Research of K∞-Robust Systems with Constrained Control

2018 ◽  
Vol 19 (11) ◽  
pp. 699-706 ◽  
Author(s):  
G. A. Rustamov ◽  
V. G. Farchadov ◽  
G. R. Rustamov
Keyword(s):  
Control Systems ◽  
Initial Conditions ◽  
Slow Motion ◽  
Initial Time ◽  
Dynamic Mode ◽  
Time Interval ◽  
Initial Instant ◽  
Initial State ◽  
Static Mode ◽  
Robust Systems

At the present, there are no satisfactory engineering solutions related to the synthesis of robust regulators taking into account the constraints on control. In this connection, it is important to study the influence of saturation effect of the controller on the robust properties of systems. In this paper, this problem is considered in connection with K∞-robust control systems with a high gain. It is shown that in control limit systems, in particular, K∞-robust systems at the initial instant of time, the control assumes an excessively large value. This ensures the robustness of the dynamic mode. The reason for this feature is related to the fact that at the initial instant of time the initial conditions has a great importance. The main reason for the deterioration of robust properties is due to the tight control in the initial time interval. Provision of robustness of the static mode does not require great control efforts. For the first time, using computer graphics in a three-dimensional coordinate system, taking into account the time, a visual representation of the sections of phase trajectories pertaining to different types of movements is given: rapid motion from an arbitrary initial state that ensures hitting the imaging point into the degenerate trajectory; slow motion along this trajectory; steady-state motion within the specified accuracy. For the limit control systems, an integral robustness estimate is proposed, which consists in calculating the integral of the absolute value of the slow motion trajectory. This indicator characterizes the discrepancy (dispersion) of the real trajectory with respect to the limiting trajectory. The reliability of theoretical reasoning is confirmed by solving a model problem in the block-vision environment of Matlab/Simulink.

scholarly journals Handling Initial Conditions in Vector Fitting for Real Time Modeling of Power System Dynamics

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2471
Author(s):  
Tommaso Bradde ◽  
Samuel Chevalier ◽  
Marco De Stefano ◽  
Stefano Grivet-Talocia ◽  
Luca Daniel
Keyword(s):  
Dynamical Systems ◽  
Power System ◽  
System Dynamics ◽  
Real Time ◽  
Initial Conditions ◽  
Test System ◽  
Initial State ◽  
Power System Dynamics ◽  
Vector Fitting ◽  
Time Modeling

This paper develops a predictive modeling algorithm, denoted as Real-Time Vector Fitting (RTVF), which is capable of approximating the real-time linearized dynamics of multi-input multi-output (MIMO) dynamical systems via rational transfer function matrices. Based on a generalization of the well-known Time-Domain Vector Fitting (TDVF) algorithm, RTVF is suitable for online modeling of dynamical systems which experience both initial-state decay contributions in the measured output signals and concurrently active input signals. These adaptations were specifically contrived to meet the needs currently present in the electrical power systems community, where real-time modeling of low frequency power system dynamics is becoming an increasingly coveted tool by power system operators. After introducing and validating the RTVF scheme on synthetic test cases, this paper presents a series of numerical tests on high-order closed-loop generator systems in the IEEE 39-bus test system.

scholarly journals The VIT Transform Approach to Discrete-Time Signals and Linear Time-Varying Systems

Eng ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 99-125
Author(s):  
Edward W. Kamen
Keyword(s):  
Discrete Time ◽  
Initial Conditions ◽  
Linear Time ◽  
Order Term ◽  
Initial Time ◽  
Time Varying ◽  
Varying Coefficients ◽  
Time Signals ◽  
Time Varying Systems ◽  
Time Varying Coefficients

A transform approach based on a variable initial time (VIT) formulation is developed for discrete-time signals and linear time-varying discrete-time systems or digital filters. The VIT transform is a formal power series in z−1, which converts functions given by linear time-varying difference equations into left polynomial fractions with variable coefficients, and with initial conditions incorporated into the framework. It is shown that the transform satisfies a number of properties that are analogous to those of the ordinary z-transform, and that it is possible to do scaling of z−i by time functions, which results in left-fraction forms for the transform of a large class of functions including sinusoids with general time-varying amplitudes and frequencies. Using the extended right Euclidean algorithm in a skew polynomial ring with time-varying coefficients, it is shown that a sum of left polynomial fractions can be written as a single fraction, which results in linear time-varying recursions for the inverse transform of the combined fraction. The extraction of a first-order term from a given polynomial fraction is carried out in terms of the evaluation of zi at time functions. In the application to linear time-varying systems, it is proved that the VIT transform of the system output is equal to the product of the VIT transform of the input and the VIT transform of the unit-pulse response function. For systems given by a time-varying moving average or an autoregressive model, the transform framework is used to determine the steady-state output response resulting from various signal inputs such as the step and cosine functions.

scholarly journals Assessing Automated Facial Action Unit Detection Systems for Analyzing Cross-Domain Facial Expression Databases

