• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.369-369
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• 2000

Control system by means of fuzzy theory has demonstrated its robustness in applying to the high-order and nonlinear dynamic system in that it can utilizes the human expert knowledges in system design. In this paper, first, the design methodology of HFC combined PID controller with fuzzy controller by membership function of weighting coefficient is proposed. Second, Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to improve the performance of hybrid fuzzy controller. Especially, in order to obtain the optimal scaling factors and PID parameters of HFC using GA based on advanced initial individual, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed in ITAE, overshoot and rising time to show applicability and superiority with simulation results.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.97-104
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• 1993

This paper deals with the design problem of a man-on-board(MOB) storage and retrieval warehousing system which is suitable for storing items of small size and light weight. It is assumed that the operator carries out a sequence of retrieving(or storing) operations traveling on a specially designed truck. Considering the operating characteristics of the man-on-board system, an optimal design model is developed in which the investment and maintenance costs of the system are minimized over a time horizon satisfying a set of constructional restrictions. The model is formulated as a nonlinear integer program and a search algorithm is proposed to find an optimum solution.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1195-1198
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• 1993

We investigate a systematic design procedure of automated rule generation of fuzzy logic based controller for uncertain dynamic systems such as an engine dynamic model.“Automated Tuning”means autonomous clustering or collection of such meaningful transitional relations in the state-space. Optimal control strategies are included in the design procedures, such as minimum squared error, minimum time, minimum energy or combined performance criteria. Fuzzy feedback control systems designed by the cell-state transition method have the properties of closed-loop stability, robustness under parameter variabtions, and a certain degree of optimality. Most of all, the main advantage of the proposed approach is that reliability can be potentially increased even if a large grain of uncertainty is involved within the control system under consideration. A numerical example is shown in which we apply our strategic fuzzy controller design to a highly nonlinear model of engine idle speed contr l.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.405-410
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• 1994

The purpose of this paper is to present the details of design procedure of a nonlinear regulator by Riemannian geometric approach and to applied it to the case of a double-effect evaporator. A nonlinear geometric model is proposed on a direct sum space of a state vector and a control vector as well as in the previous parers by the authors. The geometric model is derived by replacing the orthogonal straight coordinate axes of a linear system on the direct sum space with the curvilinear coordinate axes. The integral manifold of the geometric model becomes homeomorphic to that of fictitious linear system. For the geometric model a nonlinear regulator with a performance index is designed renewedly by the procedure of optimization. The construction method of the curvilinear coordinate axes on which the nonlinear system behaves as a linear system is discussed. To apply the above regulator theory to double-effect evaporators especially to the pilot plant at the University of Alberta, a suitable nonlinear model is determined by the plant dynamics. The optimal control law is derived through the calculation of the homeomorphism. As a result it is confirmed that the regulator is effective and superior to that of the conventional control.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.528-530
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• 1999

This paper addresses the analysis and design of fuzzy control systems for a class of complex single input single output nonlinear systems. Firstly, the nonlinear system is represented by well-known Takagai-Sugeno (TS) fuzzy model and the global controller is constructed by compensating each linear model in the rule of TS fuzzy model. The design of conventional TS fuzzy-model-based controller usually is composed of two processes. One is to determine static state feedback gain of each local model and the other is to validate the stability of the designed fuzzy controller. In this paper, we propose an alternative of the design of TS fuzzy-model-based controller. The design scheme is based on the extension of conventional optimal control theory to the design of TS fuzzy-model-based controller. By using the proposed method the design and stability analysis of the TS fuzzy model-based controller is reduced to the problem of finding the solution of a set of algebraic Riccati equations. And we use the recently developed interior point method to find the solution of AREs, where AREs are recast as the LMI formulation. One simulation example is given to show the effectiveness and feasibility of the proposed fuzzy controller design method.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.93-102
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• 2015

The D-optimal design for the nonlinear model typically depends on the unknown parameters to be estimated. Therefore, it is strongly recommended in literature to use a sequential experimental design for estimating the parameters. In this paper two stage experimental design is discussed under many different circumstances including estimating parameters. The method is so universal to be applied to any mixture of objectives for any model including linear model. A hybrid approach is suggested to handle more than 2 objectives in two-stage experimental design. The design is discussed in approximate design framework.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.221-230
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• 2001

The assembly tolerance design methods have applied linear or nonlinear programming methods and used simulation method and search algorithms to optimize the tolerance allocation of each part in an assembly. However, those methods are only considered to the relationship between tolerance and manufacturing cost, which do not consider a quality loss cost for each part tolerance. In this paper, the integrated simulation model used genetic algorithm and the Monte-Carlo simulation method was developed for the allocation of the optimal tolerance considering the manufacturing cost and quality loss cost.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.1-23
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• 2005

The decentralized static output feedback design problem is considered. A constrained trust region method is developed that solves this optimal control problem when a complete set of state variables is not available. The considered problem is interpreted as a non-linear (non-convex) constrained matrix optimization problem. Then, a decentralized constrained trust region method is developed for this problem class exploiting the diagonal structure of the problem and using inexact computations. Finally, numerical results are given for the proposed method.

• 전기의세계
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• v.29 no.3
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• pp.179-184
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• 1980

This paper presents in some detail a discussion of the design of the digital control system without nonlinear elements to exhibit deadbeat performance in response to step inputs. The transfer function of digital dontroller is obtained by calculating the sequence of inputs and outputs of the digital controller for deadbeat performance. Digital controllers are designed for unity feedback multivariable systems by this method, which is well adapted for obtaining a solution by a digital computer.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.101-104
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• 1990

The program which could determine cross-sectional dimensions of the box girder bridge at tile stage of preliminary design was developed using the optimal technique in this study. It could minimize the cost and time required in the design of box girder bridges and the construction with the prestressed precast segmental method. Objective cost function consisted of four independent variables such as widths and depth of the cross-section. The Nelder-Mead method was used to solve the nonconstrained nonlinear problem like this.