• Management & Information Systems Review
• /
• v.3
• /
• pp.201-214
• /
• 1999

Adaptive correlator receiver with neural network based on complex multilayer perceptron is persented for suppressing interference of narrow-band of direct spread spectrum communication systems. Recursive least square algorithm with backpropagation error is used for fast convergence and better performance in adaptive correlator scheme. According to signal noise and transmission power, computer simulation results show that bit error ratio of adaptive correlator using neural network improved that of adative transversal filter of direct sequence spread spectrum considering of jamming and narrow-band interference. Bit error ratio of adaptive correlator with neural network is reduced about 10-1 than that of adaptive transversal filter where interference versus signal ratio is 5dB.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.2
• /
• pp.476-483
• /
• 2010

If the data are pre-whitened, then gradient adaptive algorithms which are simpler than higher order statistics algorithms can be used in adaptive blind signal estimation. In this paper, we propose a blind subband affine projection algorithm for multiple-input multiple-output adaptive equalization in the blind environments. All of the adaptive filters in subband affine projection equalization are decomposed to polyphase components, and the coefficients of the decomposed adaptive sub-filters are updated by defining the multiple cost functions. An infinite impulse response filter bank is designed for the data pre-whitening. Pre-whitening procedure through subband filtering can speed up the convergence rate of the algorithm without additional computation. Simulation results are presented showing the proposed algorithm's convergence rate, blind equalization and blind signal separation performances.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.52 no.12
• /
• pp.698-704
• /
• 2003

Autoreclosure provides a mean of improving power transmitting ability and system stability. The conventional reclosure adopts the fixed dead time interval strategy, that is, the reclosure is activated after a time delay to restore the system to normal as quickly as possible without regard to the system conditions, however, these simple techniques cannot give the optimal operating performance. For this reason, various adaptive reclosure algorithms have been proposed recently, This paper presents an adaptive autoreclosure algorithm including the variable dead time, optimal reclosure, sequential reclosure and emergency extended equal-area criterion (EEAC) algorithm in order to improve the system stability. The reclosure algorithm performs out the operations that are attuned to the power system conditions. The proposed adaptive reclosure algorithm is verified and tested by using EMTP MODELS, and the simulation results show that the system oscillations are reduced and the transient stability is enhanced by employing the proposed adaptive reclosure algorithm.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2002.10a
• /
• pp.256-261
• /
• 2002

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.7
• /
• pp.547-555
• /
• 2003

This paper presents an adaptive control against uncertainties in tail-controlled STT (Skid-to-Turn) missiles. We derive an analytic uncertainty model from a parametric affine missile model developed by the authors. Based on this analytic model, an adaptive feedback linearizing control law accompanied by a sliding mode control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme are demonstrated by simulation.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.39 no.1
• /
• pp.83-91
• /
• 1990

An adaptive observer which is applicable to discrete linear time invariant systems of ARMA type in the presence of noise is proposed. It first estimates the system parameters of the MA type by applying only the system input to the observer. Then it estimates the output which corresponds to the output of the system without any noise. This is a special case of Suzuki's adaptive observer. This estimated output is applied to Suzuki's adaptive observer to estimate the system parameters of ARMA type and the states. The proposed method can make the estimate errors of the system parameters sufficiently small even in the presence of noise in the system. It can also make the estimate errors of the states of the system sufficiently small when there is no process noise. These properties of the proposed adaptive observer is certified by computer simulation.

• Journal of Ocean Engineering and Technology
• /
• v.14 no.2
• /
• pp.7-12
• /
• 2000

This paper presents a non-regressor based adaptive control scheme for the trajectory tracking of underwater vehicle-mounted manipulator systems(UVMS). The adaptive control system includes a class of unmodeled effects is applied to the trajectory control of an UVMS. The only information required to implement this scheme ios the upper bound and lowe bound of the system parameter matrices the upper bound of unmodeled effects the number of joints the position and attitude of the vehicle and trajectory commands. The adaptive control law estimates control gains defined by the combinations of the bounded constants of system parameter matrices and of a filtered error equation. To evaluate the performance of the non-regressor based adaptive controller computer simulation was performed with a two-link planar robot model mounted on an underwater vehicle. The hydrodynamic effects acting on the manipulator are included. It is assumed that the vehicle's motion is slow and can be predicted with a proper compensator.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.11
• /
• pp.2139-2146
• /
• 2011

In this paper, a robust adaptive controller is proposed for trajectory tracking of robot manipulators with the unknown friction coefficient and bounded disturbance. A new adaptive control law is developed based on sliding mode and derived from the Lyapunov stability analysis. The introduction of a boundary layer solves the problem of chattering. The proposed adaptive controller is globally asymptotically stable and guarantees zero steady state error for joint positions. The estimated friction coefficients can also approach the actual coefficients asymptotically. A simulation example is provided to demonstrate the performance of the proposed algorithm.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2003.05b
• /
• pp.446-449
• /
• 2003

The conventional GSC is inappropriate in real situation when the target signal is present. The steering vector error cancels the target signal and the target signal misadjusts the weight of the adaptive filter. To prevent the target signal cancellation, the robust GSC using the constrained adaptive filters was already proposed. However, the adaptive weight misadjustment is not settled in robust GSC. This Paper proposes a revised robust sidelobe canceller with adaptive compensator. To compensate the influence of target signal, the adaptive compensator is used in cascade. In computer simulation, we show the performance improvement by comparing the robust GSC with the proposed GSC.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.23 no.4
• /
• pp.578-585
• /
• 1986

This paper describes a new two-dimensional adaptive lattice algorithm which determines reflection coefficients recursively by applying the gradient search technique to a two-dimensional lattice filter proposed by Parker and Kayran. The convergence characteristics of the proposed algorithm are also described. A new tow-dimensional adaptive lattice \ulcorneralgorithm has been obtained through the application of the \ulcorneralgorithm to the two-dimention adaptive lattice algorithm. Computer simulation proves that the convergence speed of the two-dimension adaptive lattice \ulcorneralgorithm is reladtively higher than that of the conventional adaptive lattice algorithm when \ulcornerhas a small value.