Application of Memristors in Microwave Passive Circuits

The recent implementation of the fourth fundamental electric circuit element, the memristor, opened new vistas in many fields of engineering applications. In this paper, we explore several RF/microwave passive circuits that might benefit from the memristor salient characteristics. We consider a power divider, coupled resonator bandpass filters, and a low-reflection quasi-Gaussian lowpass filter with lossy elements. We utilize memristors as configurable linear resistors and we propose memristor-based bandpass filters that feature suppression of parasitic frequency pass bands and widening of the desired rejection band. The simulations are performed in the time domain, using LTspice, and the RF/microwave circuits under consideration are modeled by ideal elements available in LTspice

Enhancing Autonomy in VTOL Aircraft Based on Symbolic Computation Algorithms

Research into the autonomy of small Unmanned Aerial Vehicles (UAVs), and especially on Vertical Take Off and Landing (VTOL) systems has intensified significantly in recent years. This paper develops a generic model of a VTOL UAV in symbolic form. The novelty of this work stems from the designed Model Predictive Control (MPC) algorithm based on this symbolic model. The MPC algorithm is compared with a state-of-the-art Linear Quadratic Regulator algorithm in attitude rate acquisition and its more accurate performance and robustness to noise is demonstrated. Results for the controllers designed for each of the aircraft’s angular rates are presented in response to input disturbances

Workshop on Verification and Theorem Proving for Continuous Systems (NetCA Workshop 2005)

Oxford, UK, 26 August 200

Methods for testing of analog circuits

Práce se zabývá metodami pro testování lineárních analogových obvodů v kmitočtové oblasti. Cílem je navrhnout efektivní metody pro automatické generování testovacího plánu. Snížením počtu měření a výpočetní náročnosti lze výrazně snížit náklady za testování. Práce se zabývá multifrekveční parametrickou poruchovou analýzou, která byla plně implementována do programu Matlab. Vhodnou volbou testovacích kmitočtů lze potlačit chyby měření a chyby způsobené výrobními tolerancemi obvodových prvků. Navržené metody pro optimální volbu kmitočtů byly statisticky ověřeny metodou MonteCarlo. Pro zvýšení přesnosti a snížení výpočetní náročnosti poruchové analýzy byly vyvinuty postupy založené na metodě nejmenších čtverců a přibližné symbolické analýze.The thesis deals with methods for testing of linear analog circuits in the frequency domain. The goal is to develop new efficient methods for automatic test plan generation. To reduce test costs a minimum number of measurements as well as less computational demands are the fundamental aims. The thesis is focused on the multi-frequency parametric fault diagnosis which was fully implemented in the Matlab program. The fundamental problem consists in selection of test frequencies which can reduce the influences of measurement errors and errors caused by tolerances of well-working components. The proposed methods for test frequency selection were statistically verified by the MonteCarlo method. To improve the accuracy and reduce the computational complexity of fault diagnosis, the methods based on least-square techniques and approximate symbolic analysis were presented.

Signal Processing Research Program

Contains table of contents for Part III, table of contents for Section 1, an introduction and reports on fourteen research projects.Charles S. Draper Laboratory Contract DL-H-404158U.S. Navy - Office of Naval Research Grant N00014-89-J-1489National Science Foundation Grant MIP 87-14969Battelle LaboratoriesTel-Aviv University, Department of Electronic SystemsU.S. Army Research Office Contract DAAL03-86-D-0001The Federative Republic of Brazil ScholarshipSanders Associates, Inc.Bell Northern Research, Ltd.Amoco Foundation FellowshipGeneral Electric FellowshipNational Science Foundation FellowshipU.S. Air Force - Office of Scientific Research FellowshipU.S. Navy - Office of Naval Research Grant N00014-85-K-0272Natural Science and Engineering Research Council of Canada - Science and Technology Scholarshi

Modelling chassis flexibility in vehicle dynamics simulation

This thesis deals with the development of advanced mathematical models for the assessment of the influence of chassis flexibility on vehicle handling qualities. A review of the literature relevant to the subject is presented and discussed in the first part of the thesis. A preliminary model that includes chassis flexibility is then developed and employed for a first assessment of the significance of chassis flexibility. In the second part of the thesis a symbolic multibody library for vehicle dynamics simulations is introduced. This library constitutes the basis for the development of an advanced 14-degrees-of-freedom vehicle model that includes chassis flexibility. The model is then demonstrated using a set of data relative to a real vehicle. Finally, simulation results are discussed and conclusions are presented. The advanced model fully exploits a novel multibody formulation which represent the kinematics and the dynamics of the system with a level of accuracy which is typical of numeric multibody models while retaining the benefits of purpose-developed hand- derived models. More specifically, a semi-recursive formulation, a velocity projection technique and a symbolic development are, for the first time, coupled with flexible body modelling. The effect of chassis flexibility on vehicle handling is observed through the analysis of open- and closed-loop manoeuvres. Results show that chassis flexibility induces variations of lateral load transfer distribution and suspension kinematics that sensibly affect the steady-state behaviour of the vehicle. Further effects on dynamic response and high-speed stability are demonstrated. Also, optimal control theory is employed to demonstrate the existence of a strict correlation between chassis flexibility and driver behaviour. The research yields new insights into the dynamics of vehicles with a flexible chassis and highlights critical aspects of chassis design. Although the focus is on sports and race cars, both the modelling approach and the results can be extended to other vehicles.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks

Physics-informed PointNet: A deep learning solver for steady-state incompressible flows and thermal fields on multiple sets of irregular geometries

We present a novel physics-informed deep learning framework for solving steady-state incompressible flow on multiple sets of irregular geometries by incorporating two main elements: using a point-cloud based neural network to capture geometric features of computational domains, and using the mean squared residuals of the governing partial differential equations, boundary conditions, and sparse observations as the loss function of the network to capture the physics. While the solution of the continuity and Navier-Stokes equations is a function of the geometry of the computational domain, current versions of physics-informed neural networks have no mechanism to express this functionally in their outputs, and thus are restricted to obtain the solutions only for one computational domain with each training procedure. Using the proposed framework, three new facilities become available. First, the governing equations are solvable on a set of computational domains containing irregular geometries with high variations with respect to each other but requiring training only once. Second, after training the introduced framework on the set, it is now able to predict the solutions on domains with unseen geometries from seen and unseen categories as well. The former and the latter both lead to savings in computational costs. Finally, all the advantages of the point-cloud based neural network for irregular geometries, already used for supervised learning, are transferred to the proposed physics-informed framework. The effectiveness of our framework is shown through the method of manufactured solutions and thermally-driven flow for forward and inverse problems

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

Proceedings of the Third International Workshop on Neural Networks and Fuzzy Logic, volume 1

Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by the National Aeronautics and Space Administration and cosponsored by the University of Houston, Clear Lake. The workshop was held June 1-3, 1992 at the Lyndon B. Johnson Space Center in Houston, Texas. During the three days approximately 50 papers were presented. Technical topics addressed included adaptive systems; learning algorithms; network architectures; vision; robotics; neurobiological connections; speech recognition and synthesis; fuzzy set theory and application, control, and dynamics processing; space applications; fuzzy logic and neural network computers; approximate reasoning; and multiobject decision making