Non-linear model predictive control of a tilt-rotor quadcopter for control allocation and path following

The tilt-rotor quadcopter is an optimized structure of the standard quadcopter, which has actuating motors that can tilt about the quadcopter arm. A tilt-rotor quadcopter with more control inputs could theoretically bring stronger anti-disturbance and fault tolerance capabilities and track along a given path while maintaining a desired attitude. In this paper, a tilt-rotor quadcopter prototype is presented, whose actuator groups are independently tilted by motor servo systems. A non-linear model predictive control is further designed to allocate the inputs for actuating motors and tilting motors while solving the pathfollowing problem of a drone. Numerical simulations were run with different disturbances on the tilt-rotor quadcopter model, whose dynamics are presented according to the real quadcopter prototype. The simulation studies show the redundant control volume of the tilt-rotor quadcopter can bring stronger antidisturbance capabilities and more flexible path-tracking ability to the quadcopter, as well as demonstrate the effectiveness of the control allocation by non-linear model predictive control

Scheme for sharing classical information via tripartite entangled states

We investigate schemes for quantum secret sharing and quantum dense coding via tripartite entangled states. We present a scheme for sharing classical information via entanglement swapping using two tripartite entangled GHZ states. In order to throw light upon the security affairs of the quantum dense coding protocol, we also suggest a secure quantum dense coding scheme via W state in analogy with the theory of sharing information among involved users.Comment: 4 pages, no figure. A complete rewrritten vession, accepted for publication in Chinese Physic

Numerical Simulation of Solid-liquid Flow in Hydrocyclone

Hydrocyclone is widely used as the centrifugal separation equipment to separate, classify and concentrate the product. In this paper, the multiphase flow models of mixture and Euler-Euler are used to simulate the internal three-dimensional flow field of hydrocyclone. It is found that compared to the experiment, the mixture model is shown to have the best performance among the models of mixture, Euler-Euler and discrete phase for the separation simulation when the diameter of solid particle is less than 30 μm. Otherwise, the discrete phase model holds the best performance. Furthermore, the field of static pressure, axial and tangential velocity, and volume fraction in the hydrocyclone is obtained by the mixture model. The outcome is very helpful to explain the separation procedure and optimize the hydrocyclone design

Observation of momentum-confined in-gap impurity state in Ba0.6_{0.6}K0.4_{0.4}Fe2_2As2_2: evidence for anti-phase s±s_{\pm} pairing

We report the observation by angle-resolved photoemission spectroscopy of an impurity state located inside the superconducting gap of Ba$_{0.6}$K$_{0.4}$Fe$_2$As$_2$ and vanishing above the superconducting critical temperature, for which the spectral weight is confined in momentum space near the Fermi wave vector positions. We demonstrate, supported by theoretical simulations, that this in-gap state originates from weak non-magnetic scattering between bands with opposite sign of the superconducting gap phase. This weak scattering, likely due to off-plane Ba/K disorders, occurs mostly among neighboring Fermi surfaces, suggesting that the superconducting gap phase changes sign within holelike (and electronlike) bands. Our results impose severe restrictions on the models promoted to explain high-temperature superconductivity in these materials.Comment: 8 pages, 5 figures. Accepted for publication in Physical Review

Ultrafast Nonlinear Optical Excitation Behaviors of Mono- and Few-Layer Two Dimensional MoS2

The layered MoS2 has recently attracted significant attention for its excellent nonlinear optical properties. Here, the ultrafast nonlinear optical (NLO) absorption and excited carrier dynamics of layered MoS2 (monolayer, 3–4 layers, and 6–8 layers) are investigated via Z-scan and transient absorption spectra. Our experimental results reveal that NLO absorption coefficients of these MoS2 increase from–27 × 103 cm/GW to–11 × 103 cm/GW with more layers at 400-nm laser excitation, while the values decrease from 2.0 × 103 cm/GW to 0.8 × 103 cm/GW at 800 nm. In addition, at high pump fluence, when the NLO response occurs, the results show that not only the reformation of the excitonic bands, but also the recovery time of NLO response decreases from 150 ps to 100 ps with an increasing number of layers, while the reductive energy of A excitonic band decreases from 191.7 meV to 51.1 meV. The intriguing NLO response of MoS2 provides excellent potentials for the next-generation optoelectronic and photonic devices

A comparative study on violent sloshing with complex baffles using the ISPH method

The Smoothed Particle Hydrodynamics (SPH) method has become one of the most promising methods for violent wave impact simulations. In this paper, the incompressible SPH (ISPH) method will be used to simulate liquid sloshing in a 2D tank with complex baffles. Firstly, the numerical model is validated against the experimental results and the simulations from commercial CFD software STAR-CCM+ for a sloshing tank without any baffle. Then various sloshing tanks are simulated under different conditions to analyze the influence of the excitation frequency and baffle configuration. The results show that the complex baffles can significantly influence the impact pressures on the wall caused by the violent sloshing, and the relevant analysis can help find the engineering solutions to effectively suppress the problem. The main purpose of the paper is to study the practical importance of this effect

Intelligent Interactive Beam Training for Millimeter Wave Communications

Millimeter wave communications, equipped with large-scale antenna arrays, are able to provide Gbps data by exploring abundant spectrum resources. However, the use of a large number of antennas along with narrow beams causes a large overhead in obtaining channel state information (CSI) via beam training, especially for fast-changing channels. To reduce beam training overhead, in this paper we develop an interactive learning design paradigm (ILDP) that makes full use of domain knowledge of wireless communications (WCs) and adaptive learning ability of machine learning (ML). Specifically, the ILDP is fulfilled via deep reinforcement learning (DRL), which yields DRL-ILDP, and consists of communication model (CM) module and adaptive learning (AL) module, which work in an interactive manner. Then, we exploit the DRL-ILDP to design efficient beam training algorithms for both multi-user and user-centric cooperative communications. The proposed DRL-ILDP based algorithms enjoy three folds of advantages. Firstly, ILDP takes full advantages of the existing WC models and methods. Secondly, ILDP integrates powerful ML elements, which facilitates extracting interested statistical and probabilistic information from environments. Thirdly, via the interaction between the CM and AL modules, the algorithms are able to collect samples and extract information in real-time and sufficiently adapt to the ever-changing environments. Simulation results demonstrate the effectiveness and superiority of the designed algorithms

Probabilistic Constructive Interference Precoding for Imperfect CSIT

This paper proposes a stochastic-robust constructive interference (CI) precoding scheme for downlink multi-user MISO systems, assuming that channel state information (CSI) at the transmitter side (CSIT) is contaminated by Gaussian-distributed uncertainties. Our objective is to minimize the total transmit power under users' quality-of-service constraints: formulating CI at each user with high probabilities for a given target signal-to-noise ratio (SINR). We first analyze the probability of CI under imperfect CSIT. A series of approximations are then developed, transforming the intractable stochastic CI constraints into determined convex constraints. The non-convex stochastic-robust CI power minimization (CIPM) problem is then converted into second-order cone programming. We show that we could create tightened or relaxed approximations by changing the parameters, enabling us to find upper-bounds and lower-bounds for the original stochastic CIPM problem. The best parameter values corresponding to the tightest upper and lower bounds are also discussed and obtained. Simulation results show that the proposed methods reasonably approximate the stochastic CIPM problem. Using the given parameter values, it can guarantee the required probability of CI for each user under acceptable channel uncertainties and outperform the existing robust CI precoding in terms of both transmit power and feasibility rate. The small gap between the upper and lower bounds also shows that the proposed method does not cause too much performance loss