• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.390-398
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• 2014

The systematic optimal tuning of power system stabilizers (PSSs) using the dynamic embedded optimization (DEO) technique is described in this paper. A hybrid system model which has the differential-algebraic-impulsive-switched (DAIS) structure is used as a tool for the DEO of PSSs. Two numerical optimization methods, which are the steepest descent and Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithms, are investigated to implement the DEO using the hybrid system model. As well as the gain and time constant of phase lead compensator, the output limits of PSSs with non-smooth nonlinearities are considered as the parameters to be optimized by the DEO. The simulation results show the effectiveness and robustness of the PSSs tuned by the proposed DEO technique on the IEEE 39 bus New England system to mitigate system damping.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.464-469
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• 2005

Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.

• Membrane and Water Treatment
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• v.9 no.2
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• pp.129-136
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• 2018

In this contribution, the control of multivariable reverse osmosis (RO) desalination plant using proportional-integral-derivative (PID) controllers is presented. First, feed-forward compensators are designed using simplified decoupling method and then the PID controllers are tuned for flux (flow-rate) and conductivity (salinity). The tuning of PID controllers is accomplished by minimization of the integral of squared error (ISE). The ISEs are minimized using a recently proposed algorithm named as teacher-learner-based-optimization (TLBO). TLBO algorithm is used due to being simple and being free from algorithm-specific parameters. A comparative analysis is carried out to prove the supremacy of TLBO algorithm over other state-of-art algorithms like particle swarm optimization (PSO), artificial bee colony (ABC) and differential evolution (DE). The simulation results and comparisons show that the purposed method performs better in terms of performance and can successfully be applied for tuning of PID controllers for RO desalination plants.

• Structural Engineering and Mechanics
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• v.73 no.5
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• pp.481-486
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• 2020

This paper deals with the buckling and optimization of a nanocomposite beam. The agglomeration of nanoparticles was assumed by Mori-Tanaka model. The harmony search optimization algorithm is adaptively improved using two adjusted processes based on dynamic parameters. The governing equations were derived by Timoshenko beam model by energy method. The optimum conditions of the nanocomposite beam- based proposed AIHS are compared with several existing harmony search algorithms. Applying DQ and Hs methods, the optimum values of radius and FS were obtained. The effects of thickness, agglomeration, volume percent of CNTs and boundary conditions were assumed. The results show that with increasing the volume percent of CNTs, the optimum radius of the beam decreases while the FS was improved.

• Ocean Systems Engineering
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• v.11 no.4
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• pp.301-312
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• 2021

An optimization framework has been established and applied to a shipshape parametric FPSO hull design. A single point moored (SPM) shipshape floating system suffers a significant level of the roll motion in both the wave frequencies and low wave frequencies, which presents a coupling effect with the horizontal weathervane motion. To guarantee the security of the operating instruments installed onboard, a parametric hull design of an FPSO has been optimized with improved hydrodynamics performance. With the optimized parameters of the various hull stations' longitudinal locations, the optimization through Genetic Algorithms (GAs) has been proven to provide a significantly reduced level of the 1st-order and 2nd-order roll motion. This work presents a meaningful framework as a reference in the process of an SPM shipshape floating system's design.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.120-128
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• 1997

In this paper, A design strategy of the Surface Mounting Device for accurate and better performance is studied. Analytical modeling, sensitivity analysis, and optimization are being conducted. The ANSYS software and experimental method are used for the verification of the analytical equations with boundary conditions. Through the sensitivity analysis, the most dominant design parameter can be detected. The optimum design parameters for improving the given performances are selected by using the optimiza- tion algorithm. The design tool based on the design strategy for the analysis, modeling, and optimization will be useful for are-design and better improving of the SMD.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.601-608
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• 2015

