• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.131-138
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• 1999

In discrete-time controlled system, sampling time is one of the critical parameters for control performance. It is useful to employ different sampling rates into the system considering the feasibility of measuring system or actuating system. The systems with the different sampling rates in their input and output channels are named multirate system. Even though the original continuous-time system is time-invariant, it is realized as time-varying state equation depending on multirate sampling mechanism. By means of the augmentation of the inputs and the outputs over one Period, the time-varying system equation can be constructed into the time-invariant equation. In this paper, an alternative time-invariant model is proposed, the design method and the stability of the LQG (Linear Quadratic Gaussian) control scheme for the realization are presented. The realization is flexible to construct to the sampling rate variations, the closed-loop system is shown to be asymptotically stable even in the inter-sampling intervals and it has smaller computation in on-line control loop than the previous time-invariant realizations.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.123-130
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• 1999

In discrete-time controlled system, sampling time is one of the critical parameters for control performance. It is useful to employ different sampling rates into the system considering the feasibility of measuring system or actuating system. The systems with the different sampling rates in their input and output channels are named multirate system. Even though the original continuous-time system is time-invariant, it is realized as time-varying state equation depending on multirate sampling mechanism. By means of the augmentation of the inputs and the outputs over one period, the time-varying system equation can be constructed into the time-invariant equation. The two multirate formulations have some trade-offs in the simplicity to construct the controller, the control performance. It is good issue to determine the suitable formulation in consideration of performance of them. In this paper, the two categories of multirate formulations will be compared in terms of the linear quadratic (LQ) cost function. The results are used to select the multirate formulation and the sampling rates suitable to the desired control performance.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.112-117
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• 1992

The Real-time Distributed Control Systems(RDCS) consist of several distributed control processes which share a network medium to exchange their data. Performance of feedback control loops in the RDCS is subject to the network-induced delays from sensor to controller and from controller to actuator. The network-induced delays are directly dependent upon the data sampling times of the control components which share a network medium. In this study, a scheduling algorithm of determining data sampling times is developed using the window concept, where the sampling data from the control components dynamically share a limited number of windows.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.154-161
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• 2014

In this research we investigate motion controller performance for mobile robots according to changes in the control loop sampling time. As a result, we suggest a proper range of the sample time, which can minimize final posture errors while improving tracking capability of the controller. For controller implementation into real mobile robots, we use a smooth and continuous motion controller, which can respect robot's path curvature limitation. We examine motion control performance in experimental tests while changing the control loop sampling time. Toward this goal, we compare and analyze experimental results using two different mobile robot platforms; one with real-time control and powerful hardware capability and the other with non-real-time control and limited hardware capability.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1829-1832
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• 2004

Closed loop stability of Extended Dynamic Matrix Control (EDMC) is investigated for limited sampling time. Linear approximation of the sensitivity functions is employed in the derivation of the stability condition. It is shown that the closed loop system will be stable if the control moves suppression coefficient ${\lambda}$ is taken arbitrarily large. Special cases such as M=P=1 and M=1, P>1 are discussed in more details.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.997-1006
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• 2015

In industrial quality control, when engineers use VSI control procedure they should consider both required time to signal and switching behaviors together in the case of production process changed. Up to the present, many researchers have studied fixed sampling interval (FSI) chart and variable sampling interval (VSI) chart in the points of average number of samples to signal (ANSS) and average time to signal (ATS). However, ANSS and ATS do not provide any switching information between different sampling intervals of VSI schemes. In this study, performances of two sampling intervals VSI chart and three sampling intervals VSI chart are evaluated and compared. The numerical results show that ANSS and ATS values of two sampling intervals VSI chart and three sampling interval VSI chart are similar regardless the amount of shifts. However, the values of switching behaviors including ANSW are less efficient in three sampling intervals VSI charts than in two sampling intervals VSI chart.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.244-249
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• 1998

In this paper, the hybrid state space self-tuning control technique Is studied within the framework of fuzzy systems and dual-rate sampling control theory. We show that fuzzy modeling techniques can be used to formulate chaotic dynamical systems. Then, we develop the hybrid state space self-tuning fuzzy control techniques with dual-rate sampling for digital control of chaotic systems. An equivalent fast-rate discrete-time state-space model of the continuous-time system is constructed by using fuzzy inference systems. To obtain the continuous-time optimal state feedback gains, the constructed discrete-time fuzzy system is converted into a continuous-time system. The developed optimal continuous-time control law is then convened into an equivalent slow-rate digital control law using the proposed digital redesign method. The proposed technique enables us to systematically and effective]y carry out framework for modeling and control of chaotic systems. The proposed method has been successfully applied for controlling the chaotic trajectories of Chua's circuit.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1726-1729
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• 1997

In general, the solvability of linear robust output regulation problem are not preserved under time-sampling. Thus, it is found that the digital regulator implemented by itme-sampling of anlog output regulator designed based on the continuous-time linear system model is nothing but a 1st order approximation with respect to time-sampling. By the way, one can design an improved sampled-data regulator with respect to sampling time by utilizing the intrinsic structure of the system. In this paper, we study the system structures which it is possible to design an improved sampled-data regulator with respect to sampling time.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.391-394
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• 1996

The effects of time-sampling on nonlinear output regulation problem is investigated. Output regulatedness is preserved under time sampling as in linear systems, however output regulatability is not robust with respect to time-sampling, and thus one needs to seek an approximate nonlinear sampled-data output regulator.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.18-28
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• 1993

Processes in the real-time distributed control systems share a network medium to exchange their data. Performance of feedback control loops in the real-time distributed control systems is subject to the network-induced delays from sensor to controller, and from controller to actuator. The network-induced delays are directly dependent upon the data sampling times of control components which share a network medium. In this study, an algorithm of determining data sampling times is developed using the "window concept". where the sampling datafrom the control components dynamically share a limited number of windows. The scheduling algorithm is validated through the aimulation experiments.