• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.80-82
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• 1979

While the standard linear-quadratic-Gaussian problem has fixed horizons, this paper considers the LQG problem with moving horizons. By the separation principle the solution will be given by the kalman filter with the approaching horizon and the LQ regulator with the receding horizon. Sufficient conditions on weighting matrices are derived under which the filter and regulator are asymptotically stable. It wall be shown that the computation method of the moving-horizon LQG regulators is better than that of the standard LQG regulator. The performance measure between the two optimal controls will be compared. A simulation result is given in order to show the usefulness of the moving-horizon LQG regulator.s

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2566-2569
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• 2003

An alternative optimal control law formulation is introduced and compared with two different control law, a conventional linear quadratic regulator and the control law based on game theory. This formulation eliminates the undesired modes of the system by the projection of a controller onto the subspace orthogonal to that of the bad modes. In conventional LQR control law, the control performance can be improved only by using proper weighting matrices in performance index, normally, with high cost. The control law formulation by game theory may provide various ways to obtain the desired performance. The control law modified by the elimination of bad modes provides efficient ways to get rid of an undesired performance since it eliminates the exact modes which cause the bad control performance.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.85-97
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• 2003

An indefinite stochastic linear-quadratic(LQ) optimal control problem with cross term over an infinite time horizon is studied, allowing the weighting matrices to be indefinite. A systematic approach to the problem based on semidefinite programming (SDP) and .elated duality analysis is developed. Several implication relations among the SDP complementary duality, the existence of the solution to the generalized Riccati equation and the optimality of LQ problem are discussed. Based on these relations, a numerical procedure that provides a thorough treatment of the LQ problem via primal-dual SDP is given: it identifies a stabilizing optimal feedback control or determines the problem has no optimal solution. An example is provided to illustrate the results obtained.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.424-427
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• 1995

In this paper, a control law based on the receding horizon concept which robustly stabilizes time-varying discrete linear systems, is proposed. A dynamic game problem minimizing the worst case performance, is adopted as an optimization problem which should be resolved at every current time. The objective of the proposed control law is to guarantee the closed loop stability and the infinite horizon $H^{\infty}$ norm bound. It is shown that the objective can be achieved by selecting the proper terminal weighting matrices which satisfy the inequality conditions proposed in this paper. An example is included to illustrate the results..

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.149-154
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• 1990

In this paper, simulation results of a robust digital tracking controller on a robotic manipulator are presented. The objective is to follow a ramp reference input with zero steady state error in the presence of a disturbance and system parameter variations. Some of the difficulties are caused by the Coulomb frictions, the disturbance due to the gravitational pull, the spring effect of a link between the drive motor and the manipulator arm. Another difficulty is that, because of the non-differentiable Coulomb friction, the digital control system cannot be represented as a discrete system. It is thus necessary to design the controller based on a discrete-continuous hybrid model. The controller is based on feeding back the state variables and augmenting the system by addition discrete integrators. The feedback gain parameters are obtained by applying the quadratic optimal control theory and then choosing the new weighting matrices to eliminate the limit cycle by using the describing function method for hybrid system.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.477-491
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• 1997

A new predictive classification rule for assigning future cases into one of two multivariate normal population (with unknown normal mixture model) is considered. The development involves calculation of posterior probability of each possible normal-mixture model via a default Bayesian test criterion, called intrinsic Bayes factor, and suggests predictive distribution for future cases to be classified that accounts for model uncertainty by weighting the effect of each model by its posterior probabiliy. In this paper, our interest is focused on constructing the classification rule that takes care of uncertainty about the types of covariance matrices (homogeneity/heterogeneity) involved in the model. For the constructed rule, a Monte Carlo simulation study demonstrates routine application and notes benefits over traditional predictive calssification rule by Geisser (1982).

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.9
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• pp.937-944
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• 1991

In digital controller design, the delays in the controller should be taken into consideration when the computation time of the processor is not negligibale compared with sampling time. Recently, Mita has proposed a digital optimal servosystem taking account of the delays in the controller. In this paper, robust stability and diturbance rejection properties of this optimal servosystej are analyzed in the frequency-domain. The well-known asymptotic properties of the optimal regulators with respect to the weighting matrices of the cost functions are successfully utilized to show that the influence of the delays in the controller are drastic for certain choice of the cost function Illustrative numerical examples are presented.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.140-145
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• 2001

Various control algorithms are available to suppress the vibration of a system subjected to disturbances. LQ algorithm is simple and easy to implement the hardwares, but it lacks robustness for uncertainties and often causes difficulty in determining the weighting matrices. This study focuses on the effectiveness ILQ(Inverse Linear Quadratic optimal control) algorithm as the alternative to LQ applied to control the vibration of a building under the seismic excitation. The building is of moment resisting steel frames and assumed to behave within the elastic range. The brief overview of LQ and ILQ algorithms is introduced, and the displacement responses of the structure using ILQ algorithm are compared with those obtained from LQ control. The magnitude of control forces are also determined and compared for both LQ and ILQ algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.108-120
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• 1998

In this paper, a new control system design algorithm, which has the advantages of the existing LQR and eigenstrcture assignment methods, is proposed. The method of the transformation matrix via block controller is utilized to develop the scheme. Using the proposed algorithm, LQR weighting matrices q and R, which satisfy the desired closed-loop eigenvalues and eigenvectors, can be achieved using only simple matrix computations. The usefulness of the proposed scheme is verified by applying to a numerical example and an automotive active suspension control system design.

• Journal of Sensor Science and Technology
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• v.28 no.2
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• pp.88-93
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• 2019

This paper is concerned with distributed fusion moving average prediction for continuous-time linear stochastic systems with multiple sensors. A distributed fusion with the weighted sum structure is applied to the optimal local moving average predictors. The distributed fusion prediction algorithm represents the optimal linear fusion by weighting matrices under the minimum mean square criterion. The derivation of equations for error cross-covariances between the local predictors is the key of this paper. Example demonstrates effectiveness of the distributed fusion moving average predictor.