Browse
Submit Data
Databases
API
Help

Dataset Information

13 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Fast smooth second-order sliding mode control for systems with additive colored noises.

ABSTRACT: In this paper, a fast smooth second-order sliding mode control is presented for a class of stochastic systems with enumerable Ornstein-Uhlenbeck colored noises. The finite-time mean-square practical stability and finite-time mean-square practical reachability are first introduced. Instead of treating the noise as bounded disturbance, the stochastic control techniques are incorporated into the design of the controller. The finite-time convergence of the prescribed sliding variable dynamics system is proved by using stochastic Lyapunov-like techniques. Then the proposed sliding mode controller is applied to a second-order nonlinear stochastic system. Simulation results are presented comparing with smooth second-order sliding mode control to validate the analysis.

SUBMITTER: Yang P

PROVIDER: S-EPMC5451072 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Fast smooth second-order sliding mode control for systems with additive colored noises.

Yang Pengfei P Fang Yangwang Y Wu Youli Y Liu Yunxia Y Zhang Danxu D

PloS one 20170531 5

In this paper, a fast smooth second-order sliding mode control is presented for a class of stochastic systems with enumerable Ornstein-Uhlenbeck colored noises. The finite-time mean-square practical stability and finite-time mean-square practical reachability are first introduced. Instead of treating the noise as bounded disturbance, the stochastic control techniques are incorporated into the design of the controller. The finite-time convergence of the prescribed sliding variable dynamics system ...[more]

PMID: 28562639

Similar Datasets

Smooth super-twisting sliding mode control for the class of underactuated systems.

Project description:In this article, Smooth Super-twisting Sliding Mode Control (SSTWSMC) is investigated for the class of underactuated system. In underactuated systems, the control design is not directly applicable as for other systems (known as fully actuated systems). Therefore, at initial step, a nonlinear uncertain model of systems is transformed into the controllable canonical form, and then Smooth Super Twisting (SSTW) based Sliding Mode Control (SMC) is devised for the control design purpose for the considered class. In addition, closed loop stability of the proposed technique is presented in a fascinating way. The effectiveness and supremacy of the proposed control technique is proven by extensive analysis between conventional Sliding Mode Control (SMC), Super twisting (STW) sliding mode control and Smooth Super-twisting Sliding Mode Control (SSTWSMC). The comprehensive analysis evaluates the attributes like robustness enhancement, settling time, control effort, chattering reduction, overshoot, sliding mode convergence, etc. and is supported by simulations as well as practical implementation on ball and beam balancer (which is considered as application example).

| S-EPMC6169871 | biostudies-literature

High-performance fractional order terminal sliding mode control strategy for DC-DC Buck converter.

Project description:This paper presents an adaption of the fractional order terminal sliding mode control (AFTSMC) strategy for DC-DC Buck converter. The following strategy aims to design a novel nonlinear sliding surface function, with a double closed-loop structure of voltage and current. This strategy is a fusion of two characteristics: terminal sliding mode control (TSMC) and fractional order calculation (FOC). In addition, the influence of "the controller parameters" on the "performance of double closed-loop system" is investigated. It is observed that the value of terminal power has to be chosen to make a compromise between start-up and transient response of the converter. Therefore the AFTSMC strategy chooses the value of the terminal power adaptively, and this strategy can lead to the appropriate number of fractional order as well. Furthermore, through the fractional order analysis, the system can reach the sliding mode surface in a finite time. And the theoretical considerations are verified by numerical simulation. The performance of the AFTSMC and TSMC strategies is tested by computer simulations. And the comparison simulation results show that the AFTSMC exhibits a considerable improvement in terms of a faster output voltage response during load changes. Moreover, AFTSMC obtains a faster dynamical response, smaller steady-state error rate and lower overshoot.

| S-EPMC5662226 | biostudies-literature

Dipolar Order Parameters in Large Systems With Fast Spinning.

