Efficient Variable Step Research Articles

Robust and Accurate Monocular Pose Tracking for Large Pose Shift

Tracking the pose of a specific rigid object from monocular sequences is a basic problem in computer vision. State-of-the-art methods assume motion continuity between two consecutive frames. However, drastic relative motion causes large inter-frame pose shifts, especially in applications such as robotic grasping, failed satellite maintenance and space debris removal. Large pose shifts interrupt the inter-frame motion continuity leading to tracking failure. In this paper, we propose a robust and accurate monocular pose tracking method for tracking objects with large pose shifts. Using an indexable sparse viewpoint model to represent the object 3D geometry, we propose establishing a transitional view, which is searched for in an efficient variable-step way, to recover motion continuity. Then, a region-based optimization algorithm is adopted to optimize the pose based on the transitional view. Finally, we use a single-rendering-based pose refinement process to achieve highly accurate pose results. The experiments on the region-based object tracking (RBOT) dataset, the modified RBOT dataset, the synthetic large pose shift sequences and real sequences demonstrated that the proposed method achieved superior performance to the state-of-the-art methods in tracking objects with large pose shifts.

An efficient variable-step P&O maximum power point tracking technique for grid-connected wind energy conversion system

This paper proposes an efficient modular sector variable-step perturb and observe (VSPO) maximum power point tracking algorithm. The proposed algorithm enhances the speed tracking and minimizes oscillations level problems associated with traditional P&O methods. The routine of generating the variable step sizes depends on splitting the (P–ω) characteristic curve of wind turbines into modular sectors, in which the perturbation step size for each sector is selected by comparing a suggested ratio with another specified ratio designed according to the required accuracy. By continuously observing the distance between the actual rotor speed and the optimal rotor speed, the VSPO technique applies variable perturbation step sizes according to the current operating sector. Moreover, a wind speed estimation technique is used as a replacement of distributed anemometers for tracking the optimal rotor speed at different wind speeds. The studied system configuration includes three-phase back-to-back converter which is used to connect a 1.5 MW permanent magnet synchronous generator into the utility grid. Furthermore, the model predictive control is used for current control loop in the machine-side converter. To demonstrate the performance of the proposed algorithm, its simulation results are compared with the simulation results of conventional P&O technique under step and random wind variations. In addition, the algorithm performance is studied with real wind data (Hokkaido Island, Japan) using MATLAB/SIMULINK environment. Simulation results show that the VSPO ensures the high tracking speed of maximum power point, while the steady-state oscillation is significantly reduced. The proposed algorithm enhances the system efficiency by 3.5% over the conventional one.

Efficient reduction of PLI in ECG signal using new variable step size least mean fourth adaptive algorithm

It is very important in remote cardiac diagnosis to extract pure ECG signal from the contaminated recordings of the signal. When recording the ECG signal in the laboratory, the signal is affected by numerous artifacts. Varies artifacts generally degrades the signal quality are PLI, EM, MA and EM. In addition to these, the channel noise also added when transmitting signal from remote location to diagnosis center for analyzing the signal. There are several approaches are used to reduce the noise present in the ECG signal. From the literature it is proven that compared to non adaptive filters, adaptive filters play vital role to trace the random changes in the corrupted signals. In this paper, we proposed efficient Variable step size leaky least mean fourth algorithm and its sign versions for reducing the complexity. These algorithms shows that it gives low steady state error due to least mean fourth and fast convergence rate that is it tracks the input signal quickly because of its variable step size is high at initial iterations of signal compared to the LMS algorithm. The performance of the algorithm is evaluated using SNR, frequency spectrum, MSE, misadjustment and convergence characteristics.

Modified efficient perturb and observe maximum power point tracking technique for grid-tied PV system

Conventional maximum power point tracking (MPPT) techniques such as Perturb and Observe (P&O) and Incremental Conductance (IncCond) are used in photovoltaic (PV) systems to extract the Maximum Power (MP). These algorithms cannot track the Maximum Power Point (MPP) under a rapidly changing insolation. This paper introduces a modified efficient variable step P&O (VSPO) algorithm as an attempt to solve the aforementioned problem. The VSPO technique divides the PV-array operation region into four operating sectors. With the help of these four sectors, the step-size is changed according to how the sector far from the MPP. The performance of the conventional and variable step algorithms P&O techniques is compared. Three-phase grid-tie inverter (GTI) is used to connect the system to the utility grid. MATLAB/SIMULINK software is used to study the validity of the modified technique. The results demonstrate that the VSPO algorithm attains the MPP faster than the conventional techniques and at reduced oscillation rate.

