Cross-entropy optimization for scaling factors of a fuzzy controller: a see-and-avoid approach for unmanned aerial systems

The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand- avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions.

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand-avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

Nanotechnology for high frequency communications: nitrides and graphene

The achievement of higher frequencies (HF) and the reduction of energy consumption, to improve sensing, communication and computation, involve the continued scaling down to the nanometer level. This scaling is enabled by of innovative device designs, improved processing technologies and assessment tools, and new material structures. In this work, we have used all these factors to demonstrate state-of-the-art HF devices in two materials with quite different electronic properties: wide semiconductor bandgap III-nitrides for resonators and power amplifiers; and graphene, a zero bandgap material expected to revolutionize low noise and HF flexible electronics. Some issues faced during their development will be discussed during the talk.

Flying vs. climbing: Factors controlling arboreal seed removal in oak-beech forests

Nuts are heavy and nutritious seeds that need animals to be successfully dispersed. Most studies address nut removal by a single animal species once seeds fall onto the ground. However, nuts are also accessible before the seed drop and usually to a wide guild of seed foragers. This study examines the factorscontrollingarborealseedremoval in oak–beechforests within the whole guild of nut foragers. We found that seed-dispersing rodents (Apodemus sylvaticus) were the main acorn removers in the oaks (up to 3.75 m height), with a rapid seed encounter and a high removal rate. However, rodents did not climb the beech trees, probably due to their smoother bark in comparison to oak bark and/or the lower nutritional value of beechnuts with regard to acorns. Jays (Garrulus glandarius) were more abundant in oak stands (both dense and scattered) and clearly preferred acorns to beechnuts whereas nuthatches (Sitta europaea) were more abundant in beech stands and preferred beechnuts to acorns. Non-storing birds such as great tits (Parus major) also removed acorns and beechnuts, especially in the stands where oaks are dominant. Jays and rodents preferred sound seeds over insect-infested seeds but such a preference was not found for nuthatches. This study highlights that pure beech stands showed a reduced guild of arboreal nut foragers in comparison to oak stands. This different guild could probably affect the spatial patterns of seed dispersal, with a proportionally higher number of long dispersal events for acorns (mostly jay-dispersed) than for beechnuts (mostly nuthatch-dispersed). Long-distance dispersal of beechnuts (by jays) is determined by the presence of other preferred species (oaks) and their frequency of non-mast years. Seed location in different habitats strongly determines the contribution of different arboreal removers (including climbing rodents) and their removal speed, leading to a differential seed fate that will eventually affect tree regeneration. As nuthatches are sedentary birds, it is important to maintain old and dead trees where they can breed (crevices), forage (arthropods) and store seeds in order to favor beechnut dispersal and gene flow. By maintaining or favoring oak trees within beech stands we will ensure a wider guild of arboreal nut dispersers.

Low-thickness high-quality aluminum nitride films for super high frequency solidly mounted resonators

We investigate the sputter growth of very thin aluminum nitride (AlN) films on iridium electrodes for electroacoustic devices operating in the super high frequency range. Superior crystal quality and low stress films with thicknesses as low as 160 nm are achieved after a radio frequency plasma treatment of the iridium electrode followed by a two-step alternating current reactive magnetron sputtering of an aluminum target, which promotes better conditions for the nucleation of well textured AlN films in the very first stages of growth. Solidly mounted resonators tuned around 8 GHz with effective electromechanical coupling factors of 5.8% and quality factors Q up to 900 are achieved.

Management of irrigation frequency and nitrogen fertilization to mitigate GHG and NO emissions from drip-fertigated crops

Drip irrigation combined with split application of fertilizer nitrogen (N) dissolved in the irrigation water (i.e. drip fertigation) is commonly considered best management practice for water and nutrient efficiency. As a consequence, its use is becoming widespread. Some of the main factors (water-filled pore space, NH4+ and NO3−) regulating the emissions of greenhouse gases (i.e. N2O, CO2 and CH4) and NO from agroecosystems can easily be manipulated by drip fertigation without yield penalties. In this study, we tested management options to reduce these emissions in a field experiment with a melon (Cucumis melo L.) crop. Treatments included drip irrigation frequency (weekly/daily) and type of N fertilizer (urea/calcium nitrate) applied by fertigation. Crop yield, environmental parameters, soil mineral N concentrations and fluxes of N2O, NO, CH4 and CO2 were measured during 85 days. Fertigation with urea instead of calcium nitrate increased N2O and NO emissions by a factor of 2.4 and 2.9, respectively (P < 0.005). Daily irrigation reduced NO emissions by 42% (P < 0.005) but increased CO2 emissions by 21% (P < 0.05) compared with weekly irrigation. We found no relation between irrigation frequency and N2O emissions. Based on yield-scaled Global Warming Potential as well as NO cumulative emissions, we conclude that weekly fertigation with a NO3−-based fertilizer is the best option to combine agronomic productivity with environmental sustainability. Our study shows that adequate management of drip fertigation, while contributing to the attainment of water and food security, may provide an opportunity for climate change mitigation.

A procedure to track vibration modes under changing external factors: application to a pedestrian bridge

A low-cost vibration monitoring system has been developed and installed on an urban steel- plated stress-ribbon footbridge. The system continuously measures: the acceleration (using 18 triaxial MEMS accelerometers distributed along the structure), the ambient temperature and the wind velocity and direction. Automated output-only modal parameter estimation based on the Stochastic Subspace Identification (SSI) is carried out in order to extract the modal parameters, i.e., the natural frequencies, damping ratios and modal shapes. Thus, this paper analyzes the time evolution of the modal parameters over a whole-year data monitoring. Firstly, for similar environmental/operational factors, the uncertainties associated to the time window size used are studied and quantified. Secondly, a methodology to track the vibration modes has been established since several of them with closely-spaced natural frequencies are identified. Thirdly, the modal parameters have been correlated against external factors. It has been shown that this stress-ribbon structure is highly sensitive to temperature variation (frequency changes of more than 20%) with strongly seasonal and daily trends