Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 335

Search results for: Differential Evolution

335 Training Radial Basis Function Networks with Differential Evolution

Authors: Bing Yu , Xingshi He

Abstract:

In this paper, Differential Evolution (DE) algorithm, a new promising evolutionary algorithm, is proposed to train Radial Basis Function (RBF) network related to automatic configuration of network architecture. Classification tasks on data sets: Iris, Wine, New-thyroid, and Glass are conducted to measure the performance of neural networks. Compared with a standard RBF training algorithm in Matlab neural network toolbox, DE achieves more rational architecture for RBF networks. The resulting networks hence obtain strong generalization abilities.

Keywords: differential evolution, neural network, Rbf function

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
334 Comparison of Two Interval Models for Interval-Valued Differential Evolution

Authors: Hidehiko Okada

Abstract:

The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks. 

Keywords: Evolutionary algorithms, differential evolution, neural network, neuroevolution, interval arithmetic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
333 Supremacy of Differential Evolution Algorithm in Designing Multiplier-Less Low-Pass FIR Filter

Authors: Abhijit Chandra, Sudipta Chattopadhyay

Abstract:

In this communication, we have made an attempt to design multiplier-less low-pass finite impulse response (FIR) filter with the aid of various mutation strategies of Differential Evolution (DE) algorithm. Impulse response coefficient of the designed FIR filter has been represented as sums or differences of powers of two. Performance of the proposed filter has been evaluated in terms of its frequency response and associated hardware cost. Supremacy of our approach has been substantiated by comparing our result with many of the existing multiplier-less filter design algorithms of recent interest. It has also been demonstrated that DE-optimized filter outperforms Genetic Algorithm (GA) based design by a large margin.  Hardware efficiency of our algorithm has further been validated by implementing those filters on a Field Programmable Gate Array (FPGA) chip.

Keywords: Convergence speed, Differential Evolution (DE), error histogram, finite impulse response (FIR) filter, total power of two (TPT), zero-valued filter coefficient (ZFC).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
332 Load Frequency Control of Nonlinear Interconnected Hydro-Thermal System Using Differential Evolution Technique

Authors: Banaja Mohanty, Prakash Kumar Hota

Abstract:

This paper presents a differential evolution algorithm to design a robust PI and PID controllers for Load Frequency Control (LFC) of nonlinear interconnected power systems considering the boiler dynamics, Governor Dead Band (GDB), Generation Rate Constraint (GRC). Differential evolution algorithm is employed to search for the optimal controller parameters. The proposed method easily copes of with nonlinear constraints. Further the proposed controller is simple, effective and can ensure the desirable overall system performance. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic controller for the same power systems. The comparison is done using various performance measures like overshoot, settling time and standard error criteria of frequency and tie-line power deviation following a 1% step load perturbation in hydro area. It is noticed that, the dynamic performance of proposed controller is better than fuzzy logic controller. Furthermore, it is also seen that the proposed system is robust and is not affected by change in the system parameters.

Keywords: Automatic Generation control (AGC), Generation Rate Constraint (GRC), Governor Dead Band (GDB), Differential Evolution (DE)

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
331 A Combined Conventional and Differential Evolution Method for Model Order Reduction

Authors: J. S. Yadav, N. P. Patidar, J. Singhai, S. Panda, C. Ardil

Abstract:

In this paper a mixed method by combining an evolutionary and a conventional technique is proposed for reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM). In the conventional technique, the mixed advantages of Mihailov stability criterion and continued Fraction Expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. Then, retaining the numerator polynomial, the denominator polynomial is recalculated by an evolutionary technique. In the evolutionary method, the recently proposed Differential Evolution (DE) optimization technique is employed. DE method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. The proposed method is illustrated through a numerical example and compared with ROM where both numerator and denominator polynomials are obtained by conventional method to show its superiority.

