• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.59-65
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• 2011

In this paper, we present a reduced-order parameter-dependent robust $H_{\infty}$ filter design method for discrete-time singular systems with polytopic uncertainties. A BRL(bounded real lemma) for parameter-dependent singular systems is derived from a parameter-dependent Lyapunov function. On the basis of the obtained BRL, low order robust $H_{\infty}$ filter design method is presented by polytopic approach, new reduced-order method, and LMI(linear matrix inequality) technique. Finally, a numerical example is presented to illustrated the feasibility of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.374-377
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• 2006

본 논문은 에어컨 시스템의 효율성과 안정성에 기초하여, 과열도와 저압을 제어하는 Fuzzy 제어기 설계를 제안한다. 에어컨 시스템은 Compressor(압축기), Condenser(응축기), Evaporator(증발기), Expansion Valve(확장 밸브) 로 구성되며, 각각의 기기에 대한 제어가 독립적으로 이루어져 있다. 기존의 제어가 한 제어기를 사용한 단일방식으로 이루어지다보니 에어컨 시스템의 특성인 냉매의 상태가 달라지면 시스템 전반적으로 그 영향이 파급되는 부분까지 고려를 해 주지 못하고, 제어기의 성능이 효율적이고 안정적이지 못했다. 본 논문에서는 에어컨 시스템의 효율과 안정도에 결정적인 영향을 미치는 과열도와 저압(증발기의 압력)을 제어하기 위해, 비선형성이 강하고 불확실하며 복잡한 시스템을 쉽게 제어할 수 있는 Fuzzy 제어기를 구성하여, Expansion Valve 와 Compressor 에서 동시에 제어하는 Multi 제어기를 설계한다. 제안된 Fuzzy 제어기는 이산형 lookup_table 방식과 연속형 간략추론 방식을 사용하여 제어기를 설계하고, 유전자 알고리즘(GAs)을 이용하여 최적의 Fuzzy 제어기의 환산계수를 구한다. 그리고 시뮬레이션 결과를 통해 이산형 lookup_table 방식과 연속형 간략추론 방식의 각각의 제어기를 사용한 결과를 비교한다.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.1
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• pp.122-130
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design, this study proposes a design method for determining design variables of an automotive wheel-bearing unit of double-row angular-contact ball bearing type by using a genetic algorithm. The desired performance of the wheel-bearing unit is to maximize system life while satisfying geometrical and operational constraints without enlarging mounting spae. The use of gradient-based optimization methods for the design of the unit is restricted because this design problem is characterized by the presence of discrete design variables such as the number of balls and standard ball diameter. Therefore, the design problem of rolling element bearings is a constrained discrete optimization problem. A genetic algorithm using real coding and dynamic mutation rate is used to efficiently find the optimum discrete design values. To effectively deal with the design constraints, a ranking method is suggested for constructing a fitness function in the genetic algorithm. A computer program is developed and applied to the design of a real wheel-bearing unit model to evaluate the proposed design method. Optimum design results demonstrate the effectiveness of the design method suggested in this study by showing that the system life of an optimally designed wheel-bearing unit is enhanced in comparison with that of the current design without any constraint violations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.9
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• pp.1399-1407
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• 2004

Structural optimization has been carried out in continuous design space or in discrete design space. Generally, available designs are discrete in design practice. However, the methods for discrete variables are extremely expensive in computational cost. An iterative optimization algorithm is proposed for design in a discrete space, which is called a sequential algorithm using orthogonal arrays (SOA). We demonstrate verifying the fact that a local optimum solution can be obtained from the process with this algorithm. The local optimum solution is defined in a discrete design space. Then the search space, which is a set of candidate values of each design variables formed by the neighborhood of a current design point, is defined. It is verified that a local optimum solution can be found by sequentially moving the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained by using the SOA algorithm

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.8 s.179
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• pp.1940-1948
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• 2000

