• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.61-64
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• 1986

The Fourier Spectral Analysis has been widely utilized in the analysis of linear dynamic systems. However, it may not be generaly extended to analyze nonlinear systems. In this paper, a linear underlying dynamic structure coupled with nonlinear elements is analyzed by using newly derived equations of motion after the linear dynamic structure is characterized by the Fourier spectral analysis.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.56-69
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• 2005

In this paper, it is clearly shown that the two well-known necessary and sufficient conditions mp n as generic static output feedback pole-assignment and mp + d(m+p) n+d as generic minimum d-th order dynamic output feedback pole-assignment on complex field, unbelievably, do not match up each other in strictly proper linear systems. For the analysis, a diagram analysis is newly created (which is defined by the analysis of 'convoluted rectangular/dot diagrams' constructed via node-branch conversion of the signal flow graphs of output feedback gain loops). Under this diagram analysis, it is proved that the minimum d-th order dynamic output feedback compensator for pole-assignment in m-input, p-output, n-th order systems is quantitatively decomposed into static output feedback compensator and its associated d number of arbitrary 1st order dynamic elements in augmented (m+d)-input, (p+d)-output, (n+d)-th order systems. Total configuration of the mismatched data is presented in a Table.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.115-120
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• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.

• Bulletin of the Korean Mathematical Society
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• v.51 no.4
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• pp.1075-1085
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• 2014

In this paper we investigate asymptotic properties about asymptotic equilibrium and asymptotic equivalence for linear dynamic systems on time scales by using the notion of $u_{\infty}$-similarity. Also, we give some examples to illustrate our results.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.26.4-26
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• 2001

This paper proposes a dynamic observer that is applicable to linear time-invariant systems subject to unknown inputs. The proposed method utilizes the output feedback control structure to design an unknown input observer. We name it as the dynamic unknown input observer(UIO). The dynamic UIO can be designed easily compared to the usual static UIO, and the system response could be improved.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.162-165
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• 1995

For an accurate on-line measurement of the ship's attitude the paper develops an intelligent sensing system which uses one servo-type accelerometer and two servo-type inclinometers appropriately located on the ship. By considering the dynamics of the servo-controlled rigid pendulums of the inclinometers, linear equations for the rolling and pitching of the ship are derived separately from each other. Moreover, one accelerometer is used for extracting the heaving signal. Through the introduction of linear dynamic models and the linear observation equations for the heaving, rolling and pitching, the on-line measurement of the three signals can be reduced to the state estimation of the linear dynamic systems. A bank of Kalman filters is adaptively used to achieve the on-line accurate state estimation and to overcome changes in parameters in the linear dynamic models.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.362-367
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• 1996

In this paper, the eigenstructure of a class of linear time varying systems, termed as linear quasi-time invariant(LQTI) systems, is investigated. A system composed of dynamic devices such as linear time varying capacitors and resistors can be an example of the class. To effectively describe and analyze the LQTI systems, a generalized differential operator G is introduced. Then the dynamic systems described by the operator G are studied in terms of eigenvalue, frequency characteristics, stability and an extended convolution. Some basic attributes of the operator G are compared with those of the differential operator D. Also the corresponding generalized Laplace transform pair is defined and relevant properties are derived for frequency domain analysis of the systems under consideration. As an application example, a LQTI circuit is examined by using the concept of eigenstructure of LQTI system. The LQTI filter processes the sinusoidal signals modulated by some functions.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.4
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• pp.394-397
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• 2014

This paper deals with the comparison and dynamic behavior of a moving-coil linear oscillatory actuator (MCLOA) with/without a mechanical spring. On the basis of a dynamic simulation model, the dynamic characteristics such as a current and a stroke of the MCLOA without the spring are predicted for various values of frequency. And then, dynamic test results are given to confirm the dynamic simulations. Finally, this paper describes the influence of the spring on the dynamic behavior of the MCLOA from the dynamic experiments of the MCLOA with/without the spring.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.199-199
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• 2000

Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control have been applied to control design for uncertain LTI systems which are the approximation of LTV systems have been generally used instead. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification against plant parameter uncertainties in frozen time sense. However, if these methods are applied to the approximated linear time-invariant(LTI) plants which have large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks for LTV systems with bounded time-varying parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.342-348
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• 2015

This paper presents a two-wheel balancing mobile robot with linear workspace extension structures. The two-wheel mobile robot has two linear motions at the waist and shoulder to have extended workspace. The linear motion of the waist and shoulder provides some structural advantages. A dynamic equation of the simplified robot system is derived. Simulation studies of the position control of the robot system are performed based on the dynamic equations. The dynamic relationship between a two-wheel mobile system and linear extension mechanism is observed by simulation studies.