• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.316-318
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• 1992

The proposed algorithm uses a modified adaptive law which consists of switching -modification, normalized augmented error and low-pass filtered signal of output tracking error, furthermore, the proportional term that is a product of the output tracking error and the bounded signal having an information of output tracking error is added to the conventional control law for improvement of robustness and performance of an adaptive system. For the arbitrary nth order system, mathematical analysis and computer simulation are used to demonstrate improvement of output error characteristics, guaranteeing boundedness of all signals in the overall system.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.394-396
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• 1992

This note is concerned with the point to point control of manipulators having elastic joints. We present a PD control algorithm which is adaptive with respect to the gravity and elastic parameters of robot manipulators. While the conventional control law is used, a new adaptive law is used to improve the performance. The proposed controller is shown to be stable. It is Shown that steady-state position error converges to zero through some simulations concerning the manipulator with three revolute elastic joints.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.781-787
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• 1999

In this note, we propose two methods of adaptive sliding mode control(SMC) schemes in which fuzzy systems(FS) are utilized to approximate the unknown system functions. In the first method, a FS is utilized to approximate the unknown function f of the nonlinear system $\chi$$^{(n)}$$\chi$＝f(equation omitted), t)＋b(equation omitted), t)u and the robust adaptive law is proposed to reduce the approximation errors between the true nonlinear function and fuzzy approximator, FS. In the second method, two FSs are utilized to approximate f and b, respectively. The robust control law is also designed. The stabilities of proposed control schemes are proved.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.337-346
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• 2004

The control scheme using fuzzy modeling and Parallel Distributed Compensation (PDC) concept is proposed to provide asymptotic tracking of a reference signal for the flexible joint manipulators with uncertain parameters. From Lyapunov stability analysis and simulation results, the developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop multi-input/multi-output system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.739-744
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• 2004

This paper presents an adaptive approach to control the amount of slip of the torque converter bypass clutch using its estimated friction coefficient. The proposed approach can be readily implemented using the inexpensive speed sensors currently installed in an automobile. A measurement feedback control law to drive the slip error to zero together with an adaptation law to identify the unknown friction coefficient is developed using the Lyapunov control design method. The robustness of the control and adaptation laws to parametric and/or torque uncertainties as well as the convergence of the friction coefficient are investigated. Simulation results verify the viability of the proposed control algorithm in real-world vehicle control applications.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.51-60
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• 2007

This paper describes a visual tracking control law of an Unmanned Aerial Vehicle(UAV) for monitoring of structures and maintenance of bridges. It presents a control law based on computer vision for quasi-stationary flights above a planar target. The first part of the UAV's mission is the navigation from an initial position to a final position to define a desired trajectory in an unknown 3D environment. The proposed method uses the homography matrix computed from the visual information and derives, using backstepping techniques, an adaptive nonlinear tracking control law allowing the effective tracking and depth estimation. The depth represents the desired distance separating the camera from the target.

• Proceedings of the KIEE Conference
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• summer
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• pp.821-823
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• 2004

In this paper, a backstepping speed controller applied in SRM is presented. The driver of SRM is generally planned with a PI controller. A PI controller is becomes a satisfied structure in the system. it is used in position and speed control loops. However, when the system parameter uncertainties large inertia and load disturbance, it will not be able to expect a satisfied efficiency. Therefore, a backstepping control law was researched, which is able application even to a linear system as well as a nonlinear and it is more excellent than a origin adaptive control law. In this paper, a backstepping control law applied the drive system of SRM was used in the drive controller. The computer simulation result clearly show that the applied backstepping controller can track the speed reference signal generated by internal signals.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.144-147
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• 2001

This paper presents adaptive fuzzy controller which is uncertainty or unknown variation in different parameters with nonlinear system of helicopter. The proposed adaptive fuzzy controller applied TSK(Takagi-Sugeno-Kang) fuzzy system which is not only low number of fuzzy rule, and a linear input-output equation with a constant term, but also can represent a large class of nonlinear system with good accuracy. The adaptive law was designed by using Lyapunov stability theory. The adaptive fuzzy controller is a model reference adaptive controller which can adjust the parameter $\theta$ so that the plant output tracks the reference model output. First of all, system of helicopter was considered as stopping state, and design of controller was simulated from dynamics equation with stopping state. Results show that it is controlled more successfully with a model reference adaptive controller than with a non-adaptive fuzzy controller when there is a modelling error between system and model or a continuous added noise in such unstable system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.446-449
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• 1997

We propose a control law in discrete time domain of the bilateral feedback teleoperation system using neural network and the reference model type of adaptive control. Different from traditional teleoperation systems, the transmission time delay irregularly changes. The proposed control method controls master and slave systems through identification of master and slave models using neural networks.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1-7
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• 1993

In this paper we propose the new adaptive control algorithm by using S-G algorithm based on the error equations derived by Slotine. We verify the validity of the proposed controller and convergence of three type parameter estimation law based on S-G algorithm from the computer simulation.