• Steel and Composite Structures
• /
• 제27권3호
• /
• pp.297-310
• /
• 2018

A simple and efficient numerical optimization approach for the lightweight optimal design of composite laminated beams is presented in this paper. The proposed procedure is a combination between the finite element method (FEM) and a global optimization algorithm developed recently, namely Jaya. In the present procedure, the advantages of FEM and Jaya are exploited, where FEM is used to analyze the behavior of beam, and Jaya is modified and applied to solve formed optimization problems. In the optimization problems, the objective aims to minimize the overall weight of beam; and fiber volume fractions, thicknesses and fiber orientation angles of layers are selected as design variables. The constraints include the restriction on the first fundamental frequency and the boundaries of design variables. Several numerical examples with different design scenarios are executed. The influence of the design variable types and the boundary conditions of beam on the optimal results is investigated. Moreover, the performance of Jaya is compared with that of the well-known methods, viz. differential evolution (DE), genetic algorithm (GA), and particle swarm optimization (PSO). The obtained results reveal that the proposed approach is efficient and provides better solutions than those acquired by the compared methods.

• Composites Research
• /
• 제21권1호
• /
• pp.30-39
• /
• 2008

본 논문에서는 기존의 유전자 알고리즘을 대신하여 병렬 마이크로 유전자 알고리즘을 사용한 복합재료 적층 구조물의 최적설계를 수행하였다. 마이크로 유전자 알고리즘은 한 세대 당 보통 5개의 개체로 해를 탐색한다 비록 세대를 구성하는 인구수는 적지만 공칭수렴 판단과 재초기화 과정을 통해 다양성을 제공하기 때문에 최적해 탐색이 가능하다. 2가지의 복합재 구조물의 최적화 문제를 가정하고 이를 마이크로 유전자 알고리즘을 사용하여 해를 구하였다. 효율성 판단을 위해서 기존의 유전자 알고리즘과 결과를 비교하였다. 두 문제 모두 마이크로 유전자 알고리즘이 비슷한 결과를 도출하면서도 약 70%의 계산량 감소를 보였다. 마이크로 유전자 알고리즘을 사용하여 일정 범위 내에서 변하는 하중을 받고 있는 복합재 적층 구조물의 최적설계를 수행하였다. 계산 결과 고정된 하중상태 하에서 얻은 최적해보다 하중 변화에 덜 민감한 설계변수를 얻을 수 있었다. 이상의 문제를 통해 다양한 설계변수를 갖는 복합재 적층 구조물의 최적설계의 한 방법으로서 마이크로 유전자 알고리즘이 효율적임을 확인하였다.

• Advances in concrete construction
• /
• 제11권1호
• /
• pp.1-9
• /
• 2021

This article discusses the issue of optimizing controller design issues, in which the artificial intelligence (AI) evolutionary bat (EB) optimization algorithm is combined with the fuzzy controller in the practical application of the building. The controller of the system design includes different sub-parts such as system initial condition parameters, EB optimal algorithm, fuzzy controller, stability analysis and sensor actuator. The advantage of the design is that for continuous systems with polytypic uncertainties, the integrated H2/H∞ robust output strategy with modified criterion is derived by asymptotically adjusting design parameters. Numerical verification of the time domain and the frequency domain shows that the novel system design provides precise prediction and control of the structural displacement response, which is necessary for the active control structure in the fuzzy model. Due to genetic algorithm (GA), we use a hierarchical conditions of the Hurwitz matrix test technique and the limits of average performance, Hierarchical Fitness Function Structure (HFFS). The dynamic fuzzy controller proposed in this paper is used to find the optimal control force required for active nonlinear control of building structures. This method has achieved successful results in closed system design from the example.

• 제어로봇시스템학회논문지
• /
• 제6권3호
• /
• pp.273-283
• /
• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.

