• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.19-33
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• 2015

Recently, interest in research and development (R&D) investment decisions have increased among Korean domestic enterprises. However, existing R&D investment studies only focused on government R&D investment policies while only a few studies investigated firm level R&D investment. Prior literatures also overlooked the feedback loop between R&D investment and firm performance. Therefore, this paper identifies a system dynamics model for R&D investment decision making in domestic electronics firms. The conceptual model is derived from R&D investment-related theories found in bodies of literature on company performance, enterprise activity, and market maturity. This study investigates the dynamic feedback between R&D activities and sales using the system dynamics model. In other words, the system dynamics model is used to explain the change in the closed feedback circulation structure in R&D investment activities including technology development, production process, and marketing that subsequently result in sales increase and re-investment into R&D from the generated revenues. There are two major results. First, a similar ratio of investment on technology development and production process derives the higher company sales. Second, regardless of market maturity, marketing investment ratio positively affects sales and R&D budget growth. This study provides a system dynamics model to find the optimal ratio for R&D investment and suggests managerial strategic implications on electronic firm R&D investment decision making under market maturity condition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1397-1404
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• 2015

Recently, high data rate transmission is required in maritime communication. In this paper, we consider multiple input multiple output (MIMO) spatial multiplexing (SM). However, the performance of SM is severly degraded due to spatial channel correlation and line-of-sight (LOS) component. In the maritime communication, the MIMO channel correlation and LOS are critical due to the lack of scatteres around the transmitter and/or the receiver. When the feedback of channel information is available, precoding can enhance the error performance by exploiting the channel information. However, it is difficult to derive closed-form solution considering both the correlation and LOS. In this paper, we present open-loop precoding-based spatial multiplexing transmission method by showing that the effect of performance for the correlation and LOS. It is shown that the open-loop precoding can mitigate the performance degradation due to the LOS as well as the correlation. Consequently, we expect that the proposed open-loop precoding can be adopted to the maritime communication system.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.1
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• pp.92-101
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• 2010

Recently, the magnetic bearings which have many advantages such as no noise, less mechanical friction are widely applied to the suspension of rotors on the rotary machineries. However, the magnetic bearing system is inherently unstable, nonlinear and MIMO(multi-input-multi-output) system as well. In this paper, we design a state feedback controller using linear matrix inequality(LMI) to the multi-objective synthesis, for the magnetic bearing system with integral type servo system. The design objectives include $H_{\infty}$ performance, asymptotic disturbance rejection, and time-domain constraints on the closed-loop pole location. The results of computer simulation show the validity of the designed controller.

• Journal of Ocean Engineering and Technology
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• v.17 no.5 s.54
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• pp.57-65
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• 2003

This paper proposes an optimum design method of structural and control systems, using a 2-D truss structure as an example. The structure is subjected to initial static loads and disturbances. For the structure, a FEM model is formed. Using modal transformation, the equation of motion is transformed into modal coordinates, in order to decrease D.O.F. of the FEM model. To suppress the effect of the disturbances, the structure is controlled by an output feedback $H_{\infty}$ controller. The design variables of the combined optimal design of the control-structure systems are the cross sectional areas of truss members. The structural objective function is the structural weight. The control objective function is the $H_{\infty}$ norm, the performance index of control. The second structural objective function is the energy of the response related to the initial state, which is derived from the time integration of the quadratic form of the state in the closed-loop system. In a numerical example, simulations have been perform. Through the consideration of structural weight and $H_{\infty}$ norm, an advantage of the combined optimum design of structural and control systems is shown. Moreover, since the performance index of control is almost nearly optimiz, we can acquire better design of structural strength.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.47-54
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• 1998

