• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.632-639
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• 2003

This paper proposes a simple compensation scheme for the time delay caused by measurement, calculation and selection of voltage vector in Direct Torque Control (DTC) of an induction motor. In general scheme, it is difficult to know the exact delay time, furthermore the delay time can be varied by program routines for calculation and processing of measured data. In this proposed scheme, by applying voltage vector at the beginning of next sampling period, a fixed delay time is achieved and its compensation becomes much simpler. Furthermore, with the simple compensation algorithm, an improved performance can be achieved by shortening sampling period. Experimental results prove the feasibility of the proposed scheme in induction motor control.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.152-156
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• 2007

This paper proposes a method for real-time control of both capacitors and ULTC in a distribution system to reduce the total power loss and to improve the voltage profile over the course of a day. The multi-stage consists of the off-line stage to determine dispatch schedule based on a load forecast and the on-line stage generates the time and control sequences at each sampling time. It is then determined whether one of the control actions in the control sequence is performed at the present sampling time. The proposed method is presented for a typical radial distribution system with a single ULTC and capacitors.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1162-1167
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• 2004

This paper presents the design methodology of digital fuzzy controller(DFC) for the systems with time-delay. We propose the fuzzy feedback controller whose output is delayed with unit sampling period and predicted. The analysis and the design problem considering time-delay become easy because the proposed controller is syncronized with the sampling time. The stabilization problem of the digital fuzzy system with time-delay is solved by linear matrix inequality(LMI) theory. Convex optimization techniques are utilized to solve the stable feedback gains and a common Lyapunov function for designed fuzzy control system. To show the effectiveness the proposed control scheme, the network control example is presented.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.46-51
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• 2017

Recent controller design techniques often discretize the target system and implement a discrete controller that is digitized to match the target system. When constructing such a discrete system, it is necessary to first determine the sampling time. The smaller the sampling time is, the more advantageous it can be made similar to the original system, but the cost is a problem when realizing such a configuration as hardware. On the other hand, the longer the time, the more different the system is from the original system, and eventually the control becomes impossible. In this paper, we consider the above problem and propose a more logical approach to determine the sampling time in the discrete system and investigate the relation with the differential controller. We also apply this process to a nonlinear system called ARAGO disc and verify its validity through computer simulation.

• 전기의세계
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• v.25 no.6
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• pp.89-96
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• 1976

In this paper we deal with that the performance indices by the three adaptive sampling control laws are computed and compared. It shows that the most effective control law is the integral input difference method. The techniques of simulation by Analog/Hybrid computer are presented and the results of the output illustrate that the maximum and minimum sampling interval can be applied to the time sharing of digital controller or computer.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.192-198
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• 2016

Motion planning problem is still one of the important issues in robotic applications. In many real-time motion planning problems, it is advisable to find a feasible solution quickly and improve the found solution toward the optimal one before the previously-arranged motion plan ends. For such reasons, sampling-based approaches are becoming popular for real-time application. Especially the use of a rapidly exploring random $tree^*$ ($RRT^*$) algorithm is attractive in real-time application, because it is possible to approach an optimal solution by iterating itself. This paper presents a modified version of informed $RRT^*$ which is an extended version of $RRT^*$ to increase the rate of convergence to optimal solution by improving the sampling method of $RRT^*$. In online motion planning, the robot plans a path while simultaneously moving along the planned path. Therefore, the part of the path near the robot is less likely to be sampled extensively. For a better solution in online motion planning, we modified the sampling method of informed $RRT^*$ by combining with the sampling method to improve the path nearby robot. With comparison among basic $RRT^*$, informed $RRT^*$ and the proposed $RRT^*$ in online motion planning, the proposed $RRT^*$ showed the best result by representing the closest solution to optimum.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.199-204
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• 2004

In this paper, a new dual-rate digital control technique for the Takagi-Sugeno (T-S) fuzzy system is suggested. The proposed method takes account of the stabilizablity of the discrete-time T-S fuzzy system at the fast-rate sampling points. Our main idea is to utilize the lifted control input. The proposed approach is to obtain the dual-rate discrete-time T-S fuzzy system by discretizing the overall dynamics of the T-S fuzzy system with the lifted control, and then to derive the sufficient conditions for the stabilization in the sense of the Lyapunov asymptotic stability for this system. An example is provided for showing the feasibility of the proposed discretization method.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.457-468
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• 2007

This paper proposes an adaptive moving average (A-MA) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI A-MA chart is to adjust sampling intervals as well as to accumulate previous samples selectively in order to increase the sensitivity. The VSI A-MA chart employs a threshold limit to determine whether or not to increase sampling rate as well as to accumulate previous samples. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI A-MA chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The control length L is introduced to prevent small mean shifts from being undetected for a long period. A Markov chain model is employed to investigate the VSI A-MA sampling process. Formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI A-MA chart is proposed. Comparative studies show that the proposed VSI A-MA chart is uniformly superior to the adaptive Cumulative sum (CUSUM) chart and to the Exponentially Weighted Moving Average (EWMA) chart, and is comparable to the variable sampling size (VSS) VSI EWMA chart with respect to the ATS performance.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.448-458
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• 1999

This paper proposes sequential control charts with an upper bound on sample size. Existing sequential control charts have no restriction on the number of observations at a sampling point. For situations where sampling and testing an item is time-consuming or expensive, sequential control charts may not be directly applied. When the number of observations in a sampling point reaches the upper bound and there is no out-of-control signal, the proposed cumulative sequential control chart defers the decision to the next sampling point of which starting value is the value of the current statistic. Two Markov chains, inner and outer chains, are used to derive the formulas for evaluating the performance of the proposed chart. It is compared with $\bar{X}$ and cumulative sum control charts with fixed and variable sample sizes. The fast initial response (FIR) feature is studied. Guidelines for the design of the proposed charts are also given.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.79-81
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• 1992

This paper describes the design of an adaptive closed circuit anesthesia controller based on a multiplexed mass spectrometer system. The controller deals with measurement deterioration caused by measurement delay and rise time through a tong catheter as well as long sampling times due to the multiplexed measurements. Measurement data is extrapolated between sampling periods to increase the estimation convergence rate. A multiple-step-ahead predictive control algorithm is used to calculate intermediatc control inputs between sampling intervals. Simulations are used to validate the designed controller.