• 전기의세계
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• 제23권2호
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• pp.46-54
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• 1974

The purposes of this paper are to deal with the design of m-input, m-output linear systems by the state variable feedback, and to extend the design capability of the state variable feedback design. The design requirements are decoupling and the exact realigation of desired transfer functions. Some methods are proposed to insert series compensators in the fixed plant in the cases when series compensators are needed to meet the input-output transfer matrix specification. The method for adding series compensators to the input channels of the fixed plant is shown by examples to lead both to the loss of the ability to decouple the augmented plant by the state variable feedback, and to the loss of desired zeroes. A method which avoids these two hazards is developed in which series compensators are put on the output channels of the fixed plant: it is proved that the augmented plant is F-invariant. By treating each subsystem individually, the designer can apply some of the previous developed knowledge of the state variable design of single-input, single-output systems.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1551-1558
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• 2013

$H_2$ design of decoupled control systems is treated in the generalized plant model. The existence condition of a decoupling controller is stated and a parameterized form of all achievable decoupled closed loop transfer matrices is presented by using the directional interpolation approaches under the assumption of simple transmission zeros. The class of all decoupling controllers that yield finite cost function is obtained as a parameterized form and an illustrative example to find the optimal controller is provided.

• 대한전기학회논문지
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• 제45권3호
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• pp.407-414
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• 1996

In this paper we consider the variable structure control for a class of discrete-time uncertain multivariable systems where the nominal system is linear. Discrete-time switching dynamics are introduced so that a new type of state trajectories called sliding mode may exist on the sliding surface by state feedback. The quantitative analysis for the matched uncertainties will show that every response of the system with the proposed switching dynamics is bounded within small neighborhoods of the state-space origin. Also, by the similarity transformation it will be shown that the eigenvalues of the closed-loop systems are composed of those of the subsystems which govern the range-space dynamics and null-space dynamics. It will be also shown that ideal sliding mode can be obtained in the absence of uncertainties due to one-step attraction to the sliding surface regardless of initial position of states. (author). 12 refs., 2 figs.

• Bulletin of the Korean Chemical Society
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• 제24권3호
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• pp.279-284
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• 2003

The One Pass Method (OPM) previously presented for the identification of single input single output systems is used to estimate the parameters of a Decentralized Control System (DCS). The OPM is a linear and therefore a simple estimation method. All of the calculations are performed in one pass, and no initial parameter guess, iteration, or powerful search methods are required. These features are of interest especially when the parameters of multi input-output model are estimated. The benefits of the OPM are revealed by comparing its results against those of two recently published methods based on pulse testing. The comparison is performed using two databases from the literature. These databases include single and multi input-output process transfer functions and relevant disturbances. The closed loop responses of these processes are roughly captured by the previous methods, whereas the OPM gives much more accurate results. If the parameters of a DCS are estimated, the OPM yields the same results in multi or single structure implementation. This is a novel feature, which indicates that the OPM is a convenient and practice method for the parameter estimation of multivariable DCSs.

• 한국공작기계학회논문집
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• 제13권4호
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• pp.44-55
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• 2004

In order to meet the requirement for higher thickness accuracy in tandem cold rolling processes, it is strongly necessary to have good performance in control units. To meet this requirement, this paper suggested an output regulating control system with a roll-eccentricity estimator for each rolling stand of tandem cold mills. Considering entry thickness variation and roll eccentricity simultaneously as the major disturbances, a synthesis of multivariable control systems was presented based on H$\infty$ control theory, which could reflect the knowledge of input direction and spectrum of disturbance signals on design. Then, to effectively reject roll eccentricity, a weight function having some poles on the imaginary axis was introduced. This lead to a non-standard H$\infty$ control problem, and the design procedures for solving this problem were analytically presented. The effectiveness of the proposed control method was evaluated through computer simulations and compared to that of the conventional linear quardratic control and feedforward control methods for roll eccentricity.

• 대한수학회지
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• 제49권3호
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• pp.641-658
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• 2012

The goal of this paper is to develop a nonlinear observer-based control strategy for a multi-variables continuous stirred tank reactor (CSTR). A new robust nonlinear observer is constructed to estimate the whole process state variables. The observer is coupled with a nonlinear controller, designed based on the input-output linearization for controlling the concentration and reactor temperature. The closed loop system is shown to be globally asymptotically stable based on Lyapunov arguments. Finally, computer simulations are developed for showing the performance of the proposed controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2143-2145
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• 2003

In the linear system identification using the discrete time constant coefficients, there is a subspace method based on 4SID recently much suggested instead of the parametric method like as the maximum likelihood method. The subspace method is not related with the impulse response and difference equation in its input-output equation, but with the system matrix of the direct state space model from the input-output data. The subspace method is a very useful tool to adopt in the multivariable system identification, but it has a shortage unable to adopt in the closed-loop system identification. In this paper, we are suggested the methods to get rid of the shortage of the subspace method in the closed-loop system identification. The subspace method is used in the estimate of the output prediction values from the estimating of the state space vector. And we have compared the results with the outputs of the recursive least square method in the numerical simulation.

• 한국생산제조학회지
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• 제19권1호
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• pp.145-155
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• 2010

This paper presents a new approach to obstacle avoidance for mobile robot in unknown or partially unknown environments. The method combines two navigation subsystems: low level and high level. The low level subsystem takes part in the control of linear, angular velocities using a multivariable PI controller, and the nonlinear position control. The high level subsystem uses ultrasonic and IR sensors to detect the unknown obstacle include static and dynamic obstacle. This approach provides both obstacle avoidance and target-following behaviors and uses only the local information for decision making for the next action. Also, we propose a new algorithm for the identification and solution of the local minima situation during the robot's traversal using the set of fuzzy rules. The system has been successfully demonstrated by simulations and experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.282-284
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• 1992

In this paper, we deal with design method of two-degree-of-freedom control system which desired property of robustness and tracking can be achieved simultaneously, Controller is designed by means of model matching method and H$\infty$ weighted sensitivity minimization design method. Satisfactory result of design example is obtained by simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(I)
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• pp.198-200
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• 1987

This paper presents the choice of appropriate sets of input variables for large-scale linear multivariable systems. It is shown that the selection of a good set of input variables for control may become important when both strong and weak input variables are available. The transmission of information from the inputs to the outputs is investigated and appropriate scaling procedures to derive a scaled input matrix are proposed. Singular value decomposition methods facilitate the quantification of the systems excitation stemming from the various input variables, and thus the selection of an appropriately strong and orthogonal set of input variables. The need for and the implementation and benefits of reducing the number of input variables are illustrated by a large-scale steam generator model of a real process.