Keywords: Reduced Order Modeling, Stability, Mihailov Stability Criterion, Continued Fraction Expansions, Differential Evolution, Integral Squared Error.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
330 Reentry Trajectory Optimization Based on Differential Evolution

Authors: Songtao Chang, Yongji Wang, Lei Liu, Dangjun Zhao

Abstract:

Reentry trajectory optimization is a multi-constraints optimal control problem which is hard to solve. To tackle it, we proposed a new algorithm named CDEN(Constrained Differential Evolution Newton-Raphson Algorithm) based on Differential Evolution( DE) and Newton-Raphson.We transform the infinite dimensional optimal control problem to parameter optimization which is finite dimensional by discretize control parameter. In order to simplify the problem, we figure out the control parameter-s scope by process constraints. To handle constraints, we proposed a parameterless constraints handle process. Through comprehensive analyze the problem, we use a new algorithm integrated by DE and Newton-Raphson to solve it. It is validated by a reentry vehicle X-33, simulation results indicated that the algorithm is effective and robust.

Keywords: reentry vehicle, trajectory optimization, constraint optimal, differential evolution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
329 Solving the Economic Dispatch Problem by Using Differential Evolution

Authors: S. Khamsawang, S. Jiriwibhakorn

Abstract:

This paper proposes an application of the differential evolution (DE) algorithm for solving the economic dispatch problem (ED). Furthermore, the regenerating population procedure added to the conventional DE in order to improve escaping the local minimum solution. To test performance of DE algorithm, three thermal generating units with valve-point loading effects is used for testing. Moreover, investigating the DE parameters is presented. The simulation results show that the DE algorithm, which had been adjusted parameters, is better convergent time than other optimization methods.

Keywords: Differential evolution, Economic dispatch problem, Valve-point loading effect, Optimization method.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
328 Fractional Delay FIR Filters Design with Enhanced Differential Evolution

Authors: Krzysztof Walczak

Abstract:

Fractional delay FIR filters design method based on the differential evolution algorithm is presented. Differential evolution is an evolutionary algorithm for solving a global optimization problems in the continuous search space. In the proposed approach, an evolutionary algorithm is used to determine the coefficients of a fractional delay FIR filter based on the Farrow structure. Basic differential evolution is enhanced with a restricted mating technique, which improves the algorithm performance in terms of convergence speed and obtained solution. Evolutionary optimization is carried out by minimizing an objective function which is based on the amplitude response and phase delay errors. Experimental results show that the proposed algorithm leads to a reduction in the amplitude response and phase delay errors relative to those achieved with the Least-Squares method.

Keywords: Fractional Delay Filters, Farrow Structure, Evolutionary Computation, Differential Evolution

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
327 Controller Design of Discrete Systems by Order Reduction Technique Employing Differential Evolution Optimization Algorithm

Authors: J. S. Yadav, N. P. Patidar, J. Singhai

Abstract:

One of the main objectives of order reduction is to design a controller of lower order which can effectively control the original high order system so that the overall system is of lower order and easy to understand. In this paper, a simple method is presented for controller design of a higher order discrete system. First the original higher order discrete system in reduced to a lower order model. Then a Proportional Integral Derivative (PID) controller is designed for lower order model. An error minimization technique is employed for both order reduction and controller design. For the error minimization purpose, Differential Evolution (DE) optimization algorithm has been employed. DE method is based on the minimization of the Integral Squared Error (ISE) between the desired response and actual response pertaining to a unit step input. Finally the designed PID controller is connected to the original higher order discrete system to get the desired specification. The validity of the proposed method is illustrated through a numerical example.