A new class of efficient one-step contractivity preserving high-order time discretization methods of order 5 to 14

A family of one-step, explicit, contractivity preserving, multi-stage, multi-derivative, Hermite–Birkhoff–Taylor methods of order p = 5,6,…,14, that we denote by CPHBTRK4(d,s,p), with nonnegative coefficients are constructed by casting s-stage Runge–Kutta methods of order 4 with Taylor methods of order d. The constructed CPHBTRK4 methods are implemented using efficient variable step control and are compared to other well-known methods on a variety of initial value problems. A selected method: CP 6-stages 9-derivative HBT method of order 12, denoted by CPHBTRK412, has larger region of absolute stability than Dormand–Prince DP(8,7)13M and Taylor method T(12) of order 12. It is superior to DP(8,7)13M and T(12) methods on the basis the number of steps, CPU time, and maximum global error on several problems often used to test higher-order ODE solvers. Also, we show that the contractivity preserving property of CPHBTRK412is very efficient in suppressing the effect of the propagation of discretization errors and the new method compares positively with explicit 17 stages Runge-Kutta-Nystrom pair of order 12 by Sharp et al. on a long-term integration of a standard N-body problem. The selected CPHBTRK412is listed in the Appendix.

Kinetic Monte Carlo simulations of surface reactions on supported nanoparticles: A novel approach and computer code.

So far most kinetic Monte Carlo (kMC) simulations of heterogeneously catalyzed gas phase reactions were limited to flat crystal surfaces. The newly developed program MoCKA (Monte Carlo Karlsruhe) combines graph-theoretical and lattice-based principles to be able to efficiently handle multiple lattices with a large number of sites, which account for different facets of the catalytic nanoparticle and the support material, and pursues a general approach, which is not restricted to a specific surface or reaction. The implementation uses the efficient variable step size method and applies a fast update algorithm for its process list. It is shown that the analysis of communication between facets and of (reverse) spillover effects is possible by rewinding the kMC simulation. Hence, this approach offers a wide range of new applications for kMC simulations in heterogeneous catalysis.

Efficient Variable Step Size Approximations for Strong Solutions of Stochastic Differential Equations with Additive Noise and Time Singularity

We consider stochastic differential equations with additive noise and conditions on the coefficients in those equations that allow a time singularity in the drift coefficient. Given a maximum step size, h*, we specify variable (adaptive) step sizes relative to h* which decrease as the time node points approach the singularity. We use an Euler-type numerical scheme to produce an approximate solution and estimate the error in the approximation. When the solution is restricted to a fixed closed time interval excluding the singularity, we obtain a global pointwise error of order Oh*. An order of error Oh*p for any p<1 is obtained when the approximation is run up to a time within h*q of the singularity for an appropriate choice of exponent q. We apply this scheme to Brownian bridge, which is defined as the nonanticipating solution of a stochastic differential equation of the type under consideration. In this special case, we show that the global pointwise error is of order Oh*, independent of how close to the singularity the approximation is considered.

Power System Stability Computer Simulation Using a Differential-Algebraic Equation Solver

The preset work tested a freely domain software for solving index zero and one systems of differential-algebraic equations, named as DASSL. The code encompasses an efficient variable step size and variable order based on BDF methods to solve a system of DAEs or ODEs. The code was applied in power systems time domain studies, i.e., synchronous machine angular transient stability and long-term voltage stability, using the Brazilian South-Southeast Equivalent Power System. Using this real power system model including fast and slow response control devices, it was possible to investigate the code capability in simulating different stability phenomena in the same run. The variable step size and variable order algorithm implemented in DASSL results in a very powerful tool for power system time domain computer simulation.