Yet Another Tutorial of Disturbance Observer: Robust Stabilization and Recovery of Nominal Performance

This paper presents a tutorial-style review on the recent results about the disturbance observer (DOB) in view of robust stabilization and recovery of the nominal performance. The analysis is based on the case when the bandwidth of Q-filter is large, and it is explained in a pedagogical manner that, even in the presence of plant uncertainties and disturbances, the behavior of real uncertain plant can be made almost similar to that of disturbance-free nominal system both in the transient and in the steady-state. The conventional DOB is interpreted in a new perspective, and its restrictions and extensions are discussed

Deep Learning-Assisted Parallel Interference Cancellation for Grant-Free NOMA in Machine-Type Communication

In this paper, we present a novel approach for joint activity detection (AD), channel estimation (CE), and data detection (DD) in uplink grant-free non-orthogonal multiple access (NOMA) systems. Our approach employs an iterative and parallel interference removal strategy inspired by parallel interference cancellation (PIC), enhanced with deep learning to jointly tackle the AD, CE, and DD problems. Based on this approach, we develop three PIC frameworks, each of which is designed for either coherent or non-coherence schemes. The first framework performs joint AD and CE using received pilot signals in the coherent scheme. Building upon this framework, the second framework utilizes both the received pilot and data signals for CE, further enhancing the performances of AD, CE, and DD in the coherent scheme. The third framework is designed to accommodate the non-coherent scheme involving a small number of data bits, which simultaneously performs AD and DD. Through joint loss functions and interference cancellation modules, our approach supports end-to-end training, contributing to enhanced performances of AD, CE, and DD for both coherent and non-coherent schemes. Simulation results demonstrate the superiority of our approach over traditional techniques, exhibiting enhanced performances of AD, CE, and DD while maintaining lower computational complexity

Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle

In this paper, we derive an algorithm for enabling a single robotic unmanned aerial vehicle to herd a flock of birds away from a designated volume of space, such as the air space around an airport. The herding algorithm, referred to as the m-waypoint algorithm, is designed using a dynamic model of bird flocking based on Reynolds’ rules. We derive bounds on its performance using a combination of reduced-order modeling of the flock's motion, heuristics, and rigorous analysis. A unique contribution of the paper is the experimental demonstration of several facets of the herding algorithm on flocks of live birds reacting to a robotic pursuer. The experiments allow us to estimate several parameters of the flocking model, and especially the interaction between the pursuer and the flock. The herding algorithm is also demonstrated using numerical simulations

More Proofs for `Determination of Stability with respect to Positive Orthant for a Class of Positive Nonlinear Systems'

This is a supplement material for a published article by the authors.In the published paper `Determination of Stability with respect to Positive Orthant for a Class of Positive Nonlinear Systems,' IEEE Trans. on Automatic Control, vol. 53, no. 5, pp. 1329-1334, 2008, by the authors, some proofs are omitted due to the space limitation of the journal. In this note, we present those omitted proofs

Enrichment of rare alleles within epigenetic chromatin marks in the first intron

In previous studies, we demonstrated that some sites in the first intron likely regulate gene expression. In the present work, we sought to further confirm the functional relevance of first intron sites by estimating the quantity of rare alleles in the first intron. A basic hypothesis posited herein is that genomic regions carrying more functionally important sites will have a higher proportion of rare alleles. We estimated the proportions of rare single nucleotide polymorphisms with a minor allele frequency < 0.01 located in several histone marks in the first introns of various genes, and compared them with those in other introns and those in 2-kb upstream regions. As expected, rare alleles were found to be significantly enriched in most of the regulatory sites located in the first introns. Meanwhile, transcription factor binding sites were significantly more enriched in the 2-kb upstream regions (i.e., the regions of putative promoters of genes) than in the first introns. These results strongly support our proposal that the first intron sites of genes may have important regulatory functions in gene expression independent of promoters

AoA-based Position and Orientation Estimation Using Lens MIMO in Cooperative Vehicle-to-Vehicle Systems

Positioning accuracy is a critical requirement for vehicle-to-everything (V2X) use cases. Therefore, this paper derives the theoretical limits of estimation for the position and orientation of vehicles in a cooperative vehicle-to-vehicle (V2V) scenario, using a lens-based multiple-input multiple-output (lens-MIMO) system. Following this, we analyze the Cram$\acute{\text{e}}$r-Rao lower bounds (CRLBs) of the position and orientation estimation and explore a received signal model of a lens-MIMO for the particular angle of arrival (AoA) estimation with a V2V geometric model. Further, we propose a lower complexity AoA estimation technique exploiting the unique characteristics of the lens-MIMO for a single target vehicle; as a result, its estimation scheme is effectively extended by the successive interference cancellation (SIC) method for multiple target vehicles. Given these AoAs, we investigate the lens-MIMO estimation capability for the positions and orientations of vehicles. Subsequently, we prove that the lens-MIMO outperforms a conventional uniform linear array (ULA) in a certain configuration of a lens's structure. Finally, we confirm that the proposed localization algorithm is superior to ULA's CRLB as the resolution of the lens increases in spite of the lower complexity.Comment: 16 pages, 11 figure

Addendum for "A Study of Disturbance Observers with Unknown Relative Degree"

[Preprint] The paper "A Study of Disturbance Observers with Unknown Relative Degree" [1] by the authors could not include the proofs for Theorem 5 and Theorem 6 due to the page limit. We provide them in this supplementary document, and an example is included with simulation results

Anisotropic Dirac fermions in a Bi square net of SrMnBi2

We report the highly anisotropic Dirac fermions in a Bi square net of SrMnBi2, based on a first principle calculation, angle resolved photoemission spectroscopy, and quantum oscillations for high-quality single crystals. We found that the Dirac dispersion is generally induced in the (SrBi)+ layer containing a double-sized Bi square net. In contrast to the commonly observed isotropic Dirac cone, the Dirac cone in SrMnBi2 is highly anisotropic with a large momentum-dependent disparity of Fermi velocities of ~ 8. These findings demonstrate that a Bi square net, a common building block of various layered pnictides, provide a new platform that hosts highly anisotropic Dirac fermions.Comment: 5 pages, 4 figure

Sparse RF Lens Antenna Array Design for AoA Estimation in Wideband Systems: Placement Optimization and Performance Analysis

In this paper, we propose a novel architecture for a lens antenna array (LAA) designed to work with a small number of antennas and enable angle-of-arrival (AoA) estimation for advanced 5G vehicle-to-everything (V2X) use cases that demand wider bandwidths and higher data rates. We derive a received signal in terms of optical analysis to consider the variability of the focal region for different carrier frequencies in a wideband multi-carrier system. By taking full advantage of the beam squint effect for multiple pilot signals with different frequencies, we propose a novel reconfiguration of antenna array (RAA) for the sparse LAA and a max-energy antenna selection (MS) algorithm for the AoA estimation. In addition, this paper presents an analysis of the received power at the single antenna with the maximum energy and compares it to simulation results. In contrast to previous studies on LAA that assumed a large number of antennas, which can require high complexity and hardware costs, the proposed RAA with MS estimation algorithm is shown meets the requirements of 5G V2X in a vehicular environment while utilizing limited RF hardware and has low complexity.Comment: 15 pages, 10 figure