Project description:Order parameters are a useful tool for quantifying amplitudes of molecular motions. Here we measure dipolar order parameters by recoupling heteronuclear dipole-dipole couplings under fast spinning. We apply symmetry based recoupling methods to samples spinning under magic angle at 60 kHz by employing a variable flip angle compound inversion pulse. We validate the methods by measuring site-specific 15N-1H order parameters of a microcrystalline protein over a small temperature range and the same protein in a large, precipitated complex with antibody. The measurements of the order parameters in the complex are consistent with the observed protein undergoing overall motion within the assembly.

| S-EPMC8699854 | biostudies-literature

A second-order dynamical approach with variable damping to nonconvex smooth minimization.

Project description:We investigate a second-order dynamical system with variable damping in connection with the minimization of a nonconvex differentiable function. The dynamical system is formulated in the spirit of the differential equation which models Nesterov's accelerated convex gradient method. We show that the generated trajectory converges to a critical point, if a regularization of the objective function satisfies the Kurdyka- Lojasiewicz property. We also provide convergence rates for the trajectory formulated in terms of the Lojasiewicz exponent.

| S-EPMC7077366 | biostudies-literature

Polarizable Simulations with Second order Interaction Model - force field and software for fast polarizable calculations: Parameters for small model systems and free energy calculations.

Project description:We are presenting POSSIM (POlarizable Simulations with Second order Interaction Model) - a software package and a set of parameters designed for molecular simulations. The key feature of POSSIM is that the electrostatic polarization is taken into account using a previously introduced fast formalism. This permits cutting computational cost of using the explicit polarization by about an order of magnitude. In this article, parameters for water, methane, ethane, propane, butane, methanol and NMA are introduced. These molecules are viewed as model systems for protein simulations. We have achieved our goal of ca. 0.5 kcal/mol accuracy for gas-phase dimerization energies and no more than 2% deviations in liquid state heats of vaporization and densities. Moreover, free energies of hydration of the polarizable methane, ethane and methanol have been calculated using the statistical perturbation theory. These calculations are a model for calculating protein pKa shifts and ligand binding affinities. The free energies of hydration were found to be 2.12 kcal/mol, 1.80 kcal/mol and -4.95 kcal/mol for methane, ethane and methanol, respectively. The experimentally determined literature values are 1.91 kcal/mol, 1.83 kcal/mol and -5.11 kcal/mol. The POSSIM average error in these absolute free energies of hydration is only about 0.13 kcal/mol. Using the statistical perturbation theory with polarizable force fields is not widespread, and we believe that this work opens road to further development of the POSSIM force field and its applications for obtaining accurate energies in protein-related computer modeling.

| S-EPMC2832335 | biostudies-literature

Smooth and flat phase-locked Kerr frequency comb generation by higher order mode suppression.

Project description:High-Q microresonator is perceived as a promising platform for optical frequency comb generation, via dissipative soliton formation. In order to achieve a higher quality factor and obtain the necessary anomalous dispersion, multi-mode waveguides were previously implemented in Si3N4 microresonators. However, coupling between different transverse mode families in multi-mode waveguides results in periodic disruption of dispersion and quality factor, and consequently causes perturbation to dissipative soliton formation and amplitude modulation to the corresponding spectrum. Careful choice of pump wavelength to avoid the mode crossing region is thus critical in conventional Si3N4 microresonators. Here, we report a novel design of Si3N4 microresonator in which single-mode operation, high quality factor, and anomalous dispersion are attained simultaneously. The novel microresonator is consisted of uniform single-mode waveguides in the semi-circle region, to eliminate bending induced mode coupling, and adiabatically tapered waveguides in the straight region, to avoid excitation of higher order modes. The intrinsic quality factor of the microresonator reaches 1.36 × 10(6) while the group velocity dispersion remains to be anomalous at -50 fs(2)/mm. With this novel microresonator, we demonstrate that broadband phase-locked Kerr frequency combs with flat and smooth spectra can be generated by pumping at any resonances in the optical C-band.

| S-EPMC4867630 | biostudies-other

3D reconstruction method based on second-order semiglobal stereo matching and fast point positioning Delaunay triangulation.