Keywords: Discrete System, Model Order Reduction, PIDController, Integral Squared Error, Differential Evolution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
326 Differential Evolution Based Optimal Choice and Location of Facts Devices in Restructured Power System

Authors: K. Balamurugan, V. Dharmalingam, R. Muralisachithanandam, R. Sankaran

Abstract:

This paper deals with the optimal choice and location of FACTS devices in deregulated power systems using Differential Evolution algorithm. The main objective of this paper is to achieve the power system economic generation allocation and dispatch in deregulated electricity market. Using the proposed method, the locations of the FACTS devices, their types and ratings are optimized simultaneously. Different kinds of FACTS devices such as TCSC and SVC are simulated in this study. Furthermore, their investment costs are also considered. Simulation results validate the capability of this new approach in minimizing the overall system cost function, which includes the investment costs of the FACTS devices and the bid offers of the market participants. The proposed algorithm is an effective and practical method for the choice and location of suitable FACTS devices in deregulated electricity market.

Keywords: FACTS Devices, Deregulated Electricity Market, Optimal Location, Differential Evolution, Mat Lab.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
325 Active Vibration Control of Flexible Beam using Differential Evolution Optimisation

Authors: Mohd Sazli Saad, Hishamuddin Jamaluddin, Intan Zaurah Mat Darus

Abstract:

This paper presents the development of an active vibration control using direct adaptive controller to suppress the vibration of a flexible beam system. The controller is realized based on linear parametric form. Differential evolution optimisation algorithm is used to optimize the controller using single objective function by minimizing the mean square error of the observed vibration signal. Furthermore, an alternative approach is developed to systematically search for the best controller model structure together with it parameter values. The performance of the control scheme is presented and analysed in both time and frequency domain. Simulation results demonstrate that the proposed scheme is able to suppress the unwanted vibration effectively.

Keywords: flexible beam, finite difference method, active vibration control, differential evolution, direct adaptive controller

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
324 Power System Stability Improvement by Simultaneous Tuning of PSS and SVC Based Damping Controllers Employing Differential Evolution Algorithm

Authors: Sangram Keshori Mohapatra, Sidhartha Panda, Prasant Kumar Satpathy

Abstract:

Power-system stability improvement by simultaneous tuning of power system stabilizer (PSS) and a Static Var Compensator (SVC) based damping controller is thoroughly investigated in this paper. Both local and remote signals with associated time delays are considered in the present study. The design problem of the proposed controller is formulated as an optimization problem, and differential evolution (DE) algorithm is employed to search for the optimal controller parameters. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite bus power system and multi-machine power system. The performance of the proposed controllers with variations in the signal transmission delays has also been investigated. The proposed stabilizers are tested on a weakly connected power system subjected to different disturbances. Nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance conditions.

Keywords: Differential Evolution Algorithm, Power System Stability, Power System Stabilizer, Static Var Compensator

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
323 Design Optimization of Doubly Fed Induction Generator Performance by Differential Evolution

Authors: Mamidi Ramakrishna Rao

Abstract:

Doubly-fed induction generators (DFIG) due to their advantages like speed variation and four-quadrant operation, find its application in wind turbines. DFIG besides supplying power to the grid has to support reactive power (kvar) under grid voltage variations, should contribute minimum fault current during faults, have high efficiency, minimum weight, adequate rotor protection during crow-bar-operation from +20% to -20% of rated speed.  To achieve the optimum performance, a good electromagnetic design of DFIG is required. In this paper, a simple and heuristic global optimization – Differential Evolution has been used. Variables considered are lamination details such as slot dimensions, stack diameters, air gap length, and generator stator and rotor stack length. Two operating conditions have been considered - voltage and speed variations. Constraints included were reactive power supplied to the grid and limiting fault current and torque. The optimization has been executed separately for three objective functions - maximum efficiency, weight reduction, and grid fault stator currents. Subsequent calculations led to the conclusion that designs determined through differential evolution help in determining an optimum electrical design for each objective function.

