This paper presents a real-coded genetic algorithm (RCGA) with new genetic operations (crossover and mutation). They are called the average-bound crossover and wavelet mutation. By introducing the proposed genetic ope...
详细信息
This paper presents a real-coded genetic algorithm (RCGA) with new genetic operations (crossover and mutation). They are called the average-bound crossover and wavelet mutation. By introducing the proposed genetic operations, both the solution quality and stability are better than the RCGA with conventional genetic operations. A suite of benchmark test functions are used to evaluate the performance of the proposed algorithm. Application examples on economic load dispatch and tuning an associative-memory neural network are used to show the performance of the proposed RCGA.
The main objective of this study is to reduce the eccentric load's influence on the dynamic characteristics of a horizontally installed rotary actuator. The solution is drilling a hole into the rotary shaft of a r...
详细信息
The main objective of this study is to reduce the eccentric load's influence on the dynamic characteristics of a horizontally installed rotary actuator. The solution is drilling a hole into the rotary shaft of a rotary cylinder. With the rotation of the rotary actuator the hole will open and connect the two working chambers within a certain angular range, the back pressure will increase and the torque introduced by the back pressure partly compensates for the torque of the eccentric load. The design procedure for the connecting hole is as follows: First, experiments that study the effect of eccentric loads on the dynamic characteristics of a rotary actuator were carried out, and a stability index a(v) was proposed;Second, a mathematical model including the connecting hole was built;Third, a real-coded GA optimization design for the connecting hole whose object is to minimize av was conducted. Simulations and test results show that the method worked efficiently.
This paper presents a technique for designing a model-based fuzzy controller for a class of nonlinear systems. A Takagi-Sugeno fuzzy model, described by IF-THEN rules which locally represent linear input-output relati...
详细信息
ISBN:
(纸本)9788995003879
This paper presents a technique for designing a model-based fuzzy controller for a class of nonlinear systems. A Takagi-Sugeno fuzzy model, described by IF-THEN rules which locally represent linear input-output relations of a nonlinear system, is obtained and both the membership functions and model parameters in the consequents are simultaneously adjusted using a real-coded genetic algorithm(RCGA). Then model-based local controllers are designed by another RCGA such that the given performance index is minimized. The overall fuzzy controller is derived through a fuzzy blending of the local controllers. The design methodology is illustrated by an application to the stabilization problem of an inverted pendulum on a cart.
Particle Swarm Optimization (PSO) is a stochastic and population-based search algorithm that demonstrates its effctiveness in solving complex nonlinear optimization problems. Although the original PSO is very simple a...
详细信息
ISBN:
(纸本)9789889867140
Particle Swarm Optimization (PSO) is a stochastic and population-based search algorithm that demonstrates its effctiveness in solving complex nonlinear optimization problems. Although the original PSO is very simple and effective, how to determine appropriate values of parameters in PSO is yet to be found. This paper proposes a novel method called evolutionary PSO, which estimates values of parameters in PSO for effectively finding globally optimal parameter values by a real-codedgenetic a gorithm. A crucial idea here is to adopt a temporary cumulative fitness instead of instantaneous fitness in a realcodedgeneticalgorithm for evaluating the performance of the PSO. It provides a useful measure that efficiently determines appropriate values of parameters in PSO. To demonstrate the effectiveness of the proposed method, we implement a simple computer experiment on a 2-dimensional optimization problem, and analyze the characteristics of dependency on initial condition.
The inverse kinematics solution of an industrial robot may provide multiple robot configurations that all achieve the required goal position of the manipulator. In the absence of obstacles, multiplicity resolution can...
详细信息
The inverse kinematics solution of an industrial robot may provide multiple robot configurations that all achieve the required goal position of the manipulator. In the absence of obstacles, multiplicity resolution can be achieved by selecting the robot configuration closest to the current robot configuration in the joint space. An evolutionary approach based on a real-coded genetic algorithm is used to obtain the solution of the multimodal inverse kinematics problem of industrial robots. All the multiple configurations obtained by this approach can be displayed using a 3D modeler developed in MAT-LAB for the purpose of visualization. The multiple configurations are then compared on the basis of their closeness in joint space to the current robot configuration. Simulation experiments are carried out on a SCARA robot and a PUMA robot to illustrate the efficacy of the approach. (C) 2005 Elsevier Ltd. All rights reserved.
