• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.785-789
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• 2001

Piezoelectric actuators are characterized by non-linear dynamics and high frequency oscillations of the piezocrystal. Both properties have to be taken into consideration when optimizing real time systems. Taking benefit of the almost linear behaviour between charge and strain, current source fed piezoelectric actuators are given preference for high dynamic applications. Here special emphasis is put on current sources for multi-actuator systems and the controller design for optimal system integration of the actuator. It is shown that sliding mode operation of the converter system offers good possibilities to guaranty high accuracy and dynamics of the actuators system. The presented multi-actuator system is used for positioning and vibration damping in flexible mechanical systems.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.236-242
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• 1992

Multi-layered neural networks are applied to the identification and control of nonlinear dynamical system. Traditional adaptive control techniques can only deal with linear systems or some special nonlinear systems. A scheme for combining multi-layered neural networks with model reference network techniques has the capability to learn the nonlinearity and shows the great potential for adaptive control. In many interesting cases the system can be described by a nonlinear model in which the control input appears linearly. In this paper the identification of linear and nonlinear part are performed simultaneously. The projection algorithm and the new estimation method which uses the delta rule of neural network are compared throughout the simulation. The simulation results show that the identification and adaptive control schemes suggested are practically feasible and effective.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.3
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• pp.179-202
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• 2019

This paper presents second derivative generalized extended backward differentiation formulas (SDGEBDFs) based on the second derivative linear multi-step formulas of Cash [1]. This class of second derivative linear multistep formulas is implemented as boundary value methods on stiff problems. The order, error constant and the linear stability properties of the new methods are discussed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.332-339
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• 2014

Face classification has wide applications in security and surveillance. However, this technique presents various challenges caused by pose, illumination, and expression changes. Face recognition with long-distance images involves additional challenges, owing to focusing problems and motion blurring. Multiple frames under varying spatial or temporal settings can acquire additional information, which can be used to achieve improved classification performance. This study investigates the effectiveness of multi-frame decision-level fusion with photon-counting linear discriminant analysis. Multiple frames generate multiple scores for each class. The fusion process comprises three stages: score normalization, score validation, and score combination. Candidate scores are selected during the score validation process, after the scores are normalized. The score validation process removes bad scores that can degrade the final output. The selected candidate scores are combined using one of the following fusion rules: maximum, averaging, and majority voting. Degraded facial images are employed to demonstrate the robustness of multi-frame decision-level fusion in harsh environments. Out-of-focus and motion blurring point-spread functions are applied to the test images, to simulate long-distance acquisition. Experimental results with three facial data sets indicate the efficiency of the proposed decision-level fusion scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.401-406
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• 2012

This paper considers multi-agent systems with interval time-varying delays and switching interconnection topology. By construction of a suitable Lyapunov-Krasovskii's functional, new delay-dependent consensus control conditions for the systems are established in terms of LMIs (Linear Matrix Inequalities) which can be easily solved by various effective optimization algorithms. One numerical example is given to illustrate the effectiveness of the proposed methods.

• Industrial Engineering and Management Systems
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• v.13 no.3
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• pp.319-329
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• 2014

Supply chain management is a subject that has an increasing importance due to the developments in the global markets and technology. In this paper, a fuzzy multi-objective linear programming model is developed for the supply chain of a company dealing with procurement, storage, filling, and distribution of liquefied petroleum gas (LPG) in Turkey. The model intends to determine the quantities of LPG to be procured, stored, filled to cylinders, and transported between the plants and demand centers for six planning periods. In this model, which aims to minimize both total costs (sum of procurement, storage, filling, and transportation costs) and total transportation distances, demand quantities of the main demand centers and decision maker's aspiration levels about objective functions are fuzzy. After comparing the results obtained from the model with those obtained by using different methods, it is concluded that the proposed method can be applied to real world problems practically and it may be used in this type of problems in order to generate an efficient solution.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.519-526
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• 2006

This paper compares the seismic response control performance of linear and non-linear models fer tuned liquid damper (TLD). The existing linear and nonlinear TLD models were used for the numerical analysis of single degree of freedom (SDOF) and multi degree of freedom (MDOF) systems with TLD. The nonlinear model considers the variation of the frequency and damping of the TLD with varying excitation amplitude while the linear one has the invariant parameters. Numerical analysis results from SDOF systems indicate that the nonlinear model shows about 5% better control performance than linear one when the mass ratio is 2% and the optimal parameters for reducing peak responses are dependent on the characteristics of the excitation earthquake loads.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.526-532
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• 2014

In this paper, we present and analyze a LQ (Linear Quadratic) inverse optimal state-consensus protocol for continuous-time multi-agent systems with undirected graph topology. By Lyapunov analysis of the state-consensus error dynamics, we show the sufficient conditions on the algebraic connectivity of the graph to guarantee LQ inverse optimality and closed-loop stability. A more relaxed stability condition is also provided in terms of the algebraic connectivity. Finally, a formation control protocol for multiple mobile robots is proposed based on the target LQ inverse optimal consensus protocol, and the simulation results are provided to verify the performance of the proposed LQ inverse formation control method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.222-226
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• 2010

In this paper we study the consensus problem of SISO (Single-Input Single-Output) linear multi-agent systems under a fixed weighted undirected network communication. The dynamics of each agent can be of any order, while it is constrained to be neutrally stable. Based on a simple root locus argument, we show that the problem at hand is always solvable if the gain and zeros of the dynamic compensator, of which dimension is the same as the number of plant poles on the imaginary axis, are chosen suitably, finally the result is successfully verified by an example.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.307-310
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• 2003

In the maritime container terminal, LMTT(Linear Motor-based Transfer Technology) is horizontal transfer system for the yard automation, which has been proposed to take the place of AGV(Automated Guided Vehicle). The system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) that is consists of stator modules on the rail and shuttle car (mover). Because of large variant of mover's weight by loading and unloading containers, the difference of each characteristic of stator modules, and a stator module's trouble etc., LMCPS (Linear Motor Conveyance Positioning System) is considered as that the system is changed its model suddenly and variously. In this paper, we will introduce the soft-computing method of a multi-step prediction control for LMCPS using DR-FNN (Dynamically-constructed Recurrent Fuzzy Neural Network). The proposed control system is used two networks for multi-step prediction. Consequently, the system has an ability to adapt for external disturbance, cogging force, force ripple, and sudden changes of itself.