Search for heavy resonances decaying into a W or Z boson and a Higgs boson in final states with leptons and b-jets in 36 fb(-1) of root s=13 TeV pp collisions with the ATLAS detector

A search is conducted for new resonances decaying into a W or Z boson and a 125 GeV Higgs boson in the νν¯¯¯bb¯¯, ℓ±νbb¯¯, and ℓ+ℓ−bb¯¯ final states, where ℓ± = e± or μ±, in pp collisions at s√=13 TeV. The data used correspond to a total integrated luminosity of 36.1 fb−1 collected with the ATLAS detector at the Large Hadron Collider during the 2015 and 2016 data-taking periods. The search is conducted by examining the reconstructed invariant or transverse mass distributions of W h and Zh candidates for evidence of a localised excess in the mass range of 220 GeV up to 5 TeV. No significant excess is observed and the results are interpreted in terms of constraints on the production cross-section times branching fraction of heavy W ′ and Z′ resonances in heavy-vector-triplet models and the CP-odd scalar boson A in two-Higgs-doublet models. Upper limits are placed at the 95% confidence level and range between 9.0 × 10−4 pb and 7.3 × 10−1 pb depending on the model and mass of the resonance

Perturbation wavelet-neural sliding-mode position control for a voice coil motor driver

[[abstract]]To cope with the nonlinear electro-magneto-mechanical characteristics, this paper proposes a perturbation wavelet neural sliding mode position control (PWSPC) system for a voice coil motor (VCM) driver. A perturbed wavelet neural network (PWNN) approximator is used to online approximate the unknown nonlinear term in the VCM system dynamics. The PWNN approximator uses perturbed wavelet functions to handle the rules uncertainties like interval type-2 fuzzy sets. The structure learning ability enables the PWNN approximator to evolve its structure online. Further, the parameter learning laws and stability analysis are derived in the sense of Lyapunov function; thus, the parameter convergence and system stability can be guaranteed. Finally, the experimental results verify that the proposed PWSPC system can achieve favorable control performance such as good disturbance rejection and good tracking accuracy.[[notice]]補正完