This paper proposes an improved geneticalgorithm (GA) with multiple crossovers to estimate the system coefficients for the infinite impulse response (IIR) digital filter. In the traditional crossover operation, it ne...
详细信息
This paper proposes an improved geneticalgorithm (GA) with multiple crossovers to estimate the system coefficients for the infinite impulse response (IIR) digital filter. In the traditional crossover operation, it needs two parent chromosomes to achieve the crossover work, whereas in this paper the proposed algorithm selects three chromosomes for crossover in order to generate more promising offspring toward the problem solution. Each of unknown IIR coefficients is called a gene and the collection of genes forms a chromosome. A population of chromosomes is evolved by the genetic operations of reproduction, multiple crossover, and mutation. Finally, two illustrative examples including the band pass and band stop IIR filters are demonstrated to verify the proposed method. (c) 2006 Elsevier Ltd. All rights reserved.
We propose a methodology to optimize the natural frequencies of functionally graded structures by tailoring their material distribution. The element-free Galerkin method is used to analyze the two-dimensional steady-s...
详细信息
We propose a methodology to optimize the natural frequencies of functionally graded structures by tailoring their material distribution. The element-free Galerkin method is used to analyze the two-dimensional steady-state free and forced vibration of functionally graded beams. To optimize the material composition, the spatial distribution of volume fractions of the material constituents is defined using piecewise bicubic interpolation of volume fraction values that are specified at a finite number of grid points. Subsequently, we use a real-coded genetic algorithm to optimize the volume fraction distribution for three model problems. In the first problem, we seek material distributions that maximize each of the first three natural frequencies of a functionally graded beam. The goal of the second model problem is to minimize the mass of a functionally graded beam while constraining its natural frequencies to lie outside certain prescribed frequency bands. The last problem aims to minimize the mass of a functionally graded beam by simultaneously optimizing its thickness and material distribution such that the fundamental frequency is greater than a prescribed value.
In the automotive industry, engine test engineers are required to deal with a huge quantity of experimental data obtained from engine test beds each day. Those data must be analysed to evaluate engine performance and ...
详细信息
In the automotive industry, engine test engineers are required to deal with a huge quantity of experimental data obtained from engine test beds each day. Those data must be analysed to evaluate engine performance and to guide further engine test operations. In order to improve efficiency and reduce expenditure of time in engine testing, it is very important for engine test bed controllers to develop a mathematical model from existing engine test data. This paper presents an investigation of a neural network-geneticalgorithm (GA) combined tool for engine modelling. In the modelling tool, a real-coded GA has been employed to train three different groups of neural networks (a multilayer perceptron group, a radial basis function group, and a bar function networks group) and then finally to find the most suitable neural network model for engine modelling. The experimental results given in this paper show that the proposed tool has been successfully used for Rover engine testing.
genetic Network Programming (GNP) having a directed graph structure has been proposed as a new method of evolutionary computation. Recently, GNP has been applied to elevator group supervisory control system (EGSCS), a...
详细信息
genetic Network Programming (GNP) having a directed graph structure has been proposed as a new method of evolutionary computation. Recently, GNP has been applied to elevator group supervisory control system (EGSCS), a real-world problem, to demonstrate its applicability and effectiveness. Its previous study considers the known and fixed traffic flow, however, it is changed dynamically with time in real elevator systems. Therefore, an EGSCS with dynamic adaptive control considering such changes should be studied for practical applications. In this paper, we have applied GNP with functional localization to an EGSCS to construct such an adaptive system. In our proposal, the switching GNP can switch the functionally localized GNPs (assigning GNPs) based on the special traffic. Simulation confirmed the adaptability and effectiveness of our proposal in daily office-building traffic.
A study on improving the performance of the real-coded genetic algorithm for electromagnetic inverse scattering of two-dimensional perfectly conducting cylinders is presented. Three schemes, namely, the penalty functi...
详细信息
A study on improving the performance of the real-coded genetic algorithm for electromagnetic inverse scattering of two-dimensional perfectly conducting cylinders is presented. Three schemes, namely, the penalty function approach, the closed cubic B-splines local shape function approach and the adaptive hybrid algorithm approach are proposed to deal with the problem. These schemes can be used separately or be combined to improve the performance. Numerical examples validate the schemes.
暂无评论