A design method for maximizing fatigue life of the deep groove ball bearing without enlarging mounting space is proposed by using a genetic algorithm. The use of gradient-based optimization methods for the design of the bearing is restricted because this design problem is characterized by the presence of discrete design variables such as the number of balls and standard ball diameter. Therefore, the design problem of rolling element bearings is a constrained discrete optimization problem. A genetic algorithm using real coding is used to efficiently find the optimum discrete design values. To effectively deal with the design constraints, a ranking method is suggested for constructing a fitness function in the genetic algorithm. Constrains for manufacturing are applied in optimization scheme. Results obtained for several 63 series deep groove ball bearings demonstrated the effectiveness of the proposed design methodology by showing that the average basic dynamic capacities of optimally designed bearings increased about 9-34% compared with the standard ones.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1005-1010
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• 2004

The structural optimization has been carried out in the continuous design space or in the discrete design space. Generally, available designs are discrete in design practice. But methods for discrete variables are extremely expensive in computational cost. In order to overcome this weakness, an iterative optimization algorithm was proposed for design in the discrete space, which is called as a sequential algorithm using orthogonal arrays (SOA). We focus to verify the fact that the local solution can be obtained throughout the optimization with this algorithm. The local solution is defined in discrete design space. Then the search space, which is the set of candidate values of each design variables formed by the neighborhood of current design point, is defined. It is verified that a local solution can be founded by moving sequentially the search space. The SOA algorithm has been applied to problems such as truss type structures. Then it is confirmed that a local solution can be obtained using the SOA algorithm

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.118-123
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• 2004

In this study, genetic algorithm mixed binary and real encoding is proposed to deal with design variables of various types. And that is applied to optimum design of Multi-stage gear drive. Design of pressure vessel which is mixed discrete and continuous variables is applied to verify reasonableness of proposed genetic algorithm. The proposed genetic algorithm is applied for the gear ratio optimization and the volume minimization of geared motor which is used in field. In result, it shows that the volume has decreased about 8% compared with the existing geared motor.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.6
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• pp.49-56
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• 2010

This study was conducted to find out the best optimum design method for the design of reinforced concrete agricultural aqueduct abutment and pier structures. The mixed-discrete optimization and continuous optimization method were applied to the design of reinforced concrete agricultural aqueduct abutment and pier and the results of these optimization methods were compared each other. It is proved that mixed-discrete optimization method is more reliable, efficient and reasonable than continuous optimization method for the optimum design of the reinforced concrete agricultural aqueduct abutment and pier.

• Journal of Korean Association for Spatial Structures
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• v.9 no.3
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• pp.75-82
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• 2009

This paper investigates the variation of post-buckling behaviours of spatial structures after sizing optimization with linear assumptions. The mathematical programming technique is used to produce the optimum member size of spatial structures against external load. Total weight of structure is considered as the objective function to be minimized and the displacement occurred at loading point and member stresses of structures are used as the constraint functions. The finite difference method is used to calculate the design sensitivity of objective function with respect to design variables. The post-buckling analysis carried out by using the geometrically nonlinear finite element analysis code ISADO-GN. It is found to be that there is a huge difference between the post buckling behaviours of the initial and optimized structures. Therefore, the stability of optimized spatial structures with linear assumption should be throughly checked by appropriate nonlinear analysis techniques. Finally, the present numerical results are provided as benchmark test suite for future study of large spatial structures.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.408-413
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• 2001

The structural optimization is carried out in the continuous design space or discrete design space. Methods for discrete variables such as genetic algorithms are extremely expensive in computational cost. In this research, an iterative optimization algorithm using orthogonal arrays is developed for design in discrete space. An orthogonal array is selected on a discrete design space and levels are selected from candidate values. Matrix experiments with the orthogonal array are conducted. New results of matrix experiments are obtained with penalty functions for constraints. A new design is determined from analysis of means(ANOM). An orthogonal array is defined around the new values and matrix experiments are conducted. The final optimum design is found from iterative process. The suggested algorithm has been applied to various problems such as truss and frame type structures. The results are compared with those from a genetic algorithm and discussed.