• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. 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 perfor-mance 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.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.765-772
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• 2020

A lot of studies to overcome the limitation of flight time have been studied, since the requirement of complicated mission achievement of aircraft including Unmanned Aerial Vehicles(UAVs) has been increased. The fuel limitation could bring about not enough flight time to accomplish missions. For this reason, the rendezvous maneuver is required to accomplish aerial refueling missions. The rendezvous guidance law based on variable pursuit guidance is designed using Lyapunov stability theory in this study. Numerical simulation is performed to demonstrate the performance of the proposed rendezvous guidance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.2
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• pp.343-348
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• 2001

In this paper we propose a noise reduction algorithm which based on cellular automata with the local median rule. It is supposed that there is no information about the features of the image that must be improved. The proposed method behavior is to locally increase or decrease the gray level differences of the image without loss of the main characteristics of the image. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. We have found that the automata present very fast convergence to fixed points, stability in front of random noisy images. Based on the experimental results we discuss the advantage and efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.327-335
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• 2003

Cellular Automata is discrete dynamical systems which natural phenomena may be specified completely in terms of local relation. In this Paper we Propose noise removal and edge detection algorithm using a Potts Automata which is based on Cellular Automata. The proposed method is aimed to locally increase or decrease the differences in gray level values between pixel of the image without loss of the main characteristics of the image. The dynamical behavior of these automata is determined by Lyapunov operators for sequential and parallel update. We have found that proposed automata rules Present very fast convergence to fixed points, stability in front of random noisy images. Based on the experimental results we discuses the advantage and efficiency.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.564-570
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• 2003

This paper presents an adaptive fuzzy control scheme for nonlinear helicopter system which has uncertainty or unknown variations in parameters. The proposed adaptive fuzzy controller is a model reference adaptive controller. The parameters of fuzzy controller are adjusted so that the plant output tracks the reference model output. It is shown that the adaptive law guarantees the stability of the closed-loop system by using Lyapunov function. Several experiments with a small model helicopter having parameter variations are performed to show the usefulness of the proposed adaptive fuzzy controller.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.156-165
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• 2003

This paper describes the design of a robust adaptive fuzzy observer for uncertain nonlinear dynamical system. We propose a new method in which no strictly positive real (SPR) condition is needed. No a priori knowledge of an upper bound on the lumped uncertainty is required. The Lyapunov synthesis approach is used to guarantee a semi-global uniform ultimate boundedness property of the state observation error, as well as of all other signals in the closed-loop system. The theoretical results are illustrated through a simulation example of a mass-spring-damper system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.3
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• pp.39-46
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• 2005

In this paper, adaptive higher harmonic control technique using Neural Networks (NN) is proposed. First, linear transfer function is estimated to relate the input harmonics and output harmonics, then NN which has the universal function approximation property is applied to expand application range of the transfer function. Optimal control gain matrix computed from the transfer function is used to train NN weights. Online weight adaptation laws are derived from Lyapunov's direct method to guarantee internal stability. Results of the simulation of 6-input 2-output nonlinear system show that adaptive HHC is applicable to the system with uncertain transfer function.

• Korean Journal of Applied Biomechanics
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• v.31 no.1
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• pp.30-36
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• 2021

Objective: The objective of the present study was to analyze the relationship between strength of the lower extremity's joints and their local dynamic stability (LDS) of gait in elderly women. Method: Forty-five elderly women participated in this study. Average age, height, mass, and preference walking speed were 73.5±3.7 years, 153.8±4.8 cm, 56.7±6.4 kg, and 1.2±0.1 m/s, respectively. They were tested torque peak of the knee and ankle joints with a Human Norm and while they were walking on a treadmill at their preference speed for a long while, kinematic data were obtained using six 3-D motion capture cameras. LDS of the lower extremity's joints were calculated in maximum Lyapunov Exponent (LyE). Correlation coefficients between torque of the joints and LyE were obtained using Spearman rank. Level of significance was set at p<.05. Results: Knee flexion torque and its LDS was negatively associated with adduction-abduction and flexion-extension movement (p<.05). In addition, ratio of the knee flexion torque to extension and LDS was negatively related to internal-external rotation. Conclusion: In conclusion, knee flexion strength should preferentially be strengthened to increase LDS of the lower extremity's joints for preventing from small perturbations during walking in elderly women.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.208-213
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• 2013

The problem of finding control laws for underactuated systems has attracted growing attention since these systems are characterized by the fact that they have fewer actuators than the degrees of freedom to be controlled. A sliding mode control based on the theory of variable structure systems is a robust methodology to control nonlinear systems. In this paper, a sliding mode control with integral sliding function is proposed and asymptotical stability is proved in the Lyapunov's sense for underactuated systems. In order to verify the effectiveness of the proposed control, computer simulations for an acrobot, which is a representative underactuated system, are performed. Using Mathworks' Simulink/Simscape, the acrobot dynamics is implemented and the proposed control is composed. Simulations demonstrate the effectiveness and usefulness of the proposed control.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.28-35
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• 2012

This paper presents the method for $H_{\infty}$ fuzzy controller design of discrete-time fuzzy Markovian jump systems with state and input time delays. The Takagi and Sugeno fuzzy model is employed to represent a delayed nonlinear system that possesses Markovian jump parameters. A stochastic mode dependent Lyapunov function is employed to analyze the stability and $H_{\infty}$ disturbance attenuation performance of the fuzzy Markovian jump systems with state and input time delays. A sufficient condition for the existence of fuzzy $H_{\infty}$ controller is given in terms of matrix inequalities. Also numerical example is presented to illustrate the efficiency of the proposed design method.