Dynamic Parameter Selection Research Articles

Differential Evolution With Dynamic Parameters Selection for Optimization Problems

Over the last few decades, a number of differential evolution (DE) algorithms have been proposed with excellent performance on mathematical benchmarks. However, like any other optimization algorithm, the success of DE is highly dependent on the search operators and control parameters that are often decided a priori. The selection of the parameter values is itself a combinatorial optimization problem. Although a considerable number of investigations have been conducted with regards to parameter selection, it is known to be a tedious task. In this paper, a DE algorithm is proposed that uses a new mechanism to dynamically select the best performing combinations of parameters (amplification factor, crossover rate, and the population size) for a problem during the course of a single run. The performance of the algorithm is judged by solving three well known sets of optimization test problems (two constrained and one unconstrained). The results demonstrate that the proposed algorithm not only saves the computational time, but also shows better performance over the state-of-the-art algorithms. The proposed mechanism can easily be applied to other population-based algorithms.

New Family of Microgrid Control and Management Strategies in Smart Distribution Grids—Analysis, Comparison and Testing

This paper presents a new family of universal control and management strategies for microgrids in smart distribution grids. The paper also provides a general and computationally-efficient framework for modeling and analysis of power management strategies in a microgrid with multiple-distributed generation (DG) units which eases microgrid dynamic studies and controller parameters selection in large microgrids with multiple DG units. Three different approaches for real and reactive power management are proposed. The controllers offer the following advantages: 1) the proposed topologies can be applied to both voltage-controlled (VC) and current controlled (CC) voltage source converters (VSCs). 2) The controllers are universal and realize requirements of both grid-connected and islanded modes, i.e., they share real and reactive power during islanding with constant frequency operation and act as grid supporting VSCs in the grid connected mode. 3) The drooping variables can be either power or current, thus VC-power drooping, VC-current drooping and CC-power drooping are different available variants. 4) The concept of hybrid polar-vector control is developed in this paper. Thus, it can combine the benefits of both types of controllers in one augmented strategy. 5) The controller emulates the behavior of conventional synchronous generators (SGs) which in turn results in better integration of electronically-interfaced DG units into the power system and prevents instabilities due to interaction of fast response DGs and SGs. 6) The controllers realize seamless and robust transition to the islanding mode. The controllers are developed under new concept of synchronous converters. A theoretical analysis and simulation results show that the proposed controllers yield the aforementioned requirements in one compact structure.

Parameter Selection for a Centralized Thermostatically Controlled Appliances Load Controller Used for Intra-Hour Load Balancing

This paper presents a novel dynamic parameter selection process to optimize the performance of a centralized load controller designed to provide intra-hour load balancing services using thermostatically controlled appliances (TCAs). An optimal set of control parameters for the controller are selected by exhaustive simulations of control variables such as the sampling time of the forecaster, the magnitude of the load balancing signal, and the temperature deadband. The effects of TCA lock-off times, ambient temperatures, heat gains, and two-way communication delays on the controller design are also modeled. Customer comfort, device life cycles, and control errors are used as metrics to evaluate the performance. The results demonstrate that the optimized controller offers satisfactory performance considering all the operational uncertainties.

Power Train Design and Performance Simulation for Pure Electric Vehicle

Based on a popular sedan,a pure electric vehicle was designed.The determination of dynamic parameters and the selection of power devices were according to the design target.The dynamic performance of the vehicle was built and simulated by using the simulation software of ADVISOR.The simulation result demonstrated that the selection of dynamic parameters were feasible.The pure electric vehicle could run with good performance and the design target was achieved.

Automatic Fuzzy Parameter Selection in Dynamic Fuzzy Voter for Safety Critical Systems

The main objective of this research paper is designing automatic fuzzy parameter selection based dynamic fuzzy voter for safety critical systems with limited system knowledge. Existing fuzzy voters for controlling safety critical systems and sensor fusion are surveyed and safety performance is empirically evaluated. The major limitation identified in the existing fuzzy voters is the static fuzzy parameter selection. Optimally selected static fuzzy parameters work only for a particular set of data with the known data ranges. In this paper, a dynamic or automatic fuzzy parameter selection method for fuzzy voters is proposed based on the statistical parameters of the local set of data in each voting cycle. Safety performance is empirically evaluated by running the static and dynamic fuzzy voters on a simulated triple modular redundant (TMR) system for 10000 voting cycles. Experimental results show that proposed Dynamic fuzzy voter is giving almost 100% safety if two of the three modules of the TMR System are error free. Dynamic voter is designed in such a way that it can be plugged in and used in any safety critical system without having any knowledge regarding the data produced and their ranges.

Selection of regularization parameters using an atmospheric retrievable index in a retrieval of atmospheric profile

Using an atmospheric retrievable index and The Nelder-Mead simplex method, a dynamic regularization parameter selection method for the retrieval of atmospheric profile with remote sensing data. And a series of test is carried out with four typical regional profiles. The results show that the ranges of the optimal regularization parameter for different profiles are small. And to improve computational efficiency in the actual retrieval process, the regularization parameter can be approximately taken as a constant. The results provide a valuable method of selecting the regularization parameters in the retrieval of atmospheric profiles using the remote sensing data.