Keywords: Design optimization, performance, doubly fed induction generators, DFIG, differential evolution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
322 A Cuckoo Search with Differential Evolution for Clustering Microarray Gene Expression Data

Authors: M. Pandi, K. Premalatha

Abstract:

A DNA microarray technology is a collection of microscopic DNA spots attached to a solid surface. Scientists use DNA microarrays to measure the expression levels of large numbers of genes simultaneously or to genotype multiple regions of a genome. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. It is handled by clustering which reveals the natural structures and identifying the interesting patterns in the underlying data. In this paper, gene based clustering in gene expression data is proposed using Cuckoo Search with Differential Evolution (CS-DE). The experiment results are analyzed with gene expression benchmark datasets. The results show that CS-DE outperforms CS in benchmark datasets. To find the validation of the clustering results, this work is tested with one internal and one external cluster validation indexes.

Keywords: DNA, Microarray, genomics, Cuckoo Search, Differential Evolution, Gene expression data, Clustering.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
321 Self-Adaptive Differential Evolution Based Power Economic Dispatch of Generators with Valve-Point Effects and Multiple Fuel Options

Authors: R.Balamurugan, S.Subramanian

Abstract:

This paper presents the solution of power economic dispatch (PED) problem of generating units with valve point effects and multiple fuel options using Self-Adaptive Differential Evolution (SDE) algorithm. The global optimal solution by mathematical approaches becomes difficult for the realistic PED problem in power systems. The Differential Evolution (DE) algorithm is found to be a powerful evolutionary algorithm for global optimization in many real problems. In this paper the key parameters of control in DE algorithm such as the crossover constant CR and weight applied to random differential F are self-adapted. The PED problem formulation takes into consideration of nonsmooth fuel cost function due to valve point effects and multi fuel options of generator. The proposed approach has been examined and tested with the numerical results of PED problems with thirteen-generation units including valve-point effects, ten-generation units with multiple fuel options neglecting valve-point effects and ten-generation units including valve-point effects and multiple fuel options. The test results are promising and show the effectiveness of proposed approach for solving PED problems.

Keywords: Multiple fuels, power economic dispatch, selfadaptivedifferential evolution and valve-point effects.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
320 EML-Estimation of Multivariate t Copulas with Heuristic Optimization

Authors: Jin Zhang, Wing Lon Ng

Abstract:

In recent years, copulas have become very popular in financial research and actuarial science as they are more flexible in modelling the co-movements and relationships of risk factors as compared to the conventional linear correlation coefficient by Pearson. However, a precise estimation of the copula parameters is vital in order to correctly capture the (possibly nonlinear) dependence structure and joint tail events. In this study, we employ two optimization heuristics, namely Differential Evolution and Threshold Accepting to tackle the parameter estimation of multivariate t distribution models in the EML approach. Since the evolutionary optimizer does not rely on gradient search, the EML approach can be applied to estimation of more complicated copula models such as high-dimensional copulas. Our experimental study shows that the proposed method provides more robust and more accurate estimates as compared to the IFM approach.

Keywords: Copula Models, Student t Copula, Parameter Inference, Differential Evolution, Threshold Accepting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
319 No one Set of Parameter Values Can Simulate the Epidemics Due to SARS Occurring at Different Localities

Authors: Weerachi Sarakorn, I-Ming Tang

Abstract:

A mathematical model for the transmission of SARS is developed. In addition to dividing the population into susceptible (high and low risk), exposed, infected, quarantined, diagnosed and recovered classes, we have included a class called untraced. The model simulates the Gompertz curves which are the best representation of the cumulative numbers of probable SARS cases in Hong Kong and Singapore. The values of the parameters in the model which produces the best fit of the observed data for each city are obtained by using a differential evolution algorithm. It is seen that the values for the parameters needed to simulate the observed daily behaviors of the two epidemics are different.

