• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.510-520
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• 2014

By adopting the MAC(Media Access Control) protocol which enables to pack multiple MPDUs(MAC-level Protocol Data Units) into a single PPDU(Physical Layer Protocol Data Unit), IEEE 802.11n WLAN supports high throughput. Up to now, there have been a lot of existing channel information-based A-MPDU schemes dynamically determining the number of MSDUs according to the wireless channel condition information which is sent from the receiver to sender. However, the channel information-based scheme has a serious drawback having a high system overhead due to the frequent channel feedback information. To reduce the system overhead, the proposed BA-base dynamic A-MPDU scheme simply chooses the number of MSDUs to be retransmitted by not the frequent channel feedback information but the BA signal representing whether MPSUs belonging to the A-MPDU are received or not. Through NS-2(Network Simulator-2), we found that the proposed scheme had higher throughput and lower packet error rate than the existing fixed A-MPDU scheme.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.3
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• pp.139-149
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• 2015

In this paper, we describe a new approach to perform real-time implementation of an robust controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved direct Lyapunov method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for robot manipulator consisting of dual arm with eight degrees of freedom at the joint space and cartesian space.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.15-23
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• 1992

Neural network control has many innovative potentials for fast, accurate and intelligent adaptive control. In this paper, two kinds of neurocontrol architectures for the dynamic control of robot manipulators are developed. One is based on a System Identification and Control scheme and the other is based on the Feedback-Error leaming scheme. Both of the proposed architectures use an inverse dynamic neurocontroller in parallel with a linear neurocontroller. The difference is that the first architecture uses the system identifier to get the signals used for training neurocontrollers, while the second architecture uses a properly defined energy function. Compared with the previous types of neurocontrollers which are using an inverse dynamic neurocontroller and a fixed PD gain controller, the proposed architectures not only eliminate the painful process of the fixed gain tuning but also exhibit superior peformances because the linear neurocontroller can adapt its gains according to the applied task. This superior performance is tested and verified through computer simulation of the dynamic control of the PUMA 560 arm.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.8
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• pp.612-618
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• 2003

A hybrid vibration control scheme using ER fluid and PZT patches is proposed. Dynamic characteristics of the beam embedded with the ER fluid can be controled by changing the strength of the electric field applied on the ER fluid, thus provides a mean to avoid the resonance. It was found that active vibration control of the structure embedded with ER fluid failed to suppress the vibration excited with broad band frequency due to the limited change of the dynamic characteristics of the structure. To compensate this limited effect of the control scheme with ER fluid alone, PPF control using PZT patches as sensors and actuators is added to construct a hybrid controller. Experimental results suggests that proposed hybrid controller is effective to suppress the additional resonance vibration that appears when each controller is used alone.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.85.4-85
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• 2001

A learning controller is presented for repetitive walking motion of biped robot. The learning control scheme learns the approximate inverse dynamics input of biped walking robot and uses the learned input pattern to generate an input profile of different walking motion from that learnt. In the learning controller, the PID feedback controller takes part in stabilizing the transient response of robot dynamics while the feedforward learning controller plays a role in computing the desired actuator torques for feedforward nonlinear dynamics compensation in steady state. It is shown that all the error signals in the learning control system are bounded and the robot motion trajectory converges to the desired one asymptotically. The proposed learning control scheme is ...

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.4
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• pp.282-290
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• 2000

In this paper, the charge control with the input voltage feedback is proposed for the input series-output series-output parallel connected converter configuration for the high speed train power system application. This control scheme accomplishes the output current sharing for the output-parallel connected modules as well as the input voltage sharing for the input series connected modules for all operating conditions including the transients. It also offers the robustness for the input voltage sharing control according to the component value mismatches among the modules. And this configuration enables the usage of MOSFET for a high voltage system allowing a higher switching frequency for lighter system weight and smaller size. The performance of the proposed scheme is verified through the experimental results.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.530-541
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• 2011

In this paper, we propose an effective network-adaptive ARQ based error control scheme to provide video streaming services through IP networks where packet error usually occurs. If time delay and feedback channel are allowed, client can request server to retransmit lost packets through IP networks. However, if retransmission is unconditionally requested without considering network condition and number of simultaneous feedback messages, retransmitted packets may not arrive in a timely manner so that decoding may not occur. In the proposed ARQ, a client conditionally requests retransmission based on assumed network condition, and it further determines valid retransmission time so that effective ARQ can be applied. In order to verify the performance of the proposed adaptive ARQ based error control, NIST-Net is used to emulate packet-loss network environment. It is shown by simulations that the proposed scheme provides noticeable error resilience with significantly reduced traffics required for ARQ.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.2
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• pp.88-95
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• 1996

It is inevitable for local systems to have deviations which represent interactions and modeling errors originated from the decomposition process of a large scale system. This paper presents a decentralized control scheme for interconnected systems using local linear models and a neuro-coordinator. In the proposed method, the local system is composed of a linear model and unknown deviations caused by linearizing the subsystems around operating points or by estimating parameters of the subsystems. Because the local system has unmeasurable deviations we define a local reference model which consists of a local linear model and a neural network to estimate the deviations indirectly. The reference model is reformed into a linear model which has no deviations through a transformation of input variables and we obtain an optimum feedback control law which minimizes a local performance index. Finally, we derive a decentralized feedback control law which consists of local linear states and neural network outputs. In the decentralized control, the neuro-coordinator generates a corrective control signal to cancel the effect of deviations through backpropagation learning with the errors obtained from the differences of the local system outputs and reference model outputs. Also, the stability of local system is proved by the degree of learning of the neural network under an assumption on a neural network learning index. It is shown by computer simulations that the proposed control scheme can be applied successfully to the control of a biased two-link planar robot manipulator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8A
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• pp.798-803
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• 2006

An opportunistic scheduling is adopted to improve the capacity of the system by exploiting the multiuser diversity of multiuser MIMO(MU-MIMO) systems. However it requires the large amount of feedback carrying the channel quality information(CQI) of each user to the transmitter, The considered per user unitary and rate control(PU2RC) needs to feedback the preferred preceding index and its CQIs, and it has a defect in scheduling the streams for the grouped user. In order to overcome these drawbacks, a novel feedback reduction scheme is proposed in this paper. It employs transmitter controlled preceding and opportunistic feedback(TCP-OFB). The simulation results demonstrate that TCP-OFB shows comparable performance to PU2RC while it only requires far reduced feedback load.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.491-495
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• 2016

We deal with the regulation problem of nonlinear systems with time-varying delays in both the states and input. A new state feedback controller with dynamic gains is developed based on matrix inequality and non-predictor methods. The proposed control scheme is analyzed using the Razumikhin theorem, and its effectiveness is demonstrated with simulation results.