Underwater robotic vehicles(URVs) have been an important tool for various underwater tasks such as pipe-lining, data collection, hydrography mapping, construction, maintenance and repairing of undersea equipment, etc because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system is one of the most critical subsystems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. It is desirable to have an intelligent vehicle control system because the fixed-parameter linear controller such as PID may not be able to handle these changes promptly and result in poor performance. In this paper we described and analyzed a new type of fuzzy model-based controller which is designed for underwater robotic vehicles and based on Takagi-Sugeno-Kang(TSK) fuzzy model. The proposed fuzzy controller: 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule; 2) can guarantee the stability of the closed-loop fuzzy system; 3) is relatively easy to implement. Its good performance as well as its robustness to parameter changes will be shown and compared with those of the PID controller by simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1045-1053
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• 2009

Precision stages for 6-DOF positioning, actuated by PZT stacks, which are fed back by gap sensors and guided by flexure hinges, have enlarged their application territory in micro/nano manufacturing and measurement area. The precision stages inherently have such limitations as the nonlinearity between input and output in piezoelectric stacks, feedback signal noise in precision capacitive gap sensors and low material damping in precision kinematic linkages of mechanical flexures. To surmount these limitations, the precision stage is modeled with physics-based variables, which are identified by transient response correspondence, and a gain margin calculation algorithm using the Prandtl-Ishlinskii model and describing function is newly developed to assess system performance more precisely than linear controller design schemes. Based on such analyses, a precision positioning controller is designed. Excellent positioning accuracy with rapid settlement accomplished by the controller is shown in step responses of the closed-loop system.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1109-1114
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• 2007

This paper presents the road simulator control technology for reproducing the road input signal to implement the real road data. The simulator consists of the hydraulic pump, servo valve, hydraulic actuator and its control equipment. The QFT is utilized to control the simulator effectively. The control system illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) for a parametric uncertain model. A force controller is designed to communicate the control signal between simulator and digital controller. The efficacy of the QFT force controller is verified through the numerical simulation, in which combined dynamics and actuation of the hydraulic servo system are tested. The simulation results show that the proposed control technique works well under uncertain hydraulic plant system. The conventional software (Labview) is used to make up for the real controller in the real-time basis, and the experimental works show that the proposed algorithm works well for a single road simulator.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.4
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• pp.24-33
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• 2004

In this paper, the helicopter flight control system using online adaptive neural networks which have the universal function approximation property is considered. It is not compensation for modeling errors but approximation two functions required for feedback linearization control action from input/output of the system. To guarantee the tracking performance and the stability of the closed loop system replaced two nonlinear functions by two neural networks, weight update laws are provided by Lyapunov function and the simulation results in low speed flight mode verified the performance of the control system with the neural networks.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.731-736
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• 1994

Experiment on a lab-scale pH process is carried out to evaluate the control performance of the neural linearizing control scheme(NLCS) using a radial basis function(RBF) network which was previously proposed by Kim and Park. NLCS was developed to overcome the difficulties of the conventional neural controllers which occur when they are applied to chemical processes. Since NLCS is applicable for the processes which are already controlled by a linear controller and of which the past operating data are enough, we first control the pH process with PI controller. Using the operating data with PI controller, the linear reference model is determined by optimization. Then, a IMC controller replaces the PI controller as a feedback controller. NLCS consists of the IMC controller and a RBF network. After the learning of the neural network is fully achieved, the dynamics of the process combined with the neural network becomes linear and close to that of the linear reference model and the control performance of the linear control improves. During the training, NLCS maintains the stability and the control performance of the closed loop system. Experimental results show that the NLCS performs better than PI controller and IMC for both the servo and the regulator problems.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.639-648
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• 2002

The stewart platform manipulator is a manipulator that has the closed-loop structure with an upper plate end-effector and a base frame. The stewart platform manipulator has the merit of high working accuracy and high stiffness compared with a serial manipulator. However, this is a complex structure, so controllability of the system is not so good. In this paper, we introduce a new robust motion control algorithm using partial state feedback for a class of nonlinear systems in the presence of modelling uncertainties and external disturbances. The major contribution of this work introduces the development and design of robust observer for the state and the perturbation, which is integrated into a variable structure controller(VSC) structure. The combination of controller/observer improves the control performance, because of the robust routine called sliding mode control with sliding perturbation observer(SMCSPO). Simulation and experiment are performed to apply to the manipulator. And their results show a high accuracy and a good performance.