Keywords: SARS, mathematical modelling, differential evolution algorithm.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
318 Evolution of Fuzzy Neural Networks Using an Evolution Strategy with Fuzzy Genotype Values

Authors: Hidehiko Okada

Abstract:

Evolution strategy (ES) is a well-known instance of evolutionary algorithms, and there have been many studies on ES. In this paper, the author proposes an extended ES for solving fuzzy-valued optimization problems. In the proposed ES, genotype values are not real numbers but fuzzy numbers. Evolutionary processes in the ES are extended so that it can handle genotype instances with fuzzy numbers. In this study, the proposed method is experimentally applied to the evolution of neural networks with fuzzy weights and biases. Results reveal that fuzzy neural networks evolved using the proposed ES with fuzzy genotype values can model hidden target fuzzy functions even though no training data are explicitly provided. Next, the proposed method is evaluated in terms of variations in specifying fuzzy numbers as genotype values. One of the mostly adopted fuzzy numbers is a symmetric triangular one that can be specified by its lower and upper bounds (LU) or its center and width (CW). Experimental results revealed that the LU model contributed better to the fuzzy ES than the CW model, which indicates that the LU model should be adopted in future applications of the proposed method.

Keywords: Evolutionary algorithm, evolution strategy, fuzzy number, feedforward neural network, neuroevolution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
317 An Evolutionary Algorithm for Optimal Fuel-Type Configurations in Car Lines

Authors: Charalampos Saridakis, Stelios Tsafarakis

Abstract:

Although environmental concern is on the rise across Europe, current market data indicate that adoption rates of environmentally friendly vehicles remain extremely low. Against this background, the aim of this paper is to a) assess preferences of European consumers for clean-fuel cars and their characteristics and b) design car lines that optimize the combination of fuel types among models in the line-up. In this direction, the authors introduce a new evolutionary mechanism and implement it to stated-preference data derived from a large-scale choice-based conjoint experiment that measures consumer preferences for various factors affecting clean-fuel vehicle (CFV) adoption. The proposed two-step methodology provides interesting insights into how new and existing fuel-types can be combined in a car line that maximizes customer satisfaction.

Keywords: Clean-fuel vehicles, product line design, conjoint analysis, choice experiment, differential evolution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
316 Robust FACTS Controller Design Employing Modern Heuristic Optimization Techniques

Authors: A.K.Balirsingh, S.C.Swain, S. Panda

Abstract:

Recently, Genetic Algorithms (GA) and Differential Evolution (DE) algorithm technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of DE and GA optimization techniques, for flexible ac transmission system (FACTS)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques has been compared. Further, the optimized controllers are tested on a weekly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a FACTS-based controller, to enhance power system stability.

Keywords: Differential Evolution, Flexible AC TransmissionSystems (FACTS), Genetic Algorithm, Low Frequency Oscillations, Single-machine Infinite Bus Power System.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
315 DEMO Based Optimal Power Purchase Planning Under Electricity Price Uncertainty

Authors: Tulika Bhattacharjee, A. K.Chakraborty

Abstract:

Due to the deregulation of the Electric Supply Industry and the resulting emergence of electricity market, the volumes of power purchases are on the rise all over the world. In a bid to meet the customer-s demand in a reliable and yet economic manner, utilities purchase power from the energy market over and above its own production. This paper aims at developing an optimal power purchase model with two objectives viz economy and environment ,taking various functional operating constraints such as branch flow limits, load bus voltage magnitudes limits, unit capacity constraints and security constraints into consideration.The price of purchased power being an uncertain variable is modeled using fuzzy logic. DEMO (Differential Evolution For Multi-objective Optimization) is used to obtain the pareto-optimal solution set of the multi-objective problem formulated. Fuzzy set theory has been employed to extract the best compromise non-dominated solution. The results obtained on IEEE 30 bus system are presented and compared with that of NSGAII.

