• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.10
• /
• pp.1008-1013
• /
• 2014

This paper introduces an adaptive anti-sway tracking control algorithm for container cranes with unknown payloads and friction between the trolley and the rail. If the friction effects in the system can be modeled, there is an improved potential to design controllers that can cancel these effects. The proposed control improves the sway suppressing and the positioning capabilities of the trolley and hoisting against uncertain payload and friction. The variable structure controls are first designed based on a class of feedback linearization methods for the stabilization of the under-actuated sway dynamics. The adaptation mechanism are then designed with parameter estimation of unknown payload and friction compensation for the trolley and hoisting, based on Lyapunov stability methods for the accurate positioning and fast attenuation of trolley oscillation due to frictions in the vicinity of the target position. The asymptotic stability of the overall closed-loop system is assured irrespective of variations of rope length. Simulations are shown under various frictions and external winds in the case of no priori information of payload mass.

• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.534-539
• /
• 1988

This paper presents a method to balance the links of an articulated robot for an unknown payload using an automatic balancing mechanism. The balancing masses are controlled to move in their appropriate locations so that the joint torques of the links are eliminated. After balancing the mass of the payload is obtained from the balancing conditions. Based upon a series of simulation studies some results are discussed.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.40 no.2
• /
• pp.200-206
• /
• 1991

In this paper, an output feedback is used to reduce the effect of the vibration in the control of a flexible one-link robot arm. A PD control method with a time varying gain is proposed to improve the performance of the system in tip deflection and settling time for the step reference input. By making the change of feedback gain smoothly, th input torque can be made smooth. When there is a payload with unknown mass, an interpolation method which uses the inrehgrated value of the transient response of the hub angle is proposed for the estimation of teh payload mass. This method can be used when the reference input is known and we can get highly accurate estimate for the unknown payload. It is also demonstrated that flexible one-link arm can be controlled prettry accurately by an output feedback in a noisy environment without knowing the mass of the payload.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.2
• /
• pp.145-149
• /
• 2015

This paper introduces a sway suppression control for container cranes with unknown payloads and sway rates. With no priori knowledge concerning the magnitude of payload mass and sway rate, the proposed control maintains superior sway suppressing and trolley positioning against external disturbances. The proposed scheme combines a second order sliding mode control and an adaptive control to cope with unknown payloads. A second order sliding mode control without feedback of the sway rate is first designed, which is based on a class of feedback linearization methods for stabilization of the under-actuated sway dynamics of the container. Under applicable restrictions of the magnitude of payload inertia and sway rate, a linear regression model is obtained, and an adaptive control with a payload estimator is then designed, which is based on Lyapunov stability methods for the fast attenuation of trolley oscillations in the vicinity of the target position. The asymptotic stability of the overall closed-loop system is assured irrespective of variations of rope length. Simulation are shown in the existence of initial sway and external wind disturbances.

• Proceedings of the KIEE Conference
• /
• 1988.07a
• /
• pp.998-1001
• /
• 1988

A robust control method for robots in presented. In this method, a phase-lag controller is used for reducing the effect of the unknown payload without the measurement of joint accelerations and torque/force. Simulation results for the lower 3 joints of PUMA 560 show considerable reduction of position errors due to the unknown payload, compared to the computed-torque method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.177-182
• /
• 1989

In this paper a new adaptive control algorithm is derived, with the unknown manipulator and payload parameters being estimated online. In practice, we may simplify the algorithm by not explicity estimating all unknown parameters. Further, the controller must be robust to residual time-varying disturbance, such as striction or torque ripple. Also, the reference model is a simple douple integrator and the acceleration input for robot manipulator consists of a proportion and derivative controller for trajectory tracking purposes. The validity of this control is confirmed in simulation where two-link robot manipulator shows the robust performances in spite of the existing nonlinear interaction and unknown parametrictings

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.04a
• /
• pp.427-431
• /
• 1996

A modeling of the dynamics of two cooperating robot manipulators doing assembly job such as peg-in-hole while coordinating the payload along the desired path is proposed. The system is uncertain due to the unknown mass and moment of inertia of the manipulators and the payload. To control the system, a robust control algorithm is proposed. The control algorithm includes fuzzylogic. By the fuzzy logic, the magnitude of the input torque of the manipulators is controlled not to go over the hardware saturation with keeping path tracking errors bounded.

• Journal of Advanced Marine Engineering and Technology
• /
• v.22 no.4
• /
• pp.498-504
• /
• 1998

This paper presents an optimal control algorithm for the overhead crane. To control the swing motion and the position tracking of the payload of the overhead crane a state feedback control algorithm is applied. by using a hybrid genetic algorithm the feedback gains of the state feedback is optimized to minimize the cost function composed of position errors and payload swing angle under unknown constant disturbances. Computer simulation is performed to demonstrate the effectiveness of the proposed control algorithm.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.2
• /
• pp.160-168
• /
• 1997

A $H_{\infty}$self-tuning control scheme for the tip position of a flexible link robot handling unknown loads is presented here. The scheme essentially comprises a recursive least-squares identification algorithm and $H_{\infty}$self-tunning controller. The $H_{\infty}$control low is designed to be robust to uncertain parameters and the self-tunning action provides adaption to unknown parameters. Through numerical study, the performance comparison of the $H_{\infty}$self-tuning controller with a constant gain $H_{\infty}$controller as well as a LQG self-tuning controller clearly shows its superior ability in handling load changes in quiescent states.nt states.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.4
• /
• pp.669-677
• /
• 2020

As the number of Internet users exploded, attacks on the web increased. In addition, the attack patterns have been diversified to bypass existing defense techniques. Traditional web firewalls are difficult to detect attacks of unknown patterns.Therefore, the method of detecting abnormal behavior by artificial intelligence has been studied as an alternative. Specifically, attempts have been made to apply natural language processing techniques because the type of script or query being exploited consists of text. However, because there are many unknown words in scripts and queries, natural language processing requires a different approach. In this paper, we propose a new classification model which uses byte pair encoding (BPE) technology to learn the embedding vector, that is often used for web attack payloads, and uses an attention mechanism-based Bi-GRU neural network to extract a set of tokens that learn their order and importance. For major web attacks such as SQL injection, cross-site scripting, and command injection attacks, the accuracy of the proposed classification method is about 0.9990 and its accuracy outperforms the model suggested in the previous study.