• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.43-52
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• 2022

Design of a controller for a high-precision servo control system has been a popular topic while finding optimal parameters for multiple controllers is still a challenging subject. In this paper, we propose a practical scheme to optimize multi-parameters for the robust servo controller design by introducing a new cost function and optimization scheme. The proposed design method provides a simple and practical tool for the systematic servo design to reduce the control error with guaranteeing robust stability of the overall system. The reduction of the position error by 24% along with a faster convergence rate is demonstrated using a typical hard disk drive servo controller with 41 parameters.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.1
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• pp.29-34
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• 2008

The efforts of reflecting the system's uncertainties in design step have been made and robust optimization or reliability-based design optimization are examples of the most famous methodologies. In their formulation, the mean and standard deviation of a performance function and constraints expressed by probability conditions are involved. Therefore, it is essential to effectively and accurately calculate them and, in addition, the sensitivity results are required to obtain when the nonlinear programming is utilized during optimization process. We aim to obtain the new and efficient sensitivity formulation, which is based on integral form, on statistical moments such as the mean and standard deviation, and probability constraints. It does not require the additional functional calculation when statistical moments and failure or satisfaction probabilities are already obtained at a design point. Moreover, some numerical examples have been calculated and compared with the exact solution or the results of Monte Carlo Simulation method. The results seem to be very satisfactory.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.2
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• pp.99-104
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• 2008

This study performed robust design optimization of fighter wing planform, considering uncertainty based on neural network model. To construct uncertainty model, aerodynamic performance and their sensitivity were evaluated by 3-dimensional Euler equations and adjoint variable method at experimental points selected from central composite design. In addition, because a neural network model has the advantage of capturing non-linear characteristic, it was possible to predict sensitivity of the aerodynamic performance efficiently and accurately . From the results of robust design optimization, it could be confirmed that the robustness of the objective function and constraints were improved if the variation of uncertainty and sigma level were increased.

• Journal of Ocean Engineering and Technology
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• v.13 no.4 s.35
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• pp.182-189
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• 1999

The robust design technology which can determine design variables getting best performance function with insensitivity to the environment noise, is an important method for improving the performance of products at low cost. Applying the robust design technology in ship design, Koh et al[10] introduced the planing hull design. This paper reports the application this technology to a 150K bulk carrier which has many design variables and shows that the robust design technology is superior to optimization technique in practical use.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.3
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• pp.225-231
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• 2004

Disturbance observer (DOB) has been studied extensively and applied to many motion control fields during the last decades, but relatively few studies have been devoted to the development of analytic, systematic design methods for DOB itself, This paper thus aims to provide an analytic, systematic design method for DOB. To do this, DOB is structurally analyzed and the generalized disturbance compensation framework named robust internal-loop compensator (RIC) is introduced. Through this, the inherent equivalence between DOB and RIC is found, and the mixed sensitivity optimization problem of DOB is solved. Q-filter design is completely separated from the mixed sensitivity optimization problems of DOB although the proposed method has implicit .elation with Q-filter. Also, although the Q-fille. is separately designed with sensitivity function, the proposed DOB framework has the exactly same characteristic as the original DOB.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.225-235
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• 2005

This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included in the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.215-221
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• 1997

A new approach in solving design centering problem is presented. Like most stochastic optimization problems, optimal design centering problems have intrinsic difficulties in multivariate intergration of probability density functions. In order to avoid to avoid those difficulties, genetic algorithm and very coarse Monte Carlo simulation are used in this research. The new algorithm performs robustly while producing improved yields. This result implies that the combination of robust optimization methods and approximated simulation schemes would give promising ways for many stochastic optimizations which are inappropriate for mathematical programming.

• Smart Structures and Systems
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• v.12 no.6
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• pp.641-659
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• 2013

In this paper is studied the influence of the uncertain mass distribution over the floors on the choice of the optimal parameters of a hybrid control system for tall buildings subjected to wind load. In particular, an optimization procedure is developed for the robust design of a hybrid control system that is based on an enhanced Monte Carlo simulation technique and the genetic algorithm. The large computational effort inherent in the use of a MC-based procedure is reduced by the employment of the Latin Hypercube Sampling. With reference to a tall building modeled as a multi degrees of freedom system, several numerical analyses are carried out varying the parameters influencing the floors' masses, like the coefficient of variation of the distribution and the correlation between the floors' masses. The procedure allows to obtain optimal designs of the control system that are robust with respect to the uncertainties on the distribution of the dead and live loads.

• Structural Engineering and Mechanics
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• v.56 no.5
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• pp.707-726
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• 2015

There is a growing trend of considering uncertainty in optimization process since last few decades. In this regard, Robust Design Optimization (RDO) scheme has gained increasing momentum because of its virtue of improving performance of structure by minimizing the variation of performance and ensuring necessary safety and feasibility of constraint under uncertainty. In the present study, RDO of reinforced concrete folded plate and shell structure has been carried out incorporating uncertainty in the relevant parameters by Monte Carlo Simulation. Folded plate and shell structures are among the new generation popular structures often used in aesthetically appealing constructions. However, RDO study of such important structures is observed to be scarce. The optimization problem is formulated as cost minimization problem subjected to the force and displacements constraints considering dead, live and wind load. Then, the RDO is framed by simultaneously optimizing the expected value and the variation of the performance function using weighted sum approach. The robustness in constraint is ensured by adding suitable penalty term and through a target reliability index. The RDO problem is solved by Sequential Quadratic Programming. Subsequently, the results of the RDO are compared with conventional deterministic design approach. The parametric study implies that robust designs can be achieved by sacrificing only small increment in initial cost, but at the same time, considerable quality and guarantee of the structural behaviour can be ensured by the RDO solutions.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.215.2-215.2
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• 2005