• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.56.3-56
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• 2001

This study describes the jump error smoothing scheme with fuzzy logic based on the scalar adaptive filter. The scalar adaptive filter is an useful algorithm for smoothing abrupt jump errors. However, the performances of scalar adaptive algorithm depend on the variance of real signal. So to design an effective algorithm, many informations of real and jump signal are required. In this paper, the fuzzy rules are designed by the analysis of scalar adaptive filter, and then the improved and simplified scheme is developed for smoothing the jump error. Simulations to INS/GPS integrated system show that the proposed method is effective.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.45-49
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• 1988

This paper presents a centralized adaptive control scheme based on perturbation equations in the vicinity of a desired trajectory,which are used to design a feedback control about the desired trajectory. This adaptive control scheme reduces the manipulator control problem from a nonlinear control to controlling a linear control system about a desried trajectory. Computer simulation studies of a two-joint manipulator are performed on a IBM-PC to illustrate the performance of this adaptive control scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9C
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• pp.826-833
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• 2007

In this paper, we present an adaptive transmission system model to establish the baseline for wireless adaptive transmission using CR (Cognitive Radio) systems, and propose an adaptive transmission scheme based on IT (Interference Temperature) cognition for CR systems in the presented system environment. The proposed CR adaptive transmission scheme is the method that provides the CR user with the maximum transmit power in the range of not causing any interference to the incumbent user and guaranteeing the optimal throughput by applying CR-AMC (CR-Adaptive Modulation and Coding) in the given channel state. Simulation results show that in case of using the proposed CR adaptive transmission scheme, there is little degradation of BER performance, while causing no interference to the incumbent user. At the same time, the proposed scheme guarantees the optimal throughput to the CR user in the given channel state.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.77-80
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• 2000

Adaptive filter based code acquisition scheme offers a fast acquisition with a low error probability. However, it has been studied only under a coherent environment. In this paper, the noncoherent adaptive code acquisition scheme employing a differential detection technique is proposed. For the proposed scheme, system probabilities and the mean acquisition time are analyzed numerically. Simulation results show that the proposed system outperforms over the conventional matched filter by 2-4 ㏈ under AWGN channel for 16 taps.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.39.2-39
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• 2002

This paper presents adaptive add-on control algorithms for theconventional mode of operation of MEMS z-axis gyroscopes. This scheme is realized by adding an outer loop to a conventional force-balancing scheme that includes a parameter estimation algorithm. The parameter adaptation algorithm estimates the angular rate, identifies and compensates the quadrature error, and may permit on-line automatic mode tuning. The convergence and resolution analysis show that the proposed adaptive add-on control scheme prevents the angular rate estimate from being contaminated by the quadrature error, while keeping ideal resolution performance of a conventional force-balancing scheme.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.1
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• pp.7-17
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• 1997

During the past decade, there were many well-established theories for the adaptive control of linear systems, but 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 industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.100-104
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• 1998

This paper describes the real-time implementation of an adaptive controller fur the robotic manipulator. Digital signal processors(DSPs) are special purpose micro-processors that are particularly powerful for intensive numerical computations involving sums and products of variables. TMS320C50 chips are used in implementing real time adaptive control algorithms to provide an enhanced motion for robotic manipulators. In the proposed scheme, adaptation laws are derived from the improved Lyapunov second stability analysis based on the direct adaptive control theory. The adaptive controller consists of an adaptive feedforward controller and feedback controller. 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 adaptive controller is illustrated by simulation and experimental results for a assembling robot.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.902-911
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• 2012

This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.

• Proceedings of the KIPE Conference
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• 1996.06a
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• pp.17-20
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• 1996

An adaptive current control scheme of a permanent magnet (PM) synchronous motor with the simultaneous estimation of the magnitude of the flux linkage and stator resistance is proposed. The adaptive parameter estimation is achieved by a model reference adaptive system (MRAS) technique. The adaptive laws are derived by the Popov's hyperstability theory and the positivity concept. The predictive control scheme is employed for the current controller with the estimated parameters. The robustness of the proposed current control scheme is compared with the conventional one through the computer simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.653-660
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• 2000

In this paper, an adaptive interference excision scheme with multiple adaptive filter bank using an adaptive algorithm is proposed. This scheme suppresses interference in the wavelet packet transform domain for the direct spread spectrum communication systems. Using the Monte-Carlo simulation, we analyze the performance of the direct spread spectrum communication systems with this excision scheme using LMS and RLS adaptive algorithms in AWGN and interference channel.