• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.9
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• pp.1040-1049
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• 1992

When the model of control object is not described correctly, ambiguity is often expressed by unknown parameter, In a case that this ambiguity satisfies a certain condition of limit, if robust control method is used, even if model is not correctly discribed, control system can be composed. The characteristic of control based on the variable structure theory is that the influence by ambiguity of system eradicates high-gain feedback. Therefore in this paper, VSS indentifier is proposed. Transformation of control input producing control system in sliding mode actually reflects influence of ambiguity unknown parameter of control object. If useful information is out from transformation input by a few times of operation, proper identify mechanism is selected and this information is used, to decide the unknown parameter is possible. So more effective controller was composed by addition of the proposed identifier to the unknown parameter identifier of robot manipulator.

• 한국기계연구소 소보
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• s.18
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• pp.125-129
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• 1988

This paper proposes a sensitivity technique for analysis of the relationships between input variables (known values) and output variables(unknown values), These design variables are constrained by design equations. Thus, the output variables can be calculated by solving the equations with eliminating the input variables from the equations because the input variables become constants. If the output variables are not satisfied, the values of the input variables must be adjusted by increasing or decreasing the values and then the problem must be solved again. This is called as the iterative design procedure. The sensitivity technique, presented in this paper, gives the sensitivity on the changes of the values of the output variables to the input variables.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.10
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• pp.2067-2072
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• 2002

The closed-loop state and input observer is a pole-placement type observer and estimates unknown state and input variables simultaneously. Pole-placement type observers may have poor performances with respect to modeling error and sensing bias error. The effects of these ill-conditioning factors must be minimized for the robust performance in designing observers. In this paper, the steady-state performance of the closed-loop state and input observer is investigated quantitatively and is represented as the estimation error bounds. The performance indices are selected from these error bounds and are related to the robustness with respect to modeling errors and sensing bias. By considering both transient and steady-state performance, the main performance index is determined as the condition number of the eigenvector matrix based on $L_2$-norm.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.53.6-53
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• 2001

In this paper, we are concerned with a tracking filter algorithm which can track a maneuvering target. Among the novel tracking filter algorithms, the input estimation (IE) filter can be summarized as estimating the unknown maneuver input and compensating the state according to the estimated input, and the variable dimension filter (VDF) can be summarized as detecting the maneuver of target and changing the dimension of the target dynamics to accomodate the maneuver of target They have some goods and bads with respect to each other. The variable dimension filter with input estimation (VDIEF) is constructed by combining the two filtering algorithms. However, it requires too much computational burden while it has good performance. We propose another variable dimension with input estimation ...

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.310-314
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• 2008

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. This novel method uses the support vector machines (SVM) with its function approximation property. It works together with RLS (Recursive least-squares) algorithm. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.703-705
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• 2000

In this paper, we design a robust adaptive controller for a nonlinear systems with uncertainties to be rejected via disturbance adaptation law. The nonlinear system considered in this paper has unknown nonlinear functions being influenced by external disturbance. The upper bounds of unknown nonlinear functions at each time is estimated by using disturbance adaptation law. The estimated nonlinear functions are used to design stabilizing function and control of input. Tuning function is used to estimate unknown system parameter without overparametrization. A set-point regulation error converges to a residual set close to zero asymptotically fast.

• 전기의세계
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• v.22 no.4
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• pp.17-24
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• 1973

In the view point of practical engineering the identification problem may be considered as a problem to determine the optimal model in the sense of minimizing a given criterion function using the input-output records of the plant. In the system identification the statistical approach has been known to be very effective when the topological structure of the system and the statistical characteristics of the observation noises are known a priori. But in the practical situation there are many cases when the inforhation about the observation noises or the system noises are not available a priori. Here, the authors propose a new identification method which can be used effectively even in the cases when the variances of observation noises are unknown a priori. In the method, the identification of unknown parameters of a linear diserete system is achieved by minimizing the improved quadratic criterion function which is composed of the term of square equation errors and the term to eliminate the affection of observation noises. The method also gives the estimate of noise variance. Numerical computations for several examples show that the proposed procedure gives satisfactory results even when the short time observation data are provided.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.371-373
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• 1992

This note proposes a novel robust adaptive control algorithm for systems with unknown disturbances by introducing an additional term in the control input. This additional term is easily implementable by estimating the upper bound of the unknown disturbances. By this term, the output error can be made to be uniformly ultimately bounded in a desired region via Lyapunov second stability theorem when the relative degree of system is one.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.605-613
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• 2001

In this paper, we design a robust adaptive controller for a nonlinear system with uncertainties to be rejected via disturbance adaptation law. The nonlinear system considered has unknown nonlinear functions being influenced by external disturbance. The upper bound of unknown nonlinear functions at each time is estimated by using a disturbance adaptation law. The estimated nonlinear functions are used to design a stabilizing function a control input. Tuning function is used to estimates unknown system parameter without overparametrization. A set-point regulation error converges to a residual set close to zero asymptotically. The effectiveness of the proposed controller is investigated by computer simulation.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2611-2613
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• 2000

This paper deals with a novel approach to unknown inputs observer(UIO) design for linear time-invariant dynamical systems using a fast Walsh transform and Walsh function's differential operation. Generally, UIO has a derivation of system outputs which is not available from the measurement directly. And it is an obstacle to estimate the unknown inputs properly when unexpected measurement noises are presented. Therefore, this paper propose an algebraic approach to eliminate such problems by using a Walsh function's differential operation.