• Smart Structures and Systems
• /
• 제15권1호
• /
• pp.191-207
• /
• 2015

Proper placement of sensors plays a key role in construction and implementation of an effective structural health monitoring (SHM) system. This paper proposes a novel methodology called the distributed monkey algorithm (DMA) for the optimum design of SHM system sensor arrays. Different from the existing algorithms, the dual-structure coding method is adopted for the representation of design variables and the single large population is partitioned into subsets and each subpopulation searches the space in different directions separately, leading to quicker convergence and higher searching capability. After the personal areas of all subpopulations have been finished, the initial optimal solutions in every subpopulation are extracted and reordered into a new subpopulation, and the harmony search algorithm (HSA) is incorporated to find the final optimal solution. A computational case of a high-rise building has been implemented to demonstrate the effectiveness of the proposed method. Investigations have clearly suggested that the proposed DMA is simple in concept, few in parameters, easy in implementation, and could generate sensor configurations superior to other conventional algorithms both in terms of generating optimal solutions as well as faster convergence.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
• /
• pp.243-246
• /
• 1996

Modular robot manipulator is a robotic system assembled from discrete joints and links into one of many possible manipulator configurations. This paper describes the design method of newly developed modular robot manipulator and the methodology of a task based reconfiguration of it. New locking mechanism is proposed and it provides quick coupling and decoupling. A parallel connection method is devised and it makes modular robot manipulator working well and the number of components on each module reduced. To automatically determine a sufficient or optimal arrangement of the modules for a given task, we also devise an algorithm that automatically generates forward and inverse manipulator kinematics, and we propose an algorithm which maps task specifications to the optimized manipulator configurations. Efficient genetic algorithms are generated and used to search for a optimal manipulator from task specifications. A few of design examples are shown.

• 한국공작기계학회논문집
• /
• 제16권3호
• /
• pp.96-102
• /
• 2007

An Optimal shape design of the boom system in high ladder vehicles is performed using 3-D finite element method (FEM). Results of structural analyses providing displacements, stresses are implemented for the optimum shape design. Lanzcos algorithm is used for the modal analysis in order to find natural frequencies. The optimal shape including cross sectional thickness and length of the boom system is controlled by the subproblem method besed on displacement and Von Mises stress. It is found that a plenty of materials can be saved by using shape design optimization in high ladder vehicles. It is also found that the natural frequency is increased until 6th mode and maintained similarly or decreased after 6th mode.

• 조명전기설비학회논문지
• /
• 제23권3호
• /
• pp.24-29
• /
• 2009

In case of the optimization problems that have many design variables, the conventional genetic algorithms(GA) fall into a trap of local minima with high probability. This problem is called the premature convergence problem. To overcome it, the parallel genetic algorithms which adopt the migration mechanism have been suggested. But it is hard to determine the several parameters such as the migration size and the migration interval for the parallel GAs. Therefore, we propose a new method to determine the migration interval automatically in this paper. To verify its validity, it is applied to some traditional mathematical optimization problems and is compared with the conventional parallel GA. It is also applied to the optimal design of the brushless DC motor for an electric wheel chair which is a real world problem and has five design variables.

• 한국공작기계학회논문집
• /
• 제17권6호
• /
• pp.35-42
• /
• 2008

Most of tasks for vertical surface work in shipyard have been accomplished by human workers. However, such manual work often causes injury to workers, also the production cost becomes high due to increasing individual wage. To cope with the circumstance, shipbuilding companies try to introduce wall-climbing robots for carrying out such kind of tasks. In designing a wall-climbing robot, it is essential to minimize its own weight to improve the performance such as moving speed and power saving. For such purpose. this study proposes a method of optimal design for a wall-climbing robot using a genetic algorithm with multi-objective function. Specifically, the thickness of the robot base is minimized to reduce the weight while maintaining the allowable strength and avoiding the resonance frequencies. The proposed method is applied to the design of a wall-climbing robot, and the result shows that the method is useful at an early design stage.

• 전자공학회논문지B
• /
• 제30B권5호
• /
• pp.18-26
• /
• 1993

This paper presents the design method for two-dimensional FIR digital filter using optimization scheme. The proposed design method is to extend the optimal one-dimensional filter design algorithm proposed by Parks and McClellan to two-dimensional case. When extending one-dimensional design scheme to two-dimensional one, some problems occur. In this paper we solved the problems by using the least square error model, the two-dimensional Lagrange interpolation, and the modified alternation theory. As a result, the equi-ripple FIR filter is obtained that is more optimal and more specific than the conventional methods.