Keywords: Deregulation, Differential Evolution, Multi objective Optimization, Pareto Optimal Set, Optimal Power Flow

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
314 A Hybrid Metaheuristic Framework for Evolving the PROAFTN Classifier

Authors: Feras Al-Obeidat, Nabil Belacel, Juan A. Carretero, Prabhat Mahanti,

Abstract:

In this paper, a new learning algorithm based on a hybrid metaheuristic integrating Differential Evolution (DE) and Reduced Variable Neighborhood Search (RVNS) is introduced to train the classification method PROAFTN. To apply PROAFTN, values of several parameters need to be determined prior to classification. These parameters include boundaries of intervals and relative weights for each attribute. Based on these requirements, the hybrid approach, named DEPRO-RVNS, is presented in this study. In some cases, the major problem when applying DE to some classification problems was the premature convergence of some individuals to local optima. To eliminate this shortcoming and to improve the exploration and exploitation capabilities of DE, such individuals were set to iteratively re-explored using RVNS. Based on the generated results on both training and testing data, it is shown that the performance of PROAFTN is significantly improved. Furthermore, the experimental study shows that DEPRO-RVNS outperforms well-known machine learning classifiers in a variety of problems.

Keywords: Knowledge Discovery, Differential Evolution, Reduced Variable Neighborhood Search, Multiple criteria classification, PROAFTN, Supervised Learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
313 Frequency-Domain Design of Fractional-Order FIR Differentiators

Authors: Wei-Der Chang, Dai-Ming Chang, Eri-Wei Chiang, Chia-Hung Lin, Jian-Liung Chen

Abstract:

In this paper, a fractional-order FIR differentiator design method using the differential evolution (DE) algorithm is presented. In the proposed method, the FIR digital filter is designed to meet the frequency response of a desired fractal-order differentiator, which is evaluated in the frequency domain. To verify the design performance, another design method considered in the time-domain is also provided. Simulation results reveal the efficiency of the proposed method.

Keywords: Fractional-order differentiator, FIR digital filter, Differential evolution algorithm.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
312 Comparative Dynamic Performance of Load Frequency Control of Nonlinear Interconnected Hydro-Thermal System Using Intelligent Techniques

Authors: Banaja Mohanty, Prakash Kumar Hota

Abstract:

This paper demonstrates dynamic performance evaluation of load frequency control (LFC) with different intelligent techniques. All non-linearities and physical constraints have been considered in simulation studies such as governor dead band (GDB), generation rate constraint (GRC) and boiler dynamics. The conventional integral time absolute error has been considered as objective function. The design problem is formulated as an optimisation problem and particle swarm optimisation (PSO), bacterial foraging optimisation algorithm (BFOA) and differential evolution (DE) are employed to search optimal controller parameters. The superiority of the proposed approach has been shown by comparing the results with published fuzzy logic control (FLC) for the same interconnected power system. The comparison is done using various performance measures like overshoot, undershoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than FLC. Further, robustness analysis is carried out by varying the time constants of speed governor, turbine, tie-line power in the range of +40% to -40% to demonstrate the robustness of the proposed DE optimized PID controller.

Keywords: Automatic generation control, governor dead band, generation rate constraint, differential evolution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
311 DEA-Based Variable Structure Position Control of DC Servo Motor

Authors: Ladan Maijama’a, Jibril D. Jiya, Ejike C. Anene

Abstract:

This paper presents Differential Evolution Algorithm (DEA) based Variable Structure Position Control (VSPC) of Laboratory DC servomotor (LDCSM). DEA is employed for the optimal tuning of Variable Structure Control (VSC) parameters for position control of a DC servomotor. The VSC combines the techniques of Sliding Mode Control (SMC) that gives the advantages of small overshoot, improved step response characteristics, faster dynamic response and adaptability to plant parameter variations, suppressed influences of disturbances and uncertainties in system behavior. The results of the simulation responses of the VSC parameters adjustment by DEA were performed in Matlab Version 2010a platform and yield better dynamic performance compared with the untuned VSC designed.

