University of Texas at Arlington

About: University of Texas at Arlington is a education organization based out in Arlington, Texas, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 11758 authors who have published 28598 publications receiving 801626 citations. The organization is also known as: UT Arlington & University of Texas-Arlington.

Transmission bandpass guided-mode resonance filters.

Abstract: It is shown that the guided-mode resonance effects associated with waveguide gratings can be used to realize transmission bandpass filters. The key idea is the integration of the resonant waveguide gratings into a dielectric multilayer structure that efficiently reflects the off-resonance spectral components while passing the resonant part. This concept is applied to design multilayer transmission bandpass filters with high efficiency, narrow linewidth, symmetrical response, and low sidebands.

Optimal Tracking Control of Unknown Discrete-Time Linear Systems Using Input-Output Measured Data

Abstract: In this paper, an output-feedback solution to the infinite-horizon linear quadratic tracking (LQT) problem for unknown discrete-time systems is proposed. An augmented system composed of the system dynamics and the reference trajectory dynamics is constructed. The state of the augmented system is constructed from a limited number of measurements of the past input, output, and reference trajectory in the history of the augmented system. A novel Bellman equation is developed that evaluates the value function related to a fixed policy by using only the input, output, and reference trajectory data from the augmented system. By using approximate dynamic programming, a class of reinforcement learning methods, the LQT problem is solved online without requiring knowledge of the augmented system dynamics only by measuring the input, output, and reference trajectory from the augmented system. We develop both policy iteration (PI) and value iteration (VI) algorithms that converge to an optimal controller that require only measuring the input, output, and reference trajectory data. The convergence of the proposed PI and VI algorithms is shown. A simulation example is used to verify the effectiveness of the proposed control scheme.

Combination of the searches for pair-produced vectorlike partners of the third-generation quarks at s =13 TeV with the ATLAS detector

Abstract: A combination of the searches for pair-produced vectorlike partners of the top and bottom quarks in various decay channels (T -> Zt/Wb/Ht, B -> Zb/Wt/Hb) is performed using 36.1 fb(-1) of pp ...

Synchronization of discrete-time multi-agent systems on graphs using H 2 -Riccati design

Abstract: In this paper design methods are given for synchronization control of discrete-time multi-agent systems on directed communication graphs. The graph properties complicate the design of synchronization controllers due to the interplay between the eigenvalues of the graph Laplacian matrix and the required stabilizing gains. A method is given herein, based on an H 2 type Riccati equation, that decouples the design of the synchronizing gains from the detailed graph properties. A condition for synchronization is given based on the relation of the graph eigenvalues to a bounded circular region in the complex plane that depends on the agent dynamics and the Riccati solution. This condition relates the Mahler measure of the node dynamics system matrix to the connectivity properties of the communication graph. The notion of ‘synchronizing region’ is used. An example shows the effectiveness of these design methods for achieving synchronization in cooperative discrete-time systems.