• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2687-2689
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• 2000

In many cases the systems are so complex that it is not possible to obtain reasonable models using physical insight. Also a model based on physical insight contains a number of unknown parameters even if the structure is derived from physical laws. These problems can be solved by system identification. In this paper, Arago's disk system which has both stable and unstable regions is selected as an example for identification and a state-space model is identified using tailor-made model structure of this system. In stable region, a state-space model of Arago's disk system is identified through open loop experiment and a state-space model of unstable region is identified through closed loop experiment after using fuzzy controller to stabilize unstable system.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.852-854
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• 1995

This paper proposes a new identification method that utilizes fuzzy inference in parameter identification. The prosed system has an additional control loop where a real plant has replaced by a plant model. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. In this paper, the tuning method which determines parameters of PID controller automatically is described through applying this algorithm to DC servo motor. And we intend to investigate effectiveness of the method by experiments. This method is effective in auto-tuning because the response of the closed loop has verified. The simulated and the experimental results of the dc servo motor are shown to confirm the viability of this method.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.203-208
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• 1998

This paper presents an adaptive fuzzy controller using an neural network and adaptation algorithm. Reference-model following neuro-fuzzy controller(RMFNFC) is invesgated in order to overcome the difficulty of rule selecting and defects of the membership function in the general fuzzy logic controller(FLC). RMFNFC is developed to tune various parameter of the fuzzy controller which is used for the discrete nonlinear system control. RMFNFC is trained with the identification information and control closed loop error. A closed loop error is used for design criteria of a fuzzy controller which characterizes and quantize the control performance required in the overall control system. A control system is trained up the controller with the variation of the system obtained from the identifier and closed loop error. Numerical examples are presented to control of the discrete nonlinear system. Simulation results show the effectiveness of the proposed controller.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.35 no.4
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• pp.48-56
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• 2003

In this work an integrated model for paper plants combining wet-end and dry section is developed and a model predictive control scheme based on the plant model is proposed. Closed-loop process identification method is employed to produce a state-space model. Thick stock, filler flow, machine speed and steam pressure are selected as input variables and basis weight, ash content and moisture content are considered as output variables. The desired output trajectory is constructed in the form of 1st-order dynamics. Results of simulations for control of grade change operations are compared with plant operation data collected during the grade change operations under the same conditions as in simulations. From the comparison, we can see that the proposed model predictive control scheme reduces the grade change time and achieves stable steady-state.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.6
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• pp.403-410
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• 2008

This paper suggests a standstill estimator to accurately identify induction motor (IM) parameters necessary for the vector control. A mathematical model that faithfully represents the general skin effect is introduced. Then, two exciting signals with a different frequency are sequentially injected to track the parameters based on the skin effect of the rotor bar. Little knowledge of the unknown motor allows the proposed methodology to employ a closed-loop control of an injected current, rather than open-loop voltage injection approaches. Subsequently, this control scheme proactively prevents electrical accidents resulting from an inadequate open-loop voltage injection. We develop a specialized offline commissioning test to compensate the phase delay resulting from the drive, which significantly affects the precision of the IM parameters. The effectiveness of the identification technique is validated by means of experiments performed on the three different IMs.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.157-160
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• 1996

Physical systems axe generally continuous-time in nature. However as the data measured from these systems is generally in the form of discrete samples, and most modern signal processing is performed in the discrete-time domain, discrete-time models are employed. This paper describes methods for estimating the coefficients of continuous-time system within a closed loop control system. The method employs a recursive estimation algorithm to identify the coefficients of a discrete-time bilinear-operator model. The coefficients of the discrete-time bilinear-operator model closely approximate those of the corresponding continuous-time Laplace transform transfer function.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2003.11a
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• pp.291-305
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• 2003

In this work we developed the closed-loop model of a paper machine during grade change with the intention to provide a reliable dynamic model to be used in the model-based grade change control scheme. During the grade change, chemical and physical characteristics of paper process change with time. It is very difficult to represent these characteristics on-line by using physical process models. In this work, the wet circulation part and the drying section were considered as a single process and closed-loop identification technique was used to develop the grade change model. Comparison of the results of numerical simulations with plant operation data demonstrates the effectiveness of the model identified.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.1-4
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• 1995

We propose a new design method for a generalized predictive control (GPC) system based on the parametrization of two-degree-of freedom control systems. The objective is to design the GPC system which guarantees the stability of the control system for a perturbed plant. The design procedure of our proposed method consists of three steps. First, we design a basic controller for a nominal plant using the LQG method and parametrize a whole control system. Next, we identify the deviation between the perturbed plant and the nominal one using a closed-loop identification method and design a free parameter of parametrization to stabilize the closed-loop system. Finally, we design a feedforward controller so as to incorporate GPC technique into our controller structure. A numerical example is presented to show the effectiveness of our proposed method.

• Journal of Power System Engineering
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• v.5 no.4
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• pp.53-60
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• 2001

This paper considers a modeling for the MIMO magnetic bearing system. The rotor is flexible and has a complex shape. To obtain the nominal plant transfer functions, we perform a numerical analysis by using the finite element method(F.E.M.) for the rotor's dynamics, and make a nominal model by reducing the modes from the results. And, we have experimented on the frequency response by a closed-loop identification method, and compared it with the simulation's result on the closed-loop control system.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.318-322
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• 1998

An Electro Magnetic Suspension System, which has two floating masses connected with springs and dampers, can not keep its equilibrium when it is solved as an ordinary quartic mathematical model. So, a two dimensional con-troller, designed with quadratic mathematical model assuming the two mass model to be a rigid body, was used. As the result, the system floated stably. Therefore, we measured the transfer performances of this closed loop system contained this controller using the compression signal method proposed by N.Aoshima and identified the parameters of this system. Finally, we compared these parameters with the computing results of quartic mathematical model.