• Geomechanics and Engineering
• /
• 제24권3호
• /
• pp.237-251
• /
• 2021

The main purpose of this study is to investigate the performance of the proposed hybrid teaching-learning based optimization algorithm on the optimum design of reinforced concrete (RC) cantilever retaining walls. For this purpose, three different design examples are optimized with 100 independent runs considering continuous and discrete variables. In order to determine the algorithm performance, the optimization results were compared with the outcomes of the nine powerful meta-heuristic algorithms applied to this problem, previously: the big bang-big crunch (BB-BC), the biogeography based optimization (BBO), the flower pollination (FPA), the grey wolf optimization (GWO), the harmony search (HS), the particle swarm optimization (PSO), the teaching-learning based optimization (TLBO), the jaya (JA), and Rao-3 algorithms. Moreover, Rao-1 and Rao-2 algorithms are applied to this design problem for the first time. The objective function is defined as minimizing the total material and labor costs including concrete, steel, and formwork per unit length of the cantilever retaining walls subjected to the requirements of the American Concrete Institute (ACI 318-05). Furthermore, the effects of peak ground acceleration value on minimum total cost is investigated using various stem height, surcharge loads, and backfill slope angle. Finally, the most robust results were obtained by HTLBO with 50 populations. Consequently the optimization results show that, depending on the increase in PGA value, the optimum cost of RC cantilever retaining walls increases smoothly with the stem height but increases rapidly with the surcharge loads and backfill slope angle.

• 대한기계학회논문집A
• /
• 제21권1호
• /
• pp.112-123
• /
• 1997

The optimization techniques have been applied to versatile engineering problems for reducing manufacturing cost and for automatic design. The deterministic approaches or op5imization neglect the effects on uncertainties of design variables. The uncertainties include variation or perturbation such as tolerance band. The optimum may be useless when the constraints considering worst cases of design variables can not be satisfied, which results from constraint variation. The variation of design variables can also give rise to drastic change of performances. The two issues are related to constraint feasibility and insensitive performance. Robust design suggested in the present study is developed to gain an optimum insensitive to variation on design variables within feasible region. The multiobjective function is composed to the mean and the standard deviation of original objective function, while the constraints are supplemented by adding penalty term to original constraints. This method has a advantage that the second derivatives of the constraints are not required. A mathematical problem and several standard problems for structural optimization are solved to check out the usefulness of the suggested method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.1758-1763
• /
• 2004

This paper focuses on congestion control for ATM network with uncertain time-variant delays. The time-variant delays can be distinguished into two distinct components. The first one is represented by time-variant queueing delays in the intermediate switches that are occurred in the return paths of RM cells. The next one is a forward path delay. It is solved by the VBR model which quantifies the data propagation from the sources to the switch. Robust $H_8$ control is studied for solving congestion problem with norm-bounded time-varying uncertain parameters. The suitable robust $H_8$ controller is obtained from the solution of a convex optimization problem through LMI technique.

• 산업공학
• /
• 제15권2호
• /
• pp.189-198
• /
• 2002

Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 하계학술대회 논문집 D
• /
• pp.2161-2163
• /
• 2004

This paper focuses on congestion control for ATM network with uncertain time-variant delays. The time-variant delays can be distinguished into two distinct components. The first one that is represented by time-variant queueing delays in the intermediate switches is occurred in the return paths of RM cells. The next one is a forward path delay. It is solved by the VBR Model which quantifies the data propagation from the sources to the switch. Robust $H_{\infty}$ control is studied for solving congestion problem with norm-bounded time-varying uncertain parameters. The suitable robust $H_{\infty}$ controller is obtained from the solution of a convex optimization problem including terms of LMIs.

• International Journal of Control, Automation, and Systems
• /
• 제6권2호
• /
• pp.171-179
• /
• 2008

This paper addresses the synthesis of an iterative learning controller for a class of linear systems with norm-bounded parameter uncertainties. We take into account an iterative learning algorithm with current cycle feedback in order to achieve both robust convergence and robust stability. The synthesis problem of the developed iterative learning control (ILC) system is reformulated as the ${\gamma}$-suboptimal $H_{\infty}$ control problem via the linear fractional transformation (LFT). A sufficient convergence condition of the ILC system is presented in terms of linear matrix inequalities (LMIs). Furthermore, the ILC system with fast convergence rate is constructed using a convex optimization technique with LMI constraints. The simulation results demonstrate the effectiveness of the proposed method.

