scholarly journals Robustness and performance trade-offs in control design for flexible structures

1994 ◽  
Vol 2 (4) ◽  
pp. 352-361 ◽  
Author(s):  
G.J. Balas ◽  
J.C. Doyle
Keyword(s):  
Flexible Structures ◽  
Control Design ◽  
Trade Offs ◽  
And Performance

Specialization and performance trade‐offs across hosts in cactophilic Drosophila species

2021 ◽  
Author(s):  
Santiago Bouzas ◽  
María F. Barbarich ◽  
Eduardo M. Soto ◽  
Julián Padró ◽  
Valeria P. Carreira ◽  
...  
Keyword(s):  
Drosophila Species ◽  
Cactophilic Drosophila ◽  
Trade Offs ◽  
And Performance

scholarly journals Noise and Breakdown Characterization of SPAD Detectors with Time-Gated Photon-Counting Operation

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5287
Author(s):  
Hiwa Mahmoudi ◽  
Michael Hofbauer ◽  
Bernhard Goll ◽  
Horst Zimmermann
Keyword(s):  
Breakdown Voltage ◽  
Single Photon ◽  
Photon Counting ◽  
Low Noise ◽  
Dark Count ◽  
Fully Integrated ◽  
Trade Offs ◽  
And Performance ◽  
Noise Models

Being ready-to-detect over a certain portion of time makes the time-gated single-photon avalanche diode (SPAD) an attractive candidate for low-noise photon-counting applications. A careful SPAD noise and performance characterization, however, is critical to avoid time-consuming experimental optimization and redesign iterations for such applications. Here, we present an extensive empirical study of the breakdown voltage, as well as the dark-count and afterpulsing noise mechanisms for a fully integrated time-gated SPAD detector in 0.35-μm CMOS based on experimental data acquired in a dark condition. An “effective” SPAD breakdown voltage is introduced to enable efficient characterization and modeling of the dark-count and afterpulsing probabilities with respect to the excess bias voltage and the gating duration time. The presented breakdown and noise models will allow for accurate modeling and optimization of SPAD-based detector designs, where the SPAD noise can impose severe trade-offs with speed and sensitivity as is shown via an example.

Renewable energy selection based on a new entropy and dissimilarity measure on an interval-valued neutrosophic set

2021 ◽  
pp. 1-18
Author(s):  
ShuoYan Chou ◽  
Truong ThiThuy Duong ◽  
Nguyen Xuan Thao
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Membership Function ◽  
Fossil Fuels ◽  
Multiple Criteria Decision Making ◽  
Clean Energy ◽  
Dissimilarity Measure ◽  
Neutrosophic Set ◽  
Trade Offs ◽  
And Performance

Energy plays a central part in economic development, yet alongside fossil fuels bring vast environmental impact. In recent years, renewable energy has gradually become a viable source for clean energy to alleviate and decouple with a negative connotation. Different types of renewable energy are not without trade-offs beyond costs and performance. Multiple-criteria decision-making (MCDM) has become one of the most prominent tools in making decisions with multiple conflicting criteria existing in many complex real-world problems. Information obtained for decision making may be ambiguous or uncertain. Neutrosophic is an extension of fuzzy set types with three membership functions: truth membership function, falsity membership function and indeterminacy membership function. It is a useful tool when dealing with uncertainty issues. Entropy measures the uncertainty of information under neutrosophic circumstances which can be used to identify the weights of criteria in MCDM model. Meanwhile, the dissimilarity measure is useful in dealing with the ranking of alternatives in term of distance. This article proposes to build a new entropy and dissimilarity measure as well as to construct a novel MCDM model based on them to improve the inclusiveness of the perspectives for decision making. In this paper, we also give out a case study of using this model through the process of a renewable energy selection scenario in Taiwan performed and assessed.

scholarly journals A multi-channel $$\varvec{H}_\infty $$ preview control approach to load alleviation design for flexible aircraft

2021 ◽  
Author(s):  
Ahmed Khalil ◽  
Nicolas Fezans
Keyword(s):  
Design Methodology ◽  
Control Design ◽  
Doppler Lidar ◽  
Preview Control ◽  
Reduced Order ◽  
Control Approach ◽  
Structural Fatigue ◽  
Trade Offs ◽  
Gust Load Alleviation ◽  
Near Future

AbstractGust load alleviation functions are mainly designed for two objectives: first, alleviating the structural loads resulting from turbulence or gust encounter, and hence reducing the structural fatigue and/or weight; and second, enhancing the ride qualities, and hence the passengers’ comfort. Whilst load alleviation functions can improve both aspects, the designer will still need to make design trade-offs between these two objectives and also between various types and locations of the structural loads. The possible emergence of affordable and reliable remote wind sensor techniques (e.g., Doppler LIDAR) in the future leads to considering new types of load alleviation functions as these sensors would permit anticipating the near future gusts and other types of turbulence. In this paper, we propose a preview control design methodology for the design of a load alleviation function with such anticipation capabilities, based on recent advancements on discrete-time reduced-order multi-channel $$H_\infty $$ H ∞ techniques. The methodology is illustrated on the DLR Discus-2c flexible sailplane model.

High-Performance Image Filters via Sparse Approximations

2020 ◽  
Vol 3 (2) ◽  
pp. 1-19
Author(s):  
Kersten Schuster ◽  
Philip Trettner ◽  
Leif Kobbelt
Keyword(s):  
High Performance ◽  
Hardware Acceleration ◽  
Optimization Method ◽  
Translation Invariant ◽  
Approximation Quality ◽  
Trade Offs ◽  
Sparse Approximations ◽  
Image Filters ◽  
Good Trade ◽  
And Performance

We present a numerical optimization method to find highly efficient (sparse) approximations for convolutional image filters. Using a modified parallel tempering approach, we solve a constrained optimization that maximizes approximation quality while strictly staying within a user-prescribed performance budget. The results are multi-pass filters where each pass computes a weighted sum of bilinearly interpolated sparse image samples, exploiting hardware acceleration on the GPU. We systematically decompose the target filter into a series of sparse convolutions, trying to find good trade-offs between approximation quality and performance. Since our sparse filters are linear and translation-invariant, they do not exhibit the aliasing and temporal coherence issues that often appear in filters working on image pyramids. We show several applications, ranging from simple Gaussian or box blurs to the emulation of sophisticated Bokeh effects with user-provided masks. Our filters achieve high performance as well as high quality, often providing significant speed-up at acceptable quality even for separable filters. The optimized filters can be baked into shaders and used as a drop-in replacement for filtering tasks in image processing or rendering pipelines.

Passthrough+

2020 ◽  
Vol 3 (1) ◽  
pp. 1-17
Author(s):  
Gaurav Chaurasia ◽  
Arthur Nieuwoudt ◽  
Alexandru-Eugen Ichim ◽  
Richard Szeliski ◽  
Alexander Sorkine-Hornung
Keyword(s):  
Real Time ◽  
Video Encoding ◽  
View Synthesis ◽  
Performance Constraints ◽  
Trade Offs ◽  
Stereoscopic View ◽  
Target User ◽  
Spatio Temporal ◽  
And Performance ◽  
3D Scene

We present an end-to-end system for real-time environment capture, 3D reconstruction, and stereoscopic view synthesis on a mobile VR headset. Our solution allows the user to use the cameras on their VR headset as their eyes to see and interact with the real world while still wearing their headset, a feature often referred to as Passthrough. The central challenge when building such a system is the choice and implementation of algorithms under the strict compute, power, and performance constraints imposed by the target user experience and mobile platform. A key contribution of this paper is a complete description of a corresponding system that performs temporally stable passthrough rendering at 72 Hz with only 200 mW power consumption on a mobile Snapdragon 835 platform. Our algorithmic contributions for enabling this performance include the computation of a coarse 3D scene proxy on the embedded video encoding hardware, followed by a depth densification and filtering step, and finally stereoscopic texturing and spatio-temporal up-sampling. We provide a detailed discussion and evaluation of the challenges we encountered, as well as algorithm and performance trade-offs in terms of compute and resulting passthrough quality.;AB@The described system is available to users as the Passthrough+ feature on Oculus Quest. We believe that by publishing the underlying system and methods, we provide valuable insights to the community on how to design and implement real-time environment sensing and rendering on heavily resource constrained hardware.

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