• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.734-738
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• 1996

An adaptive output feedback controller is designed for tracking control of an n-link robot manipulator with unknown load. High-gain observers with same structure as error dynamic systems are used to estimate joint velocities. The parameter adaptation is achieved by the smoothed projection algorithm. The control inputs are saturated outside a domain of interest. Simulation results on a 2-link manipulator illustrate that when the speed of the high-gain observer is sufficiently high, the proposed controller recovers the performance under state feedback control.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1295-1298
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• 2003

The steam generator level in a PWR is very difficult to control particularly at low power. And the constant control gain and time value are not adaptive in steam generator level controller. In normal operation constant control gain and time value have no problem. But there is problem at low power. So variable control gains based on the temperature are required. The best control gain is decided by the experienced knowledge. A fuzzy gain tuner is used for the gain tuning. In the design of fuzzy gain-tuner processing, the experienced knowledge is employed for making fuzzy rules.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.12
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• pp.65-73
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• 2007

In this paper, the gain scheduled state feedback and disturbance feedforward control design proposed in the previous paper has been applied to a simple matching system and a turret stabilization system. In such systems, it is needed to attenuate disturbance response effectively as long as control input satisfies the given constraint on its magnitude. The scheduled control gains are derived in the framework of linear matrix inequality(LMI) optimization by means of the MatLab toolbox. Its effectiveness is verified along with the simulation results compared with the conventional optimum constant gain control and the scheduled state feedback control cases.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.141.1-141
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• 2001

This paper describes an approach for synthesizing a modularized gain scheduled PD type fuzzy logic controller(FLC) for a high maneuverable aircraft system, where the gains of FLC are on-line adapted according to the flight condition. Specially, the systematic procedure via root locus technique is carried out for the sellection of the gains of FLC. Simulation results demonstrate that the proposed gain scheduled fuzzy logic controller yields better control performance than the normal (without gain scheduling) fuzzy controller.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.428-430
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• 1997

An LQG/LTR based gain scheduling control scheme for the two link inverted pendulum is presented. It is shown by simulation that the gain scheduling scheme based on the robust linear control theory still preserves the robust property of the linear control scheme and can be applied to control a class of nonlinear systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.65-70
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• 2011

The increased disk rotational velocity to improve the data transfer rate has raised up many serious problems in its servo control system which should control the position and velocity of a spot relative to a rotating disk. This paper proposes gain-scheduling-based track-seek control for single stage actuator of hard disk drives. Gain scheduling is a technique that can extend the validity of the linearization approach to a range of operating points and one of the most popular approaches to nonlinear control design. The proposed method schedules controller gains to improve the transient response and minimize overshoot during the functions of the read/write head positioning servomechanism for the seek control. The validity of the proposed method is demonstrated through stability analysis and simulation results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2319-2324
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• 2005

This paper proposes a intelligent gain and boundary layer based sliding mode control (SMC) method for robotic systems with unknown model uncertainties. For intelligent gain and boundary layer, we employ the self recurrent wavelet neural network (SRWNN) which has the properties such as a simple structure and fast convergence. In our control structure, the SRWNNs are used for estimating the width of boundary layer, uncertainty bound, and nonlinear terms of robotic systems. The adaptation laws for all parameters of SRWNNs and reconstruction error bounds are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with unknown uncertainties. Accordingly, the proposed method can overcome the chattering phenomena in the control effort and has the robustness regardless of unknown uncertainties. Finally, simulation results for the three-link manipulator, one of the robotic systems, are included to illustrate the effectiveness of the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.6
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• pp.25-35
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• 1999

This paper presents a control gain tuning scheme for multi-axis PID control systems by Taguchi method. As an experimental set-up, a parallel mechanism machine tool has been selected. This machine has eight servodrives and each servodrive has four control gains, respectively. Therefore, total 32 control gains have to be tuned. Through a series of design of experiments, an optimal and robust set of PID control gains is tuned. The index of the sum of position error and velocity error is reduced to 61.4% after the experimental gain tuning regardless of the feedrate variation.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.8-14
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• 2000

In this paper, three adaptive sliding mode control algorithms, which self-tune both the sliding mode gain and the boundary layer thickness, are proposed. The first algorithm uses a gain adaptation rule is combined with the boundary layer thickness adaptatioin rule to satisfy the sliding condition. In the third algorithm, the computation burden of the second algorithm is reduced further, and therefore no extra cost is required for real-time implementation. Due to the mixed sliding mode gain and the boundary layer thickness adaptation scheme, the tracking error and the chattering of the control input can be reduced greatly.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.212-220
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• 2020

This paper deals with a strategy of gain optimization for the kinematic control algorithm of a wire-driven surgical robot. The proposed controller consists of the closed-loop inverse kinematics with the back-calculation method. The closed-loop inverse kinematics has 18 PID control gains, and the back-calculation method has 6 gains. An efficient strategy is designed to optimize 18 values first and then the remaining 6 values. The optimal gain sets are searched under the step input with performance indices. In this gain optimization, the objective function is defined as the minimum value of signal-to-noise ratio of the performance indices for 6 DoF (Degree-of-Freedom) motion that is based on the Taguchi method, and the constraints are applied to obtain stable responses for each motion evenly. The gain sets obtained are verified by simulations using the test trajectories. In comparative results, the optimal gain value based on the performance index combined with ISE (integral of square error) and settling time showed the best control performance.