Evolutionary L∞ identification and model reduction for robust control

An evolutionary approach for modern robust control oriented system identification and model reduction in the frequency domain is proposed. The technique provides both an optimized nominal model and a 'worst-case' additive or multiplicative uncertainty bounding function which is compatible with robust control design methodologies. In addition, the evolutionary approach is applicable to both continuous- and discrete-time systems without the need for linear parametrization or a confined problem domain for deterministic convex optimization. The proposed method is validated against a laboratory multiple-input multiple-output (MIMO) test rig and benchmark problems, which show a higher fitting accuracy and provides a tighter L�¢���� error bound than existing methods in the literature do

Which Surrogate Works for Empirical Performance Modelling? A Case Study with Differential Evolution

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.It is not uncommon that meta-heuristic algorithms contain some intrinsic parameters, the optimal configuration of which is crucial for achieving their peak performance. However, evaluating the effectiveness of a configuration is expensive, as it involves many costly runs of the target algorithm. Perhaps surprisingly, it is possible to build a cheap-to-evaluate surrogate that models the algorithm's empirical performance as a function of its parameters. Such surrogates constitute an important building block for understanding algorithm performance, algorithm portfolio/selection, and the automatic algorithm configuration. In principle, many off-the-shelf machine learning techniques can be used to build surrogates. In this paper, we take the differential evolution (DE) as the baseline algorithm for proof-of-concept study. Regression models are trained to model the DE's empirical performance given a parameter configuration. In particular, we evaluate and compare four popular regression algorithms both in terms of how well they predict the empirical performance with respect to a particular parameter configuration, and also how well they approximate the parameter versus the empirical performance landscapes.Royal Societ

Scalable squeezed light source for continuous variable quantum sampling

We propose a novel squeezed light source capable of meeting the stringent requirements of continuous variable quantum sampling. Using the effective $\chi_2$ interaction induced by a strong driving beam in the presence of the $\chi_3$ response in an integrated microresonator, our device is compatible with established nanophotonic fabrication platforms. With typical realistic parameters, squeezed states with a mean photon number of 10 or higher can be generated in a single consistent temporal mode at repetition rates in excess of 100MHz. Over 15dB of squeezing is achievable in existing ultra-low loss platforms

Students' uses and gratifications for using computer-mediated communication media in learning contexts

Despite a growing stream of research into the use of computer-mediated communication (CMC) media in higher education, there remains limited understanding about the students‘ motivations for using CMC alongside non-CMC media within a learning context. This article identifies seven dimensions of motivation from the perspective of uses and gratifications (U&G), including information seeking, convenience, connectivity, problem solving, content management, social presence, and social context cues. It was found that each CMC satisfied different motivations for its use, and that overall CMC best fulfilled information seeking, convenience, connectivity, and content management motivations. This study also identifies a number of similarities and differences between CMC and non- CMC media in terms of the motivations for their use. Finally, the study concludes with a discussion of the implications for Information Systems (IS) researchers, higher education, and organizations

Influence of Nb2O5 substitution on the structural and electrical properties of Bi3TaO7 ceramics

Herein we report the doping mechanism and impedance study of the Nb-substituted Bi3Ta1-xNbxO7 (0 ≤ x ≤ 0.5) prepared via conventional solid-state method at 900 °C over 24 h. The substitutional solid solution crystallised in a cubic fluorite structure, space group Fm-3m and with lattice parameter, a = b = c, in the range 5.4477 (±0.0037)–5.4654 (±0.0011) Å. An insignificant unit cell expansion was observed with increasing Nb2O5 content and the linear correlation between lattice parameter and composition variable showed that the Vegard's Law was obeyed. Both TGA and DTA analyses confirmed that the Bi3Ta1-xNbxO7 solid solution was thermally stable as neither phase transition nor weight loss was observed within the studied temperature range, ∼28 °C–1000 °C. The electrical conductivities of these samples were found to increase with increasing Nb concentration; the Bi3Ta0.5Nb0.5O7 exhibited the highest conductivity, ∼1.2 × 10−2 S cm−1 at 700 °C with a low activation energy of 1.03 eV

Predictable Disruption Tolerant Networks and Delivery Guarantees

This article studies disruption tolerant networks (DTNs) where each node knows the probabilistic distribution of contacts with other nodes. It proposes a framework that allows one to formalize the behaviour of such a network. It generalizes extreme cases that have been studied before where (a) either nodes only know their contact frequency with each other or (b) they have a perfect knowledge of who meets who and when. This paper then gives an example of how this framework can be used; it shows how one can find a packet forwarding algorithm optimized to meet the 'delay/bandwidth consumption' trade-off: packets are duplicated so as to (statistically) guarantee a given delay or delivery probability, but not too much so as to reduce the bandwidth, energy, and memory consumption.Comment: 9 page