Keywords: Differential evolution algorithm, laboratory DC servomotor, sliding mode control, variable structure control.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
310 Radial Basis Surrogate Model Integrated to Evolutionary Algorithm for Solving Computation Intensive Black-Box Problems

Authors: Abdulbaset Saad, Adel Younis, Zuomin Dong

Abstract:

For design optimization with high-dimensional expensive problems, an effective and efficient optimization methodology is desired. This work proposes a series of modification to the Differential Evolution (DE) algorithm for solving computation Intensive Black-Box Problems. The proposed methodology is called Radial Basis Meta-Model Algorithm Assisted Differential Evolutionary (RBF-DE), which is a global optimization algorithm based on the meta-modeling techniques. A meta-modeling assisted DE is proposed to solve computationally expensive optimization problems. The Radial Basis Function (RBF) model is used as a surrogate model to approximate the expensive objective function, while DE employs a mechanism to dynamically select the best performing combination of parameters such as differential rate, cross over probability, and population size. The proposed algorithm is tested on benchmark functions and real life practical applications and problems. The test results demonstrate that the proposed algorithm is promising and performs well compared to other optimization algorithms. The proposed algorithm is capable of converging to acceptable and good solutions in terms of accuracy, number of evaluations, and time needed to converge.

Keywords: Differential evolution, engineering design, expensive computations, meta-modeling, radial basis function, optimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
309 A Geometrical Perspective on the Insulin Evolution

Authors: Yuhei Kunihiro, Sorin V. Sabau, Kazuhiro Shibuya

Abstract:

We study the molecular evolution of insulin from metric geometry point of view. In mathematics, and in particular in geometry, distances and metrics between objects are of fundamental importance. Using a weaker notion than the classical distance, namely the weighted quasi-metrics, one can study the geometry of biological sequences (DNA, mRNA, or proteins) space. We analyze from geometrical point of view a family of 60 insulin homologous sequences ranging on a large variety of living organisms from human to the nematode C. elegans. We show that the distances between sequences provide important information about the evolution and function of insulin.

Keywords: Metric geometry, evolution, insulin.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
308 Trust and Reputation Mechanism with Path Optimization in Multipath Routing

Authors: Ramya Dorai, M. Rajaram

Abstract:

A Mobile Adhoc Network (MANET) is a collection of mobile nodes that communicate with each other with wireless links and without pre-existing communication infrastructure. Routing is an important issue which impacts network performance. As MANETs lack central administration and prior organization, their security concerns are different from those of conventional networks. Wireless links make MANETs susceptible to attacks. This study proposes a new trust mechanism to mitigate wormhole attack in MANETs. Different optimization techniques find available optimal path from source to destination. This study extends trust and reputation to an improved link quality and channel utilization based Adhoc Ondemand Multipath Distance Vector (AOMDV). Differential Evolution (DE) is used for optimization.

Keywords: Mobile Adhoc Network (MANET), Adhoc Ondemand Multi-Path Distance Vector (AOMDV), Trust and Reputation, Differential Evolution (DE), Link Quality, Channel Utilization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
307 Optimized Vector Quantization for Bayer Color Filter Array

Authors: M. Lakshmi, J. Senthil Kumar

Abstract:

Digital cameras to reduce cost, use an image sensor to capture color images. Color Filter Array (CFA) in digital cameras permits only one of the three primary (red-green-blue) colors to be sensed in a pixel and interpolates the two missing components through a method named demosaicking. Captured data is interpolated into a full color image and compressed in applications. Color interpolation before compression leads to data redundancy. This paper proposes a new Vector Quantization (VQ) technique to construct a VQ codebook with Differential Evolution (DE) Algorithm. The new technique is compared to conventional Linde- Buzo-Gray (LBG) method.

Keywords: Color Filter Array (CFA), Biorthogonal Wavelet, Vector Quantization (VQ), Differential Evolution (DE).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
306 Differential Sandwich Theorems with Generalised Derivative Operator

Authors: Maslina Darus, Khalifa Al-Shaqsi

Abstract:

In this paper, a generalized derivatives operator n λ,βf introduced by the authors will be discussed. Some subordination and superordination results involving this operator for certain normalized analytic functions in the open unit disk will be investigated. Our results extend corresponding previously known results.

Keywords: Analytic functions, Univalent functions, Derivative operator, Differential subordination, Differential superordination.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF