• Proceedings of the KSME Conference
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• 2004.04a
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• pp.852-857
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• 2004

In this paper, an angular self-sensing algorithm is proposed and implemented to a Lorentz force type integrated motor-bearing system. It is based on the principle that the flux linkages of stator windings, calculated from the voltage and torque control current, are the functions of the rotor angle. The tracking angular position error is proven to vanish using the Lyapunov stability method, and the experimental results show that the initial error decays within about 5 seconds. It is found that the resolution of the algorithm remains about 1º over the speed range of 100 to 1000 rpm.

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

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.79-84
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.26-37
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller. feedback controller. and PID type time-varying auxiliary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require a an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the ESK Conference
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• 1996.04a
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• pp.160-167
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• 1996

The early diagnosis has an very important role in curing dementia. But there was not an effective method to diagnose it until now. In this paper we analyzed the EEG in Alzheimer's disease and normal control groups to compare by nonlinear parameter such as the largest Lyapunov exponent $L_{1}$. We found that patients with Alzheimer's disease have significantly lower$L_{1}$ than normal groups. And we propose the nonlinear analysis of EEG as a useful tool for the early diagnosis of Alzheimer's disease.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.271-278
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• 2005

In this paper, we present an adaptive observer for multi-output nonlinear systems that include unknown constant parameters and are not necessarily observable. Based on generalized nonlinear observer canonical form, new adaptive observer canonical form is proposed. Sufficient conditions are given for a nonlinear system to be transformed into the proposed adaptive observer canonical form. The existence of the proposed adaptive observer is given in terms of Lyapunov-like condition and SPR condition. An illustrative example is presented to show the design procedure of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.214-218
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• 1997

We propose a VSC(Variable Structure Controller) with a PI-type reaching law. In General, conventional VSCs with a reaching law including a discontinuous term have the chattering problem, and thus the system may be unstable due to the disregarded high frequency dynamics in the modeling process. To resolve this problem, the PI-type reaching law is proposed in this paper. The proposed reaching law makes it easy to determine the reaching dynamics as well as the reaching time by utilizing the 2nd-order system analysis. Furthermore, since the discontinous term is not involved in the reaching law, the chattering is considerably reduced. To show the effectiveness of the proposed scheme, the stability of the proposed system is proved by Lyapunov method and the computer simulations are performed for the Ball Balance System.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1081-1087
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• 2006

Generally, biped walking is difficult to control because a biped robot is a nonlinear system with various uncertainties. In this paper, we propose a hybrid sliding-mode control method using a WNN uncertainty observer for stable walking of the 5-link biped robot with model uncertainties and the external disturbance. In our control system, the sliding mode control is used as main controller for the stable walking and a wavelet neural network(WNN) is used as an uncertainty observe. to estimate uncertainties of a biped robot model, and the error compensator is designed to compensate the reconstruction error of the WNN. The weights of WNN are trained by adaptation laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified through computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.151-156
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• 1998

This paper presents an $H_{\infty)$ output feedback controller design method for linear systems with delayed state, delayed control input, and delayed masurement output. Using a Lyapunov functional, the stability for delayed systems is discussed independently of delays. Also, sufficient condition for the existence of $H_{\infty)$ controllers of any order is given in terms of three linear matrix inequalities(LMIs). Based on positive definite solutions of their LMIs, we briefly explain the way to construct $H_{\infty)$ controller, which stabilizes time-delay systems independently of delays and guarantees an $H_{\infty)$norm bound.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.35-43
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• 2008

The control of underactuated mechanical system is very complex for the loss of its control inputs. The model of underactuated mechanical systems in a potential field is built with Lagrangian method and its structural properties are analyzed in detail. A genetic algorithm (GA)based stable control approach is proposed for the class of under actuated mechanical systems. The Lyapunov stability theory and system properties are utilized to guarantee the system stability to its equilibrium. The real-valued GA is used to adjust the controller parameters to improve the system performance. This approach is applied to the underactuated double-pendulum-type overhead crane and the simulation results illustrate the complex system dynamics and the validity of the proposed control algorithm.