environments. The authors recommend using this technology to support and complement the clinical tools to attend to the serious public health problem represented by falls in older adults.

Today, computer vision algorithms are very important for different fields and applications, such as closed-circuit television security, health status monitoring, and recognizing a specific person or object and robotics. Regarding this topic, the present paper deals with a recent review of the literature on computer vision algorithms (recognition and tracking of faces, bodies, and objects) oriented towards socially assistive robot applications. The performance, frames per second (FPS) processing speed, and hardware implemented to run the algorithms are highlighted by comparing the available solutions. Moreover, this paper provides general information for researchers interested in knowing which vision algorithms are available, enabling them to select the one that is most suitable to include in their robotic system applications.

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