• Journal of Communications and Networks
• /
• 제16권1호
• /
• pp.45-55
• /
• 2014

The paper investigates the problem of designing the multiple-antenna relay in a two-way relay network by taking into account the imperfect channel state information (CSI). The objective is to design the multiple-antenna relay based upon the CSI estimates, where the estimation errors are included to attain the robust design under the worst-case philosophy. In particular, the worst-case transmit power at the multiple-antenna relay is minimized while guaranteeing the worst-case quality of service requirements that the received signal-to-noise ratio (SNR) at both sources are above a prescribed threshold value. Since the worst-case received SNR expression is too complex for subsequent derivation and processing, its lower bound is explored instead by minimizing the numerator and maximizing the denominator of the worst-case SNR. The aforementioned problem is mathematically formulated and shown to be nonconvex. This motivates the pursuit of semidefinite relaxation coupled with a randomization technique to obtain computationally efficient high-quality approximate solutions. This paper has shown that the original optimization problem can be reformulated and then relaxed to a convex problem that can be solved by utilizing suitable randomization loop. Numerical results compare the proposed multiple-antenna relay with the existing nonrobust method, and therefore validate its robustness against the channel uncertainty. Finally, the feasibility of the proposed design and the associated influencing factors are discussed by means of extensive Monte Carlo simulations.

• Structural Engineering and Mechanics
• /
• 제67권1호
• /
• pp.33-43
• /
• 2018

The dynamic output-feedback robust control method based on linear matrix inequality (LMI) method is presented for suppressing vibration response of a functionally graded material (FGM) beam with piezoelectric actuator/sensor layers in this paper. Based on the reduced model obtained by using direct mode truncation, the linear fractional state space representation of a piezoelectric FGM beam with material properties varying through the thickness is developed by considering both the inherent uncertainties in constitution material properties as well as material distribution and the model error due to mode truncation. The dynamic output-feedback robust H-infinity control law is implemented to suppress the vibration response of the piezoelectric FGM beam and the LMI method is utilized to convert control problem into convex optimization problem for efficient computation. In numerical studies, the flexural vibration control of a cantilever piezoelectric FGM beam is considered to investigate the accuracy and efficiency of the proposed control method. Compared with the efficient linear quadratic regulator (LQR) widely employed in literatures, the proposed robust control method requires less control voltage applied to the piezoelectric actuator in the case of same control performance for the controlled closed-loop system.

• Structural Engineering and Mechanics
• /
• 제86권5호
• /
• pp.647-661
• /
• 2023

It is recognized that the installation of energy dissipation devices, such as the tuned mass damper (TMD), decreases the dynamic response of structures, however, the best parameters of each device persist hard to determine. Unlike many works that perform only a deterministic optimization, this work proposes a complete methodology to minimize the dynamic response of footbridges by optimizing the parameters of multiple tuned mass dampers (MTMD) taking into account uncertainties present in the parameters of the structure and also of the human excitation. For application purposes, a steel footbridge, based on a real structure, is studied. Three different scenarios for the MTMD are simulated. The proposed robust optimization problem is solved via the Circle-Inspired Optimization Algorithm (CIOA), a novel and efficient metaheuristic algorithm recently developed by the authors. The objective function is to minimize the mean maximum vertical displacement of the footbridge, whereas the design variables are the stiffness and damping constants of the MTMD. The results showed the excellent capacity of the proposed methodology, reducing the mean maximum vertical displacement by more than 36% and in a computational time about 9% less than using a classical genetic algorithm. The results obtained by the proposed methodology are also compared with results obtained through traditional TMD design methods, showing again the best performance of the proposed optimization method. Finally, an analysis of the maximum vertical acceleration showed a reduction of more than 91% for the three scenarios, leading the footbridge to acceleration values below the recommended comfort limits. Hence, the proposed methodology could be employed to optimize MTMD, improving the design of footbridges.

• 대한기계학회논문집A
• /
• 제27권8호
• /
• pp.1426-1435
• /
• 2003

Design goal is to find the one that has the highest probability of success and the smallest variation. A robustness index has been proposed to satisfy these conditions. The two-step optimization process of the target problem requires a scaling factor. The search process of a scaling factor is replaced with the making of the decoupled design between the mean and the standard deviation. The decoupled design matrix is formed from the sensitivity or the sum of squares. After establishing the design matrix, the robust design process has a new three-step one. The first is ″reduce variability,″ the second is ″make the candidate designs that satisfy constraints and move the mean on the target,″ and the final is ″select the best robust design using the proposed robustness index.″ The robust design process is verified by three examples and the results using the robustness index are compared with those of other indices.