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4222
Author(s):  
Shushi Namba ◽  
Wataru Sato ◽  
Masaki Osumi ◽  
Koh Shimokawa
Keyword(s):  
Affective Computing ◽  
Detection System ◽  
Characteristic Curve ◽  
Unmet Need ◽  
Systematic Evaluation ◽  
Dynamic Mode ◽  
Coding System ◽  
Static Mode ◽  
Action Unit ◽  
Facial Action

In the field of affective computing, achieving accurate automatic detection of facial movements is an important issue, and great progress has already been made. However, a systematic evaluation of systems that now have access to the dynamic facial database remains an unmet need. This study compared the performance of three systems (FaceReader, OpenFace, AFARtoolbox) that detect each facial movement corresponding to an action unit (AU) derived from the Facial Action Coding System. All machines could detect the presence of AUs from the dynamic facial database at a level above chance. Moreover, OpenFace and AFAR provided higher area under the receiver operating characteristic curve values compared to FaceReader. In addition, several confusion biases of facial components (e.g., AU12 and AU14) were observed to be related to each automated AU detection system and the static mode was superior to dynamic mode for analyzing the posed facial database. These findings demonstrate the features of prediction patterns for each system and provide guidance for research on facial expressions.

The synthesis method of regulators for multichannel systems using neural networks

2020 ◽  
pp. 111-118
Author(s):  
Александр Александрович Воевода ◽  
Дмитрий Олегович Романников
Keyword(s):  
Neural Networks ◽  
Reinforcement Learning ◽  
Automatic Control ◽  
Control Systems ◽  
Synthesis Method ◽  
Neural Net ◽  
Initial State ◽  
Set Point ◽  
Automatic Control Systems ◽  
Policy Gradient

Синтез регуляторов для многоканальных систем - актуальная и сложная задача. Одним из возможных способов синтеза является применение нейронных сетей. Нейронный регулятор либо обучают на предварительно рассчитанных данных, либо используют для настройки параметров ПИД-регулятора из начального устойчивого положения замкнутой системы. Предложено использовать нейронные сети для регулирования двухканального объекта, при этом обучение будет выполняться из неустойчивого (произвольного) начального положения с применением методов обучения нейронных сетей с подкреплением. Предложена структура нейронной сети и замкнутой системы, в которой уставка задается при помощи входного параметра нейронной сети регулятора The problem for synthesis of automatic control systems is hard, especially for multichannel objects. One of the approaches is the use of neural networks. For the approaches that are based on the use of reinforcement learning, there is an additional issue - supporting of range of values for the set points. The method of synthesis of automatic control systems using neural networks and the process of its learning with reinforcement learning that allows neural networks learning for supporting regulation is proposed in the predefined range of set points. The main steps of the method are 1) to form a neural net input as a state of the object and system set point; 2) to perform modelling of the system with a set of randomly generated set points from the desired range; 3) to perform a one-step of the learning using the Deterministic Policy Gradient method. The originality of the proposed method is that, in contrast to existing methods of using a neural network to synthesize a controller, the proposed method allows training a controller from an unstable initial state in a closed system and set of a range of set points. The method was applied to the problem of stabilizing the outputs of a two-channel object, for which stabilization both outputs and the first near the input set point is required

Alloy surface composition resulting from fabrication, as determined by s.i.m.s. (secondary ion mass spectrometry)

1980 ◽  
Vol 295 (1413) ◽  
pp. 134-135
Keyword(s):  
Secondary Ion Mass Spectrometry ◽  
Surface Composition ◽  
Ion Beam ◽  
Sample Surface ◽  
Beam Current ◽  
Ion Source ◽  
Beam Current Density ◽  
Dynamic Mode ◽  
Static Mode ◽  
Subsequent Performance

In s.i.m.s. the sample surface is ion bombarded and the emitted secondary ions are mass analysed. When used in the static mode with very low primary ion beam current densities (10 -11 A/mm 2 ), the technique analyses the outermost atomic layers with the following advantages (Benninghoven 1973, I975): the structural—chemical nature of the surface may be deduced from the masses of the ejected ionized clusters of atoms; detection of hydrogen and its compounds is possible; sensitivity is extremely high (10 -6 monolayer) for a number of elements. Composition profiles are obtained by increasing the primary beam current density (dynamic mode) or by combining the technique in the static mode with ion beam machining with a separate, more powerful ion source. The application of static s.i.m.s. in metallurgy has been explored by analysing a variety of alloy surfaces after fabrication procedures in relation to surface quality and subsequent performance. In a copper—silver eutectic alloy braze it was found that the composition of the solid surface depended markedly on its pretreatment. Generally there was a surface enrichment of copper relative to silver in melting processes while sawing and polishing enriched the surface in silver

