• Smart Structures and Systems
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• v.20 no.1
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• pp.1-10
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• 2017

Ionic Polymer Metal Composite (IPMC) is an electroactive polymer (EAP) and a promising candidate actuator for various potential applications mainly due to its flexible, low voltage/power requirements, small and compact design, and lack of moving parts. Although widely used in industry, this material requires accurate numerical models and knowledge of optimal control methods. This paper presents State-Dependent Riccati Equation (SDRE) approach as one of rapidly emerging methodologies for designing nonlinear controllers. Additionally, the present paper describes a novel method of Multi HGO Observer design. In the proposed design, the calculated position of the IPMC strip accurately tracks the target position, which is illustrated by the experiments. Numerical results and comparison with experimental data are presented and the effectiveness of the proposed control strategy is verified in experiments.

• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.653-665
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• 2010

In this study, we introduce a neurofuzzy approach to the design of fuzzy controllers. The development process exploits key technologies of Computational Intelligence (CI), namely, genetic algorithms (GA) and neurofuzzy networks. The crux of the design methodology deals with the selection and determination of optimal values of the scaling factors of fuzzy controllers, which are essential to the entire optimization process. First, the tuning of the scaling factors of the fuzzy controller is carried out. Next, we form a nonlinear mapping for the scaling factors, which are realized by GA-based neurofuzzy networks by using a fuzzy set or fuzzy relation. The proposed approach is applied to control nonlinear systems like the inverted pendulum. Results of comprehensive numerical studies are presented through a detailed comparative analysis.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.8
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• pp.469-476
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• 2004

In this paper, a 3D shape optimization algorithm which guarantees a smooth optimal shape is presented using parameterized sensitivity analysis. The design surface is parameterized using Bezier spline and B-spline, and the control points of the spline are taken as the design variables. The parameterized sensitivity for the control points are found from that for nodal points. The design sensitivity and adjoint variable formulae are also derived for the 3D non-linear problems. Through an application to the shape optimization of 3D electromagnet to get a uniform magnetic field, the effectiveness of the proposed algorithm is shown.

• Journal of Korean Society of Transportation
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• v.6 no.1
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• pp.5-16
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• 1988

Development is given to an optimal network design method using continuous design variables. Modified Hooke-and-Jeeves algorithm is implemented in order to solve nonlinear programming problem which is approximately equivalent to the real network design problem with system efficiency crieteria and improvement cost as objective function. the method was tested for various forms of initial solution, and dimensions of initial step size of link improvements. At each searching point of evaluating the objective function, a link flow problem was solved with user equilibrium principles using the Frank-Wolfe algorithm. The results obtained are quite promising interms fo numbers of evaluation, and the speed of convergence. Suggestions are given to selections of efficient initial solution, initial step size and convergence criteria. An approximate method is also suggested for reducing computation time.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.43-48
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• 2003

In this study the optimization of plate-fin type heat sink for the thermal stability is performed numerically. The optimum design variables are obtained when the temperature rise and the pressure drop are minimized simultaneously. The flow and thermal fields are predicted using the finite volume method and the optimization is carried out by using the sequential quadratic programming (SQP) method which is widely used in the constrained nonlinear optimization problem. The results show that when the temperature rise is less than 34.6 K, the optimal design variables are as follows; $B_{1}$ = 2.468 mm, $B_{2}$ = 1.365 mm, and t = 10.962 mm. The Pareto optimal solutions are also presented for the pressure drop and the temperature rise.

• Solar Energy
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• v.6 no.1
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• pp.37-46
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• 1986

This paper deals with analytical methods for estimating the optimal design parameters of wind turbine from power output curve. Asmussen [5] has been used a linearized power output curve for an analytical expression for the specific output of wind turbine generators, but a nonlinear power output curve is developed to determine the design parameters of optimal wind turbine in this study that has maximum specific output and minimum swept area. Thus, the design results of this research will yield reliabilities in construction of wind turbine system and detailed results are presented for several district in Korea. Although the results presented pertain to a wind turbine system without storage, the design approach is equally applicable to system with storage.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.165-175
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• 2000

In order to improve the function of a door seal, its section design technique is discussed in this study, Its roles are prevention of an inflow of dusts, noise interception, insulation, wateproof, and the vibroisolating action which reduces vibration between the body and the door of a car while running, and the buffer action which sustain the proper reacting force as the door is closed. In this study, the optimal cross section of a door seal is designed using nonlinear finite element analysis (commercial finete element analysis program EASi-SEAL) and tables of orthogonal arralys with respect to relations between door and door seal to secure the satisfactory airtight property with the minimum force to shut the door.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2873-2875
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• 2005

The optimal structure of the conventional Fuzzy Polynomial Neural Networks (FPNN)[3] depends on experience of designer. For the conventional Fuzzy Polynomial Neural Networks, input variable number, number of input variable, number of Membership Functions(MFs) and consequence structures are selected through the experience of a model designer iteratively. In this paper, we propose the new design methodology to find the optimal structure of Fuzzy Polymomial Neural Network by using Genetic Algorithms(GAs)[4, 5]. In the sequel, It is shown that the proposed Advanced Genetic Algorithms based Fuzzy Polynomial Neural Network(Advanced GAs-based FPNN) is more useful and effective than the existing models for nonlinear process. We used Medical Imaging System(MIS)[6] data to evaluate the performance of the proposed model.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.452-454
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• 1998

Asymmetric cylinders are usually used as an actuator of active suspensions. The conventional optimal controller design does not include actuator dynamics as a state. and force controller is needed to track the desired force. But the actuator is not ideal, so performance of an active suspension system is degraded. In this paper, we take account nonlinear actuator dynamics and obtain a linear model using a feedback linearization technique then apply optimal control method. For real time application, gain-scheduling method is used. Effectiveness of proposed method is demonstrated by numerical simulation of 1/4 car model.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.93-98
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• 2001

This paper studies on the design of an ILQ(Inverse Linear Quadratic optimal control) looper control system for hot strip mills. The looper which is placed between each stand plays an important role in controlling strip width by regulating strip tension variation generated from the velocity difference of main work rolls. The mathematical model for looper is firstly obtained by Taylor's linearization of nonlinear differential equations, where it is given as a linear and time invariant state-space equation. Secondly, a looper servo controller is designed by ILQ control algorithm, which is an inverse problem of LQ(Linear Quadratic optimal control) control. By tunning control gain arbitration parameters and time constants, it is shown that the ILQ looper servo controller has the performance that makes well to follow desired trajectories of both strip tension and looper angle.