• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.11-16
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• 2014

In this paper, the two-wheels robot using a predictive controller to maintain the balance of the posture control in real time have been examined. A reaction wheel pendulum control method is adopted to maintain the balance while the bicycle robot is driving. The objective of this research was to design and implement a self-balancing algorithm using the dsPIC30F4013 embedded processor. To calculate the attitude in ARS using 2 axis gyro(roll, pitch) and 3 axis accelerometers (x, y, z). In this study, the disturbance of the posture for the asymmetrical propose to overcome the predictive controller which was a problem in the control of a remote system by introducing the two wheels of the robot controller and the linear prediction of the system controller combines the simulation was performed. Also, the robust characteristic for realizing the goal of designing a loop filter too robust controller is designed so that satisfactory stability of the control system to improve stability of the system to minimize degradation of performance was confirmed.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.2
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• pp.196-203
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• 2005

In this paper, a digital controller for satisfying time response requirements for UPS inverters is designed in a fixed sampling time. The CRA (Characteristic Ratio Assignment) is used as the continuous time design method to deal with the problems of overshoot and settling time. The main design approaches are the inward and outward approaches based on a double-loop feedback structure. The continuous-time controller is discretized by the emulation method. The performances of the proposed controller are evaluated through several simulations carried out with Simpower System Toolbox 3.0 from Simulink$^{(R)}.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.166.3-166
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• 2001

This paper presents a modeling and control method of active suspension system with full-car model by using H$\infty$ control theory. The full-car model has seven degree of freedom including heaving, pitching and rolling motions. As the control method, H$\infty$ controller is designed so as to guarantee the robustness of closed loop system under the presence of uncertainties and disturbances. Active system with H$\infty$ controller can reduce the accelerations of the car-body in the heaving, pitching and rolling directions. The effectiveness of the controller is proved through simulation results in both time and frequency domains.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.6
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• pp.1399-1411
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• 1994

A model helicopter has more versatile flight capability than the fixed-wing aircraft and it can be used as an unmaned vehicle in hazardous area. A helicopter, similar to other aircrafts, is an unstable, multi-input multi-output nonlinear system exposed to strong disturbance. So it should be controlled by robust control theories that can be applied to multivariable systems. In this study, motion equations of hovering are established, linearized and transformed into a state equation form. Various parameters are measured and calculated in other to obtain the stability derivatives in the state equation. Hovering flight controller is designed using the digital LQG/LTR(Linear Quadratic Gaussian/Loop Transfer Recovery) control theory. The designed controller is tested by the nonlinear simulations and implemented on an IBM-PC/386. Experiments were carried out on a model helicopter attached to the 3-DOF gimbal. The designed controller showed satisfactory hovering capability to maintain the hovering for more than 40 seconds.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.248-255
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• 2000

Whereas the linear PID controller is widely used for control of industrial servo systems a high precision positioning system is not easy to control only with the PID controller due to uncertain nonlinear dynamics such as friction backlash etc. As a viable means to overcome the difficulty a learning control scheme is proposed in this paper that is simple and straightforward to implement. The proposed learning controller takes full advantage of current feedback capability of the inner-loop of the control system in that electrical motor dynamics as the well as mechanical part of X-Y positioning system is included in the learning control scheme, The experimental results are given to demonstrate its feasibility and effectiveness in terms of convergence precision of tracking and robustness in comparison with the conventional control method.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.218-228
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• 2001

The switched reluctance motor(SRM) has been increasingly used in high-performance servo applications such as electric vehicles, aircraft, and direct-drive robots. The dynamic equations of SRMs are, however, highly nonlinear and this makes it difficult to control SRMs with high performance. In this paper, we propose a new robust current tracking controller for SAMs which can compensate the nonlinear characteristics of SRM(i.e., back-emf and inductance) completely and hence shows perfect tracking performance even with an arbitrary small current control loop gain. Furthermore, even in case that there exist some model uncertainties, our current controller guarantees that the stator currents can track the reference current commands with sufficiently small tracking errors. In order to justify our work, we present the tracking performance analysis and some simulation results.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.1004-1013
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• 1999

This paper considers the transient stability problem of power system. The power system model is given as interconnected system consisting of many machines which are described by swing equations. We design a transient stability controller using passivity and neural network. The structure of the neural network controller is derived using a filtered error/passivity approach. In general, a neural network cannot be guaranteed to be passive, but the weight tuning algorithm given here do guarantee desirable passivity properties of the neural network and hence of the closed-loop error system. Moreover proposed controller shows good robustness by simulation for uncertainties in parameters, which can not be shown in the speed gradient method proposed by Fradkov[3,7].

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.67-73
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• 2002

This paper presents a new design method of optimal continuous deadbeat controller by using second-order smoothing elements. The continuous deadbeat controller is made of a serial integral compensator and a local feedback compensator introduced into the state feedback loop. The decision method of the damping factor and the natural angular frequency of the smoothing element is described. A numerical example is given to show how well input-output characteristics are improved. Especially according to the variable input and disturbance, corresponding CDBC design method is suggested. By computer simulations, control inputs and system outputs are shown to have desirable property such as smoothness.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.41.3-41
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• 2001

In this paper, we present a decentralized adaptive neural net(NN) controller for the transient stability and voltage regulation of a multimachine power system. First, an adaptively input-output linearizing controller using NN is designed to eliminate the nonlinearities and interactions between generators. Then, a robust control term which bounds terminal voltage to a neighborhood of the operating point within the desired value is introduced using only local information. In addition, we consider input saturation which exists in the SCR amplifier and prove that the stability of the overall closed-loop system is maintained regardless of the input saturation. The design procedure is tested on a two machine infinite bus power system.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.2
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• pp.100-105
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• 2011

By adopting HIL(Hardware-in-the-Loop), component characteristics in vehicle environment can be obtained without implementing component in the vehicle. In this paper, when specific motor is adopted as traction motor in hybrid electric vehicle HIL implementation procedures are explained. In order to implement HIL method motor testing. vehicle performance simulator and load characteristic are explained. Vehicle controller used in simulator is directly uploaded in real controller. Especially as a load dynamometer actively controlled motor system is used without connecting conventional mechanical inertia. Motor characteristics are obtained using HIL implementation when test motor is used as a traction motor for parallel hybrid electric vehicle. Proposed method can be used as experimental equipment to educate driving characteristics of hybrid electric vehicle.