Project description:Binocular vision uses the parallax principle of the human eye to obtain 3D information of an object, which is widely used as an important means of acquiring 3D information for 3D reconstruction tasks. To improve the accuracy and efficiency of 3D reconstruction, we propose a 3D reconstruction method that combines second-order semiglobal matching, guided filtering and Delaunay triangulation. First, the existing second-order semiglobal matching method is improved, and the smoothness constraint of multiple angle directions is added to the matching cost to generate a more robust disparity map. Second, the 3D coordinates of all points are calculated by combining camera parameters and disparity maps to obtain the 3D point cloud, which is smoothed by guided filtering to remove noise points and retain details. Finally, a method to quickly locate the insertion point and accelerate Delaunay triangulation is proposed. The surface of the point cloud is reconstructed by Delaunay triangulation based on fast point positioning to improve the visibility of the 3D model. The proposed approach was evaluated using the Middlebury and KITTI datasets. The experimental results show that the proposed second-order semiglobal matching method has higher accuracy than other stereo matching methods and that the proposed Delaunay triangulation method based on fast point location requires less time than the original Delaunay triangulation.

| S-EPMC8789135 | biostudies-literature

Second-Order Footsteps Illusions.

Project description:In the "footsteps illusion", light and dark squares travel at constant speed across black and white stripes. The squares appear to move faster and slower as their contrast against the stripes varies. We now demonstrate some second-order footsteps illusions, in which all edges are defined by colors or textures-even though luminance-based neural motion detectors are blind to such edges.

| S-EPMC4975121 | biostudies-literature

Fast mode decomposition in few-mode fibers.

Project description:Retrieval of the optical phase information from measurement of intensity is of a high interest because this would facilitate simple and cost-efficient techniques and devices. In scientific and industrial applications that exploit multi-mode fibers, a prior knowledge of spatial mode structure of the fiber, in principle, makes it possible to recover phases using measured intensity distribution. However, current mode decomposition algorithms based on the analysis of the intensity distribution at the output of a few-mode fiber, such as optimization methods or neural networks, still have high computational costs and high latency that is a serious impediment for applications, such as telecommunications. Speed of signal processing is one of the key challenges in this approach. We present a high-performance mode decomposition algorithm with a processing time of tens of microseconds. The proposed mathematical algorithm that does not use any machine learning techniques, is several orders of magnitude faster than the state-of-the-art deep-learning-based methods. We anticipate that our results can stimulate further research on algorithms beyond popular machine learning methods and they can lead to the development of low-cost phase retrieval receivers for various applications of few-mode fibers ranging from imaging to telecommunications.

| S-EPMC7606473 | biostudies-literature

A second-order iterated smoothing algorithm.

Project description:Simulation-based inference for partially observed stochastic dynamic models is currently receiving much attention due to the fact that direct computation of the likelihood is not possible in many practical situations. Iterated filtering methodologies enable maximization of the likelihood function using simulation-based sequential Monte Carlo filters. Doucet et al. (2013) developed an approximation for the first and second derivatives of the log likelihood via simulation-based sequential Monte Carlo smoothing and proved that the approximation has some attractive theoretical properties. We investigated an iterated smoothing algorithm carrying out likelihood maximization using these derivative approximations. Further, we developed a new iterated smoothing algorithm, using a modification of these derivative estimates, for which we establish both theoretical results and effective practical performance. On benchmark computational challenges, this method beat the first-order iterated filtering algorithm. The method's performance was comparable to a recently developed iterated filtering algorithm based on an iterated Bayes map. Our iterated smoothing algorithm and its theoretical justification provide new directions for future developments in simulation-based inference for latent variable models such as partially observed Markov process models.

| S-EPMC5573285 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data