• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.635-641
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• 2016

In many industrial applications that use the electric motors robust controllers are needed. The method using a neural network in order to design a robust controller when a disturbance occurs is studied. Backpropagation algorithm, which is used in a conventional neural network controller is used in many areas, but when the number of neurons in the input layer, hidden layer and output layer of the neural network increases the processing speed of the learning process is slow. In this paper an adaptive PI(Proportional and Integral) controller based on CTRNN(Continuous Time Recurrent Neural Network) for permanent magnet synchronous motors is presented. By varying the load and the speed the validity of the proposed method is verified through simulation and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.121.1-121
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• 2001

Congestion control is a critical issue in TCP networks, Recently, active queue management (AQM) was proposed for congestion control at routers. The random early detection RED algorithm is widely known in the AQM algorithms, We present an adaptive nonlinear RED (NRED) algorithm, which has nonlinear drop probability profile. The proposed algorithm enhanced the performance of the RED algorithm by the self-parameterization based on the traffic load Furthermore, the proposed algorithm can effectively adapt itself between he RED and the drop-tail queue management by adopting proper nonlinearity in the drop probability profile. Through simulation, we show the effectiveness of the proposed algorithm comparing with the drop-tail and the original RED algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.496-499
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• 1997

Field robot represented by excavator can be applied for various kinds of working in manufacturing, construction, agriculture etc. because of the flexibility of its multi-joint mechanism and the high power of hydraulic actuators. In general, the dynamics of field robot have strong coupling, various kinds of non-linearity, and time-varying parameters according to working conditions. Therefore, it is very difficult to describe the system well, and design controller systematically based on its model. This paper established the mathematical model of field robot driven by electro-hydraulic servomechanism and constructed the adaptive control system robust to external load variations. The proposed control system for the field robot was evaluated by the computer simulation and the performance results of trajectory tracking were compared with that of PID control system.

• The Journal of the Acoustical Society of Korea
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• v.27 no.1E
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• pp.1-10
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• 2008

A noise suppression algorithm is proposed for nonstationary noisy environments. The proposed algorithm is different from the conventional approaches such as the spectral subtraction algorithm and the minimum statistics noise estimation algorithm in that it classifies speech and noise signals in time-frequency bins. It calculates the ratio of the variance of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. If the ratio is greater than an adaptive threshold, speech is considered to be present. Our adaptive algorithm tracks the threshold and controls the trade-off between residual noise and distortion. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of simplicity and light computational load for estimating the noise. This algorithm reduces the residual noise significantly, and is superior to the conventional methods.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.269-274
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• 1990

Usually, robot manipulators in production lines are operated with reperting work trajectories. This paper presents the repeated adaptive learning algorithm for robot manipulates for the case of a trajectory. This algorithm uses the nonlinear dynamic model including the repeated friction compensating term, The advantage of the scheme is that It allows friction compensation which may be otherwise difficult for differently constructed models. A secondary advantage of the sheme is that it can also adapt to torque calculation in order to reduce the computational load of the control computer. To show the efficiency of the proposed controller, a computer simulation is performed for the planar robot manipulator with a 2 degree of freedom.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.5
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• pp.1-15
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• 1993

In DQDB networks, the bandwidth can be increased considerably be using the EN(Erasure Node) algorithms and DR(Destination Release) algorithms. However, the important issue in implementing them is using method of extra capacity fairly. To improve it, this paper proposes AEN(Adaptive Erasure Node) algorithm which erasure function is activated by network traffic load. Its functional architecture consists of SESM, RCSM, LMSM in addition to the basic DQDB state machines (DQSM, RQM). The SESM and RCSM state machines are placed in front of the DQSM and RQM state machines in order for the node to take advantage of the newly cleared slots. This paper also presents some simulation results showing the effect of AEN algorithm on access delay, throughput and segment erasing ratio in the single and multiple priority networks. The results show that the AEN algorithm offer the better performance characteristics than existing algorithms under overload conditions.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.902-906
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• 2008

The linear motors are easily affected by load disturbance, force ripple, friction, and parameter variations because there is no mechanical transmission to reduce the effects of model uncertainties and external disturbance. For highspeed/high-accuracy position control of a linear-motor-driven two axes, a nonlinear adaptive controller including a cross-coupling algorithm is designed in this paper. The nonlinear effects such as friction and force ripple are estimated and compensated. An enhanced approach for cross-coupling algorithm is proposed to effectively improve the biaxial contour accuracy with the closed-loop stability. The proposed controller is evaluated through the computer simulations.

• International Journal of Contents
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• v.8 no.4
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• pp.7-11
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• 2012

Cloud Computing can be viewed as a dynamically-scalable pool of resources. Virtualization is one of the key technologies enabling Cloud Computing functionalities. Virtual machines (VMs) scheduling and allocation is essential in Cloud Computing environment. In this paper, two dynamic VMs scheduling and allocating schemes are presented and compared. One dynamically on-demand allocates VMs while the other deploys optimal threshold to control the scheduling and allocating of VMs. The aim is to dynamically allocate the virtual resources among the Cloud Computing applications based on their load changes to improve resource utilization and reduce the user usage cost. The schemes are implemented by using SimPy, and the simulation results show that the proposed adaptive scheme with one threshold can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.

• Journal of Power Electronics
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• v.7 no.1
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• pp.1-12
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• 2007

Novel nonlinear backstepping control with integrated adaptive control function is developed for high-performance positioning control systems. The proposed schemes are synthesized by a systematic approach and implemented based on a modern low-cost DSP controller, TMS320C32. A baseline backstepping control scheme is derived first, and is then extended to include a nonlinear adaptive control against the system parameter changes and load variations. The backstepping control utilizes Lyapunov function to guarantee the convergence of the position tracking error. The final control algorithm is a convenient in the implementation of a practical 32-bit DSP controller. The new control system can achieve superior performance over the conventional nested PI controllers, with improved position tracking, control bandwidth, and robustness against external disturbances, which is demonstrated by experimental results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.249-252
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• 2001

We, for the first time, propose a novel adaptive beamforming algorithm for smart antenna. The algorithm requires neither spatial knowledge nor reference signal. The algorithm is based on gradient method and its merit is in the simplicity of calculation load while maintaining good performance. Computer simulations are presented to verify the performance.