The static aeroelastic analysis and optimization of flexible wings are conducted for steady state conditions while both aerodynamic and structural parameters can be used as optimization variables. The system of multidisciplinary design optimization as a robust methodology to couple commercial codes for a static aeroelastic optimization purpose to yield a convenient adaptation to engineering applications is developed. Aspect ratio, taper ratio, sweepback angle are chosen as optimization variables and the skin thickness of the wing. The real-coded adaptive range multi-objective genetic algorithm code, which represents the global multi-objective optimization algorithm, was used to control the optimization process. The support vector regression(SVR) is applied for optimization, in order to reduce the time of computation. For this multi-objective design optimization problem, numerical results show that several useful Pareto optimal designs exist for the flexible wing.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.1-2
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• 1994

With the prevalence of computers in modern organizations, simulation is receiving more atention as an effectvie decision -making tool. Simualtion is a computer-based numerical technique which uses mathmatical and logical models to approximate the behaviror of a real-world system. However, iptimization of synamic stochastic systems often defy analytical and algorithmic soluions. Although a simulation approach is often free fo the liminting assumption s of mathematical modeling, cost and time consiceration s make simulation the henayst's last resort. Therefore, whenever possible, analytical and algorithmica solutions are favored over simulation. This paper discussed the issues and procedrues for using simulation as a tool for optimization of stochastic complex systems that are dmodeled by computer simulation . Its emphasis is mostly on issues that are speicific to simulation optimization instead of consentrating on the general optimizationand mathematical programming techniques . A simulation optimization problem is an optimization problem where the objective function. constraints, or both are response that can only be evauated by computer simulation. As such, these functions are only implicit functions of decision parameters of the system, and often stochastic in nature as well. Most of optimization techniqes can be classified as single or multiple-resoneses techniques . The optimization of single response functins has been researched extensively and consists of many techniques. In the single response category, these strategies are gradient based search techniques, stochastic approximate techniques, response surface techniques, and heuristic search techniques. In the multiple response categroy, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphica techniqes, direct search techniques, constrained optimization techniques, unconstrained optimization techniques, and goal programming techniques. The choice of theprocedreu to employ in simulation optimization depends on the analyst and the problem to be solved. For many practival and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computersimulation is one of the most effective means of studying such complex systems. In this paper, after discussion of simulation optmization techniques, the applications of above techniques will be presented in the modeling process of many flexible manufacturing systems.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.365-368
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• 2003

Despite of the simple equipment and operation, DMT has been widely used to obtain various soil parameters and those parameters have been successfully applied to geotechnical design practice. Among them, the estimation of horizontal coefficient of consolidation is so useful that many researchs recently have been carried out. However, simulation of the penetration of the DMT blade is complex due to the inherent difficulty on analyzing a plane strain deformation of the soil around blade. Therefore, empirical and semi-empirical methods that use the theoretical solution developed fur piezocone with some assumptions have been used to estimate the coefficient of consolidation from Dilatometer dissipation test. In this paper, coefficients of consolidation c$\_$h/ which were obtained using equivalent radius that is same area with the DMT blade and optimization technique are compared with those obtained from Oedometer test and other interpretation methods. It was found that a new method used in this study can give more precise horizontal coefficient of consolidation than other methods do.

• Interaction and multiscale mechanics
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• v.6 no.4
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• pp.339-356
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• 2013

This paper investigates the optimized parameters of Tuned Mass Dampers (TMDs) for vibration control of high-rise structures including Soil Structure Interaction (SSI). The Artificial Bee Colony (ABC) method is employed for optimization. The TMD Mass, damping coefficient and spring stiffness are assumed as the design variables of the controller; and the objective is set as the reduction of both the maximum displacement and acceleration of the building. The time domain analysis based on Newmark method is employed to obtain the displacement, velocity and acceleration of different stories and TMD in response to 6 types of far field earthquakes. The optimized mass, frequency and damping ratio are then formulated for different soil types; and employed for the design of TMD for the 40 and 15 story buildings and 10 different earthquakes, and well results are achieved. This study leads the researchers to the better understanding and designing of TMDs as passive controllers for the mitigation of earthquake oscillations.