Universal direct tuner for loop control in industry

This paper introduces a direct universal (automatic) tuner for basic loop control in industrial applications. The direct feature refers to the fact that a first-hand model, such as a step response first-order plus dead time approximation, is not required. Instead, a point in the frequency domain and the corresponding slope of the loop frequency response is identified by single test suitable for industrial applications. The proposed method has been shown to overcome pitfalls found in other (automatic) tuning methods and has been validated in a wide range of common and exotic processes in simulation and experimental conditions. The method is very robust to noise, an important feature for real life industrial applications. Comparison is performed with other well-known methods, such as approximate M-constrained integral gain optimization (AMIGO) and Skogestad internal model controller (SIMC), which are indirect methods, i.e., they are based on a first-hand approximation of step response data. The results indicate great similarity between the results, whereas the direct method has the advantage of skipping this intermediate step of identification. The control structure is the most commonly used in industry, i.e., proportional-integral-derivative (PID) type. As the derivative action is often not used in industry due to its difficult choice, in the proposed method, we use a direct relation between the integral and derivative gains. This enables the user to have in the tuning structure the advantages of the derivative action, therefore much improving the potential of good performance in real life control applications

A Second Order Godunov Method for Multidimensional Relativistic Magnetohydrodynamics

We describe a new Godunov algorithm for relativistic magnetohydrodynamics (RMHD) that combines a simple, unsplit second order accurate integrator with the constrained transport (CT) method for enforcing the solenoidal constraint on the magnetic field. A variety of approximate Riemann solvers are implemented to compute the fluxes of the conserved variables. The methods are tested with a comprehensive suite of multidimensional problems. These tests have helped us develop a hierarchy of correction steps that are applied when the integration algorithm predicts unphysical states due to errors in the fluxes, or errors in the inversion between conserved and primitive variables. Although used exceedingly rarely, these corrections dramatically improve the stability of the algorithm. We present preliminary results from the application of these algorithms to two problems in RMHD: the propagation of supersonic magnetized jets, and the amplification of magnetic field by turbulence driven by the relativistic Kelvin-Helmholtz instability (KHI). Both of these applications reveal important differences between the results computed with Riemann solvers that adopt different approximations for the fluxes. For example, we show that use of Riemann solvers which include both contact and rotational discontinuities can increase the strength of the magnetic field within the cocoon by a factor of ten in simulations of RMHD jets, and can increase the spectral resolution of three-dimensional RMHD turbulence driven by the KHI by a factor of 2. This increase in accuracy far outweighs the associated increase in computational cost. Our RMHD scheme is publicly available as part of the Athena code.Comment: 75 pages, 28 figures, accepted for publication in ApJS. Version with high resolution figures available from http://jila.colorado.edu/~krb3u/Athena_SR/rmhd_method_paper.pd

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

Fractional Order State Feedback Control for Improved Lateral Stability of Semi-Autonomous Commercial Heavy Vehicles

With the growing development of autonomous and semi-autonomous large commercial heavy vehicles, the lateral stability control of articulated vehicles have caught the attention of researchers recently. Active vehicle front steering (AFS) can enhance the handling performance and stability of articulated vehicles for an emergency highway maneuver scenario. However, with large vehicles such tractor-trailers, the system becomes more complex to control and there is an increased occurrence of instabilities. This research investigates a new control scheme based on fractional calculus as a technique that ensures lateral stability of articulated large heavy vehicles during evasive highway maneuvering scenarios. The control method is first implemented to a passenger vehicle model with 2-axles based on the well-known “bicycle model”. The model is then extended and applied onto larger three-axle commercial heavy vehicles in platooning operations. To validate the proposed new control algorithm, the system is linearized and a fractional order PI state feedback control is developed based on the linearized model. Then using Matlab/Simulink, the developed fractional-order linear controller is implemented onto the non-linear tractor-trailer dynamic model. The tractor-trailer system is modeled based on the conventional integer-order techniques and then a non-integer linear controller is developed to control the system. Overall, results confirm that the proposed controller improves the lateral stability of a tractor-trailer response time by 20% as compared to a professional truck driver during an evasive highway maneuvering scenario. In addition, the effects of variable truck cargo loading and longitudinal speed are evaluated to confirm the robustness of the new control method under a variety of potential operating conditions

Realization of Fractance Device using Continued Fraction Expansion Method

The realization of fractional-order circuits is an emerging area of research for people working in the areas of control systems, signal processing and other related fields. In this paper, an attempt is made to realize fractance devices. The continued fraction expansion formula is used to calculate the fractance device's rational approximation. For the simulation in the experimentation, the third-order approximation for fractional order, α = -1/2, -1/3, -1/4 is used. For the aim of mathematical simulation, the MATLAB platform was used. The proposed rational approximation is used to create a circuit. The TINA programme is used to simulate circuits. It has been discovered that the simulation and theoretical conclusions are in agreement

An adaptive fixed-mesh ALE method for free surface flows

In this work we present a Fixed-Mesh ALE method for the numerical simulation of free surface flows capable of using an adaptive finite element mesh covering a background domain. This mesh is successively refined and unrefined at each time step in order to focus the computational effort on the spatial regions where it is required. Some of the main ingredients of the formulation are the use of an Arbitrary-Lagrangian–Eulerian formulation for computing temporal derivatives, the use of stabilization terms for stabilizing convection, stabilizing the lack of compatibility between velocity and pressure interpolation spaces, and stabilizing the ill-conditioning introduced by the cuts on the background finite element mesh, and the coupling of the algorithm with an adaptive mesh refinement procedure suitable for running on distributed memory environments. Algorithmic steps for the projection between meshes are presented together with the algebraic fractional step approach used for improving the condition number of the linear systems to be solved. The method is tested in several numerical examples. The expected convergence rates both in space and time are observed. Smooth solution fields for both velocity and pressure are obtained (as a result of the contribution of the stabilization terms). Finally, a good agreement between the numerical results and the reference experimental data is obtained.Postprint (published version