• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.3
• /
• pp.458-465
• /
• 2008

In this paper, we propose a non-fragile guaranteed cost controller design method for uncertain linear systems with constant delyas in state. The norm bounded and time-varying uncertainties are subjected to system and controller design matrices. A quadratic cost function is considered as the performance measure for the system. Based on the Lyapunov method, an LMI(Linear Matrix Inequality) optimization problem is established to design the controller which uses information of delayed state and minimizes the upper bound of the quadratic cost function for all admissible system uncertainties and controller gain variations. Numerical examples show the effectiveness of the proposed method.

• Journal of Integrative Natural Science
• /
• v.14 no.4
• /
• pp.197-204
• /
• 2021

Under the two-phase warranty, the warranty period is divided into two intervals, one of which is for renewing replacement warranty, and the other is for minimal repair warranty. Jung^[13] discusses the two types of extended two-phase warranty models. In this paper, we suggest the replacement model after the extended two-phase warranty that has been proposed by Jung^[13]. To determine the optimal replacement policy, we adopt the expected cost rate per unit time. So, the expressions for the total expected cost, the expected length of the cycle and the expected cost rate per unit time from the user's point of view are derived. Also, we discuss the optimal replacement policy and the uniqueness of the solution for the optimization. Furthermore, the numerical examples are provided to illustrate the proposed the replacement model.

• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.468-473
• /
• 2004

New reliability-based topology optimization method is proposed by utilizing single-loop single vector approach, which approximate searching the most probable point in the probabilistic design domain analytically, to reduce the time cost and dealing with several constraints to handle practical design requirements. To examine uncertainties in the topology design of a structure, the modulus of elasticity of the material and applied loadings are considered as probabilistic design variables. The results of design examples show that the proposed method provides efficiency curtailing the time for the optimization process and accuracy satisfying the specified reliability.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.2
• /
• pp.471-477
• /
• 2014

The novel permanent magnetic actuator (PMA) and its optimal design method were proposed in this paper. The proposed PMA is referred to as the separated permanent magnetic actuator (SPMA) and significantly superior in terms of its cost and performance level over a conventional PMA. The proposed optimal design method uses the evolutionary strategy algorithm (ESA), the kriging meta-model (KMM), and the multi-step optimization. The KMM can compensate the slow convergence of the ESA. The proposed multi-step optimization process, which separates the independent variables, can decrease time and increase the reliability for the optimal design result. Briefly, the optimization time and the poor reliability of the optimum are mitigated by the proposed optimization method.

• Nuclear Engineering and Technology
• /
• v.50 no.6
• /
• pp.877-885
• /
• 2018

Various controllers such as proportional-integral-derivative (PID) controllers have been designed and optimized for load-following issues in nuclear reactors. To achieve high performance, gain tuning is of great importance in PID controllers. In this work, gains of a PID controller are optimized for power-level control of a typical pressurized water reactor using particle swarm optimization (PSO) algorithm. The point kinetic is used as a reactor power model. In PSO, the objective (cost) function defined by decision variables including overshoot, settling time, and stabilization time (stability condition) must be minimized (optimized). Stability condition is guaranteed by Lyapunov synthesis. The simulation results demonstrated good stability and high performance of the closed-loop PSO-PID controller to response power demand.

• Coupled systems mechanics
• /
• v.13 no.3
• /
• pp.219-229
• /
• 2024

By introducing optimization algorithms into the machining process, product quality can be improved, time saved, and costs reduced. The cutting speed and feed can be handled by the turning machine. The approach of optimizing is used to manage pyrotechnics, Lawler's, greedy, bacterial colony, elephant herding, ant lion, spiral, auction, and pattern search for these ten odd ways. Ten artificial optimization methodologies were used to investigate the time and cost of a turning machine. It has been discovered how to create the optimal turning machine procedure. The best solution approach for the turning machine process problem is found, and the results are verified using ANSYS.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.10
• /
• pp.66-76
• /
• 2002

Automated welding and soldering are an important manufacturing issue in order to lower the cost, increase the quality, and avoid labor problems. An off-line programming, OLP, is one of the powerful methods to solve this kind of diversity problem. Unless an OLP system is ready for the path optimization in welding and soldering, the waste of time and cost is unavoidable due to inefficient paths in welding and soldering processes. Therefore, this study attempts to obtain path optimization using a genetic algorithm based on artificial intelligences. The problem of welding path optimization is defined as a conventional TSP (traveling salesman problem), but still paths have to go through welding lines. An improved genetic algorithm was suggested and the problem was formulated as a TSP problem considering the both end points of each welding line read from database files, and then the transit problem of welding line was solved using the improved suggested genetic algorithm.

• Tribology and Lubricants
• /
• v.39 no.3
• /
• pp.94-101
• /
• 2023

Automotive wheel bearings are a critical component of vehicles that support their weight and facilitate rotation. Life and stiffness are significant performance characteristics of wheel bearings. Designing wheel bearings involves finding optimal design variables that satisfy both performances. CO₂ emission reduction and fuel efficiency regulations attribute to the recent increase in design requirements for lightweight and compact automotive parts while maintaining performance. However, achieving a design that maintains performance while reducing weight poses challenges, as performance and weight are generally inversely proportional. In this study, we perform design optimization of automotive wheel bearings considering life and stiffness. We develop a program that calculates the basic rated life and modified rated life based on international standards for evaluating the life of wheel bearings. We develop a regression equation using regression analysis to address the time-consuming stiffness analysis during repetitive analysis. We perform ANOVA and main effect analyses to understand the statistical characteristics of the developed regression equation. Furthermore, we verify its reliability by comparing the predicted and test results. We perform design optimization using the developed life prediction program, stiffness regression equation and weight regression equation. We select bearing specifications and geometry as design variables, weight as the cost function, and life and stiffness as constraints. Through design optimization, we investigate the influence of design variables on the cost function and constraints by comparing the initial and optimal design values.

• Proceedings of the KIEE Conference
• /
• 2000.07a
• /
• pp.142-146
• /
• 2000

This paper Presents a heuristic algorithm based on branch exchange method to solve ORP (Optimal Routing Problem) for distribution system planning. The ORP is a complex task which is generally formulated as a combinatorial optimization problem with various constraints. The cost function of ORP is consisted of the investment cost and the system operation cost that is generally expressed with system power loss. This paper also adopt an specialy designed selection method of maximum loss reduction loop and branch to reduce optimization time. The effectiveness of the proposed algorithm was shown with 32, 69 bus example system.

• Journal of Electrical Engineering and information Science
• /
• v.2 no.6
• /
• pp.28-35
• /
• 1997

A new approach concurrent transistor sizing and buffer insertion for low power optimization is proposed in this paper. The method considers the tradeoff between upsizing transistors and inserting buffers and chooses the solution with the lowest possible power and area cost. It operates by analyzing the feasible region of the cost-delay curves of the unbuffered and buffered circuits. As such the feasible region of circuits optimized by our method is extended to encompass the envelop of cost-delay curves which represent the union of the feasible regions of all buffered ad unbuffered versions of the circuit. The method is efficient and tunable in that optimality can be traded for compute time and as a result it can in theory near optimal results.