• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.2
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• pp.55-63
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• 2014

Fractures and wrinkles are two major defects frequently found in the sheet metal forming process. The process has several noise factors that cannot be ignored when determining the optimal process conditions. Therefore, without any countermeasures against noise, attempts to reduce defects through optimal design methods have often led to failure. In this study, a new and robust design methodology that can reduce the possibility of formation of fractures and wrinkles is presented using decision-making theory. A two-attribute value function is presented to form the design metric for the sheet metal forming process. A modified complex method is adopted to isolate the optimal robust design variables. One of the major limitations of the traditional robust design methodology, which is based on an orthogonal array experiment, is that the values of the optimal design variables have to coincide with one of the experimental levels. As this restriction is eliminated in the complex method, a better solution can be expected. The procedure of the proposed method is illustrated through a robust design of the sheet metal forming process of a side member of an automobile body.

• Structural Engineering and Mechanics
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• v.86 no.2
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• pp.249-260
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• 2023

The uncertainties involved in structural performances are of importance when the optimum number and property of seismic retrofit devices are determined. This paper proposes a seismic retrofit design framework for asymmetric soft-first-story buildings, considering uncertainties in the soil condition and seismic retrofit device. The effect of the uncertain parameters on the structural performance is used to find a robust and optimal seismic retrofit solution. The framework finds a robust and optimal seismic retrofit solution by finding the optimal locations and mechanical properties of the seismic retrofit device for different realizations of the uncertain parameters. The structural performance for each realization is computed to evaluate the effect of the uncertainty parameters on the seismic performance. The framework utilizes parallel processing to decrease the computationally intensive nonlinear dynamic analysis time. The framework returns a robust design solution that satisfies the given limit state for every realization of the uncertain parameters. The proposed framework is applied to the seismic retrofit design of a five-story asymmetric soft-first-story case study structure retrofitted with a viscoelastic damper. Robust optimal parameters for retrofitting a structure to satisfy the limit state for the different realizations of the uncertain parameter are found using the proposed framework. According to the performance evaluation results of the retrofitted structure, the developed framework is proved effective in the seismic retrofit of the asymmetric structure with inherent uncertainties.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2483-2491
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• 2002

This study presents an efficient method for robust optimal design. In order to avoid the excessive evaluations of the exact performance functions, two-point diagonal quadratic approximation method is employed for approximating them during optimization process. This approximation method is one of the two point approximation methods. Therefore, the second order sensitivity information of the approximated performance functions are calculated by an analytical method. As a result, this enables one to avoid the expensive evaluations of the exact $2^{nd}$ derivatives of the performance functions unlike the conventional robust optimal design methods based on the gradient information. Finally, in order to show the numerical performance of the proposed method, one mathematical problem and two mechanical design problems are solved and their results are compared with those of the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1062-1069
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• 2003

This paper presents a new loop shaping technique for design of robust optimal PID controllers in order to satisfy the performance requirements. PID controller can be designed by selecting the suitable weighting factors Q and R. This technique is developed by pushing all two zeros formed by PID controller closely to a larger pole of the second order plant. As a result, a good loop shaping is achieved in the high frequencies region on the Bode plot. For the robust optimal tuning of PID controller for second order system, a new loop shaping procedure is developed via LQR approach.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2262-2267
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• 2018

In electric machine design, there is a large computation cost for finite element analyses (FEA) when analyzing nonlinear characteristics in the machine Therefore, for the optimal design of an electric machine, designers commonly use an optimization algorithm capable of excellent convergence performance. However, robustness consideration, as this factor can guarantee machine performances capabilities within design uncertainties such as the manufacturing tolerance or external perturbations, is essential during the machine design process. Moreover, additional FEA is required to search robust optimum. To address this issue, this paper proposes a computationally efficient robust optimization algorithm. To reduce the computational burden of the FEA, the proposed algorithm employs a useful technique which termed static analysis assisted technique (SAAT). The proposed method is verified via the effective robust optimal design of electric machine to reduce cogging torque at a reasonable computational cost.

• Journal of the Korea Safety Management & Science
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• v.2 no.2
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• pp.29-40
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• 2000

In this paper, under JIT kanban system designed by Moeeni, each performance measures (service level, inventory level) identify the robust optimal level at a uncertain environment, and when there are multiple performance characteristics, it propose the optimal design-method and the optimal level decision-method, which consider multiple performance characteristics.

• Journal of information and communication convergence engineering
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• v.2 no.3
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• pp.198-201
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• 2004

In this paper, the discrete optimal control is made to have the robust property of Sliding mode controller. A augmented system with a virtual state is constructed for this objective and noble sliding surface is constructed based on this system. The sliding surface is the same as the optimal control trajectory in the original system. The states follow the optimal trajectory even if there exist uncertainties. The reaching phase problem of sliding mode control is disappear in this method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.513-521
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• 2017

Robust optimal operation of a microgrid is required since the increase of the penetration level of renewable generators in the microgrid raises uncertainty due to their intermittent power output. In this paper, an application of probabilistic optimization method to economical operation of a microgrid is studied. To simplify the treatment of the uncertainties of renewable generations and load, the new 'band of virtual equivalent load variation' is introduced considering their uncertainties. A simplified robust optimization methodology to generate the scenarios within the band of virtual equivalent load variation and to obtain the optimal solution for the worst scenario is presented based on Monte Carlo method. The microgrid to be studied here is composed of distributed generation system(DGs), battery systems and loads. The distributed generation systems include combined heat and power(CHP) and small generators such as diesel generators and the renewable energy generators such as photovoltaic(PV) systems and wind power systems. The modeling of the objective function for considering interruption cost by the penalty function is presented. Through the case study for a microgrid with uncertainties, the validity of proposed robust optimization methodology is evaluated.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.10-14
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• 2004

We present a predictive control algorithm combined with the robust robot control that is constructed on the Lyapunov min-max approach. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about the model, it is an important trend to design a robust control law that guarantees the desired properties of the manipulator under uncertain elements. In the preceding robust control work, we need to tune several control parameters in the admissible set where the desired stability can be achieved. By introducing an optimal predictive control technique in robust control we can find out much more deterministic controller for both the stability and the performance of manipulators. A new class of robust control combined with an optimal predictive control is constructed. We apply it to a simple type of 2-link robot manipulator and show that a desired performance can be achieved through the computer simulation.

• Smart Structures and Systems
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• v.13 no.3
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• pp.473-500
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• 2014

Tuned mass dampers (TMDs) have been installed in many high-rise buildings, to improve their resiliency under dynamic loads. However, high-rise buildings may experience natural frequency changes under ambient temperature fluctuations, extreme wind loads and relative humidity variations. This makes the design of a TMD challenging and may lead to a detuned scenario, which can reduce significantly the performance. To alleviate this problem, the current paper presents a proposed approach for the design of a robust and efficient TMD. The approach accounts for the uncertain natural frequency, the optimization objective and the input excitation. The study shows that robust design parameters can be different from the optimal parameters. Nevertheless, predetermined optimal parameters are useful to attain design robustness. A case study of a high-rise building is executed. The TMD designed with the proposed approach showed its robustness and effectiveness in reducing the responses of high-rise buildings under multidirectional wind. The case study represents an engineered design that is instructive. The results show that shear buildings may be controlled with less effort than cantilever buildings. Structural control performance in high-rise buildings may depend on the shape of the building, hence the flow patterns, as well as the wind direction angle. To further increase the performance of the robust TMD in one lateral direction, active control using LQG and fuzzy logic controllers was carried out. The performance of the controllers is remarkable in enhancing the response reduction. In addition, the fuzzy logic controller may be more robust than the LQG controller.