Large deviations in linear control systems with nonzero initial conditions

2015 ◽  
Vol 76 (6) ◽  
pp. 957-976 ◽  
Author(s):  
B. T. Polyak ◽  
A. A. Tremba ◽  
M. V. Khlebnikov ◽  
P. S. Shcherbakov ◽  
G. V. Smirnov
Keyword(s):  
Large Deviations ◽  
Control Systems ◽  
Initial Conditions ◽  
Linear Control ◽  
Linear Control Systems

scholarly journals Study of the influence of initial-state fluctuations on hydrodynamic simulations

2020 ◽  
Vol 245 ◽  
pp. 06005
Author(s):  
Marcin Słodkowski ◽  
Patryk Gawryszewski ◽  
Dominik Setniewski
Keyword(s):  
Initial Conditions ◽  
Graphics Processing Unit ◽  
Heavy Ion ◽  
Processing Unit ◽  
Initial State ◽  
Final State ◽  
Hydrodynamic Simulation ◽  
Hydrodynamic Simulations ◽  
Cartesian Coordinate ◽  
Ion Collision

In this work, we are focusing on assessing the contribution of the initial-state fluctuations of heavy ion collision in the hydrodynamic simulations. We are trying to answer the question of whether the hydrodynamic simulation retains the same level of fluctuation in the final-state as for the initial stage. In another scenario, the hydrodynamic simulations of the fluctuation drowns in the final distribution of expanding matter. For this purpose, we prepared sufficient relativistic hydrodynamic program to study A+A interaction which allows analysing initial-state fluctuations in the bulk nuclear matter. For such an assumption, it is better to use high spatial resolution. Therefore, we applied the (3+1) dimensional Cartesian coordinate system. We implemented our program using parallel computing on graphics cards processors - Graphics Processing Unit (GPU). Simulations were carried out with various levels of fluctuation in initial conditions using the average method of events coming from UrQMD models. Energy density distributions were analysed and the contribution of fluctuations in initial conditions was assessed in the hydrodynamic simulation.

scholarly journals Probability distributions of COVID-19 tweet posted trends use a nonhomogeneous Poisson process

2020 ◽  
Vol 1 (4) ◽  
pp. 229-238
Author(s):  
Devi Munandar ◽  
Sudradjat Supian ◽  
Subiyanto Subiyanto
Keyword(s):  
Social Media ◽  
Poisson Process ◽  
Exponential Distribution ◽  
Probability Distributions ◽  
Nonhomogeneous Poisson Process ◽  
Time Interval ◽  
Initial State ◽  
Time Intervals ◽  
Time Parameters ◽  
Parameter Values

The influence of social media in disseminating information, especially during the COVID-19 pandemic, can be observed with time interval, so that the probability of number of tweets discussed by netizens on social media can be observed. The nonhomogeneous Poisson process (NHPP) is a Poisson process dependent on time parameters and the exponential distribution having unequal parameter values and, independently of each other. The probability of no occurrence an event in the initial state is one and the probability of an event in initial state is zero. Using of non-homogeneous Poisson in this paper aims to predict and count the number of tweet posts with the keyword coronavirus, COVID-19 with set time intervals every day. Posting of tweets from one time each day to the next do not affect each other and the number of tweets is not the same. The dataset used in this study is crawling of COVID-19 tweets three times a day with duration of 20 minutes each crawled for 13 days or 39 time intervals. The result of this study obtained predictions and calculated for the probability of the number of tweets for the tendency of netizens to post on the situation of the COVID-19 pandemic.

Conducting Polymer nanoComposites (CPC): Nanocharacterisation of layer by layer sprayed PMMA-CNT vapour sensors by Atomic force Microscopy in current Sensing Mode (CS-AFM)

2008 ◽  
Vol 1143 ◽  
Author(s):  
Bijandra Kumar ◽  
Mickaël Castro ◽  
Jianbo Lu ◽  
Jean-François Feller
Keyword(s):  
Atomic Force Microscopy ◽  
Spray Deposition ◽  
Dynamic Mode ◽  
Layer By Layer ◽  
Initial State ◽  
Contact Mode ◽  
Current Sensing ◽  
Multi Wall Carbon Nanotubes ◽  
Force Microscopy ◽  
Atomic Force

ABSTRACTOrganic vapour sensors based on poly (methylmethacrylate)-multi-wall carbon nanotubes (PMMA-CNT) conductive polymer nanocomposite (CPC) were developed via layer by layer technique by spray deposition. CPC Sensors were exposed to three different classes of solvents (chloroform, methanol and water) and their chemo-electrical properties were followed as a function of CNTcontent in dynamic mode. Detection time was found to be shorter than that necessary for full recovery of initial state. CNT real three dimensional network has been visualized by Atomic force microscopy in a field assisted intermittent contact mode. More interestingly real conductive network system and electrical ability of CPC have been explored by current-sensing atomic force microscopy (CS-AFM). Realistic effect of voltage on electrical conductivity has been found linear.

Sign in / Sign up

Export Citation Format

Share Document