Kinematic Analysis on Materials on Counter Flow Screen and Selection of Dynamic Parameters of Machine

The paper presents the structural characteristics of counter flow screen. Pieces of plastic film and sandstones with different friction factors and elasticity coefficients are chosen as the research objects. The motion state and the sorting mechanism of materials in the sorting process are studied. According to the motion analysis on pieces of plastic film and sandstones on counter flow screen, it can be concluded that the materials with different friction factors and elasticity coefficients can all be sorted by counter flow screen. The more difference they have in friction factors and elasticity coefficients, the better sorting performance can be achieved. The selection and computation on the dynamical parameters of counter flow screen is carried out, which provides the theory evidence for the design of new friction sorting equipment and opens up new prospects for the application of counter flow screen.

Adaptive parameter control of evolutionary algorithms to improve quality-time trade-off

Parameter control of evolutionary algorithms (EAs) poses special challenges as EA uses a population and requires many parameters to be controlled for an effective search. Quality improvement is dependent on several factors, such as, fitness estimation, population diversity and convergence rate. A widely practiced approach to identify a good set of parameters for a particular class of problem is through experimentation. Ideally, the parameter selection should depend on the resource availability, and thus, a rigid choice may not be suitable. In this work, we propose an automated framework for parameter selection, which can adapt according to the constraints specified. To condition the parameter choice through resource constraint/utilization, we consider two typical scenarios, one where maximum available run-time is pre-specified and the other in which a utility function modeling the quality-time trade-off is used instead of a rigid deadline. We present static and dynamic parameter selection strategies based on a probabilistic profiling method. Experiments performed with traveling salesman problem (TSP) and standard cell placement problem show that an informed adaptive parameter control mechanism can yield better results than a static selection.

Detecting Wide Lines Using Isotropic Nonlinear Filtering

Lines provide important information in images, and line detection is crucial in many applications. However, most of the existing algorithms focus only on the extraction of line positions, ignoring line thickness. This paper presents a novel wide line detector using an isotropic nonlinear filter. Unlike most existing edge and line detectors which use directional derivatives, our proposed wide line detector applies a nonlinear filter to extract a line completely without any derivative. The detector is based on the isotropic responses via circular masks. A general scheme for the analysis of the robustness of the proposed wide line detector is introduced and the dynamic selection of parameters is developed. In addition, this paper investigates the relationship between the size of circular masks and the width of detected lines. A sequence of tests has been conducted on a variety of image samples and our experimental results demonstrate the feasibility and effectiveness of the proposed method.

Analysis of dynamic error and selection of parameters of a measuring transducer based on step, linear, and parabolic signals

Analysis of dynamic error and selection of parameters of a measuring transducer based on step, linear, and parabolic signals

Response of double-wall composite shells to random point loads

This paper presents an analytical study of double-wall-laminated fiber-reinforced cylindrical shell response to random loads. A soft viscoelastic core with dilatational modes included is used. The theory of laminated shells is simplified by assumptions similar to those in the Donnell-Mushtari development for isotropic shells. Modal solutions of simply supported shells are obtained. Modal frequencies and deflection response spectral densities are determined. It is found that this approach allows for easy parametric evaluation and that by proper selection of dynamic parameters, viscoelastic core characteristics, and fiber reinforcement orientation, vibration response can be reduced.

An Approach to Expert Control of Interactive Software Systems

Expert problem-solving strategies in many domains require the use of detailed mathematical techniques coupled with experiential knowledge about how and when to use the appropriate techniques. In many of these domains, such techniques are made available to experts in large software packages. In attempting to build expert systems for these domains, we wish to make use of these packages, and are therefore faced with an important problem: how to integrate the existing software, and knowledge about its use, into a practical expert system. The expert knowledge is used, in dynamic selection and interpretation of appropriate programs and parameters, to reach a successful goal in the problem solving. We describe the framework of a hybrid expert system for representing problem-solving knowledge in these domains. This hybrid system may be characterized as consisting of a production system and mathematical methods. The software package is reorganized as necessary to map it into the mathematical-method representation of a hybrid system. This approach has evolved out of an effort to build an expert system for performing well-log analysis, ELAS (expert log analysis system).

Dynamic Analysis and Optimal Selection of Parameters of a Finite Element Modeled Lathe Spindle Under Random Cutting Forces

The dynamic analysis of an elastically supported lathe spindle-workpiece system subjected to random cutting forces is presented. The stochastic partial differential equation characterizing the behavior of the system was formulated from the Euler-Bernouli equation. Based on free vibration analysis and experimental verification of the natural frequencies, the hinged boundary condition was considered for the running center. A finite element technique in conjunction with the modal analysis method were used to calculate the mean square displacement of the workpiece. The experimentally calculated power spectral density of the cutting forces was used as the input excitation to the mathematical model. The effect of bearing stiffness and damping, and bearing spacing on the mean square displacement were studied. A direct search optimization technique was carried out to select optimal bearing stiffness and the bearing spacing. Results are presented in the form of plots and tables.