• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1-4
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• 2004

The dual-mode strategy has been adopted in many constrained MPC methods. The size of stabilizable regions of states of MPC methods depends on the size of underlying feasible and positively invariant set and number of control moves. These results, however, could be conservative because the definition of positive invariance does not allow temporal leave of states from the set, In this paper, a concept of periodic invariance is introduced in which states are allowed to leave a set temporarily but return into the set in finite steps. The periodic invariance can defined with respect to sets of different state feedback gains. These facts make it possible for the periodically invariant sets to considerably larger than ordinary invariant sets. The periodic invariance can be defined for systems with polyhedral model uncertainties. We derive a MPC method based on these periodically invariant sets. Some numerical examples are given to show that the use of periodic invariance yields considerably larger stabilizable sets than the case of using ordinary invariance.

• International Journal of Automotive Technology
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• 제6권4호
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• pp.375-381
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• 2005

This paper presents linear algebraic equations in the form of recursive formula to compute elastokinematic characteristics of a suspension system. Conventional methods of elastokinematic analysis are based on nonlinear kinematic constrant equations and force equilibrium equations for constrained mechanical systems, which require complicated and time-consuming implicit computing methods to obtain the solution. The proposed linearized elastokinematic equations in the form of recursive formula are derived based on the assumption that the displacements of elastokinematic behavior of a constrained mechanical system under external forces are very small. The equations can be easily computerized in codes, and have the advantage of sharing the input data of existing general multi body dynamic analysis codes. The equations can be applied to any form of suspension once the type of kinematic joints and elastic components are identified. The validity of the method has been proved through the comparison of the results from established elastokinematic analysis software. Error estimation and analysis due to piecewise linear assumption are also discussed.

• 한국통신학회논문지
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• 제19권2호
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• pp.338-344
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• 1994

Price 정리를 일반적인 제로메모리 함수와 그 입력이 제한적 비가우시안 프로세스에 대하여 일반화 한다. 제한적 비가우시안 프로세스는 둘 이상의 상호 독립인 프로세스들의 합으로 되어 있고, 이 중 첫번째 프로세스는 가우시안인 것을 말한다. 이런 일반화된 정리의 응용성을 보여주기 위해 예를 든다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.697-699
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• 2000

In this paper, an extension of model predictive controller for nonlinear process using Takagi-Sugeno(TS) fuzzy model is proposed Since the consequent parts of TS fuzzy model comprise linear equations of input and output variables. it is locally linear, and the Generalized Predictive Control(GPC) technique which has been developed to control Linear Time Invariant(LTI) plants, can be extended as a parallel distributed controller. Also fuzzy soft constraints are introduced to handle both equality and inequality constraints in a unified form. So the traditional constrained GPC can be transferred to a standard fuzzy optimization problem. The proposed method conciliates the advantages of the fuzzy modeling with the advantages of the constrained predictive control, and the degree of freedom is increased in specifying the desired process behavior.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.377-382
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• 2005

This paper presents a new method for the attitude control of planar space robots. In order to control highly constrained non-linear system such as a 3D space robot, the analytical formulation for the system with complex dynamics and effective control methodology based on the formulation, are not always obtainable. In the proposed method, correspondingly, a non-analytical but effective self-organizing modeling method for controlling a highly constrained system is proposed based on a polynomial data mining algorithm. In order to control the attitude of a planar space robot, it is well known to require inputs characterized by a special pattern in time series with a non-deterministic length. In order to correspond to this type of control paradigm, we adopt the Model Predictive Control (MPC) scheme where the length of the non-deterministic horizon is determined based on implementation cost and control performance. The optimal solution to finding the size of the input pattern is found by a solving two-stage programming problem.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.619-623
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• 1992

In pattern recognition, the conventional neural networks contain a large number of weights and require considerable training times and preprocessor to classify a transformed patterns. In this paper, we propose a constrained pattern recognition method which is insensitive to rotation of input pattern by various degrees and does not need any preprocessing. Because these neural networks can not be trained by the conventional training algorithm such as error back propagation, a novel training algorithm is suggested. As such a system is useful in problem related to calssify overse side and reverse side of 500 won coin. As an illustrative example, identification problem of overse and reverse side of 500 won coin is shown.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2001년도 추계 학술발표회 논문집 Proceedings of EESK Conference-Fall 2001
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• pp.52-56
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• 2001

In order to get information on more reliable S-wave attenuation characteristics in the Gyeongsang Basin, local earthquake data compiled during the period of years 1997~2000 are analyzed using spectral smoothing technique. Total 421 seismograms recorded at 12 local stations by 68 earthquakes of local magnitudes equal to or greater than 1.4 are examined. Among them, 155 records with good S/N ratio were analyzed. As results, statistically well constrained attenuation characteristics are fecund. Those are; (1) 0.000158362 < $x_{q}$-value (0.000196474) < 0.000234586, (2) 0.00657 < $x_{s}$-value (0.01061) < 0.01465, and (3) 1158 < Q-value (1383) < 1716, where the upper and low limits are values with 95% confidence level. We obtained remarkably well constrained $X_{s}$-value which has not been determined previously. The results can be used as input data far ground motion computations in earthquake engineering.ing.g.

• 말소리와 음성과학
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• 제3권3호
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• pp.91-98
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• 2011

In this paper, a multi-channel speech enhancement method using the linearly constrained minimum variance (LCMV) algorithm and a variable learning rate control is proposed. To control the learning rate for adaptive filters of the LCMV algorithm, the direction of arrival (DOA) is measured for each short-time input signal and the likelihood function of the target speech presence is estimated to control the filter learning rate. Using the likelihood measure, the learning rate is increased during the pure noise interval and decreased during the target speech interval. To optimize the parameter of the mapping function between the likelihood value and the corresponding learning rate, an exhaustive search is performed using the Bark's scale distortion (BSD) as the performance index. Experimental results show that the proposed algorithm outperforms the conventional LCMV with fixed learning rate in the BSD by around 1.5 dB.

• 제어로봇시스템학회논문지
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• 제22권6호
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• pp.397-402
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• 2016

This paper proposes a robust tracking control for constrained uncertain linear systems by combining a disturbance observer (DOB) and linear matrix inequality (LMI) based state feedback control. To this end, the state feedback control is designed for the nominal system and then a DOB based feed-forward control is added to reject uncertainties. In doing so, the DOB and state feedback controller are joined in a way that the combined control satisfies the input constraints and closed loop stability is guaranteed. Simulation results are provided to show that the proposed control scheme successfully stabilizes uncertain systems.

• ETRI Journal
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• 제22권3호
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• pp.1-9
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• 2000

Self-Clocked Fair Queueing (SCFQ) algorithm has been considered as an attractive packet scheduling algorithm because of its implementation simplicity, but it has unbounded delay property in some input traffic conditions. In this paper, we propose a Rate Proportional SCFQ (RP-SCFQ) algorithm which is a rate proportional version of SCFQ. If any fair queueing algorithm can be categorized into the rate proportional class and input is constrained by a leaky bucket, its delay is bounded and the same as that of Weighted Fair Queueing (WFQ) which is known as an optimal fair queueing algorithm. RP-SCFQ calculates the timestamps of packets arriving during the transmission of a packet using the current value of system potential updated at every packet departing instant and uses a starting potential when it updates the system potential. By doing so, RP-SCFQ can have the rate proportional property. RP-SCFQ is appropriate for high-speed packet-switched networks since its implementation complexity is low while it guarantees the bounded delay even in the worst-case input traffic conditions.