• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.76-83
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• 1996

We have developed the unconventional robot arm which is composed of the two main parts, one is a ball screw and the other is a robot arm. The dynamic systems of the robot arm and ball screw are unstable systems coupled with each other. The ball screw mechanism is unstable system but controllable system. The robot arm's dynamics is quasi stable system when ball screw's angular position is zero, else, unstable system. Our system has the duality between stability and controllability at the view point of control. This duality causes difficulty to control of the robot arm using normal control law. We have investigated the location of the characteristic roots of the dynamic equation. And we have found out that the best condition for the control of the arm is quasi stable state. In this paper, we have proposed multiple control laws which are consist of three components to guarantee the stability and controllability simultaneously. The computer simulations were carried out based on VSC about the angular position control of the robot arm, and it is confirmed that the good performances could be obtained by using new controller.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.612-619
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• 2005

A robust adaptive speed sensorless induction motor direct torque control (DTC) using a neural network (NN) is presented in this paper. The inherent lumped uncertainties of the induction motor DTC system such as parametric uncertainty, external load disturbance and unmodeled dynamics are approximated by the NN. An additional robust control term is introduced to compensate for the reconstruction error. A control law and adaptive laws for the weights in the NN, as well as the bounding constant of the lumped uncertainties are established so that the whole closed-loop system is stable in the sense of Lyapunov. The effect of the speed estimation error is analyzed, and the stability proof of the control system is also proved. Experimental results as well as computer simulations are presented to show the validity and efficiency of the proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1853-1856
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• 2003

This paper considers the problem of longitudinal control of a platoon of automotive vehicles on a straight lane of a highway and proposes control laws in the event of loss of communication between the lead vehicle and the other vehicles in the platoon. Since safety plays a key role in the development of an Automated Highway System, fault-tolerant control is vital. In this paper, we develop a control algorithm in vehicle platooning and prove that this control algorithm is stable for certain class of faults such as parameter uncertainties. The performance of the controller is demonstrated through a series of simulations incorporating various vehicles and AHS faults. Results of simulation shows that the vehicles have good performance in spite of simple automotive and AHS failure, such as actuator failure,that is to say, engine input failure, communication failure between lead vehicle and the another vehicles.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1086-1092
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• 2000

To realize a visual servo control of slender manipulators, two problems to be solved are analysed. The stability problem on so-called noncolocation control and the infinite order problem of the real Jacobian matrix caused by the elastic deformation are discussed. By considering the dynamic relations between rigid and elastic modes, a Jacobian operator is derived and the physical meaning is also explained. Then, for practical control, a simple control scheme using an approximate Jacobian is proposed and its stable conditions are proven by means of the $L_$2$ stability theory. The scheme is structurally similar to the conventional PD control laws, but external sensors(e. g. visual sensor) are used for positioning and internal sensors for damping. A good performance is obtained via control experiments of a slender two link manipulator.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.830-831
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• 2011

The paper makes an investigation on a speed and stator flux linkage estimator for permanent magnet synchronous motor (PMSM) sensorless drives using the technology of model reference adaptive system (MRAS). The designed estimator including two models and two adaptive estimating laws is proved to be stable by the Popov hyper-stability theory. The speed, the stator flux linkage and the resistance are estimated accurately by the proposed estimator while overcoming the shortcoming of the traditional one. The experiment results demonstrate its effectiveness.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.8
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• pp.647-655
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• 2001

In adaptive neuro-control, neural networks are used to approximate unknown plant nonlinearities. Until now, most of the studies in the field of controller design for nonlinear system using neural network considers the affine system with fixed number of neurons. This paper considers nonaffine nonlinear systems and on-line variation of the number of neurons. A control law and adaptive laws for neural network weights are established so that the whole system is stable in the sense of Lyapunov. In addition, at the expense of th input, tracking error converges to the arbitrary small neighborhood of the origin. The efficiency of the proposed scheme is shown through simulations ofa simple nonaffine nonlinear system.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1860-1861
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• 2006

In this paper, we design a robust controller of biped robot system with uncertainties, using recurrent neural network. In our proposed control system, we use the self-recurrent wavelet neural network (SRWNN). The SRWNN makes up for the weak points in wavelet neural network(WNN). While the WNN has fast convergence ability, it dose not have a memory. So the WNN cannot confront unexpected change of the system. However, the SRWNN, having advantage of WNN such as fast convergence, can easily encounter the unexpected change of the system. For stable walking control of biped robot, we use sliding mode control (SMC). Here, uncertainties are predicted by SRWNN. The weights of SRWNN are trained by adaptive laws based on Lyapunov stability theorem. Finally, we carry out computer simulations with a biped robot model to verify the effectiveness of the proposed control system,.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.741-746
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• 1987

Solar cell which transforms the light energy into the electric energy from Sun comes into prominence as a new energy for next generation. However, it is difficult to obtain the stable output voltage and current from the solar cell due to the uncertainty in weather conditions, etc, In the present paper, two types of control laws are considered for regulating the input voltage in a photovoltaic energy storage system such as the system with the super conducting magnetic energy storage. (1) Oone is the design of optimal controller. (2) The other is that of weighted minimum prediction error controllers (weighted one-step ahead controllers). Simulation study for the above controllers is performed to see how they work and to get preliminary knowledge in the regulation of the input voltage to the experimental photovoltaic energy storage system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1871-1876
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• 2005

In this paper, We present a new nonlinear adaptive control law using a disturbance accommodating control (DAC) observer for a Japanese automatic landing flight experiment vehicle called ALFLEX. A future spaceplane must have ability to deal with greater fluctuations in the stability and control derivatives of flight dynamics, because its flight region is much wider than that of conventional aircraft. In our previous studies, digital adaptive flight control systems have been developed based on a linear-parameter-varying (LPV) model depending on dynamic pressure, and obtained good simulation results. However, under previous control laws, it is difficult to accommodate uncertainties represented by disturbance and nonlinearity, and to design a stable flight control system. Therefore, in this study, we attempted to design a nonlinear adaptive control law using the DAC Observer and inverse dynamic methods. A good tracking property of the obtained system was confirmed in numerical simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1516-1520
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• 2005

We proposed the indirect adaptive fuzzy model based sliding mode controller to control a nonaffine nonlinear systems. Takagi-Sugano fuzzy system is used to represent the nonaffine nonlinear system and then inverted to design the controller at each sampling time. Also sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. The proposed controller and adaptive laws guarantee that the closed-loop system is stable in the sense of Lyapunov and the output tracks a desired trajectory asymptotically.