• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.1022-1032
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• 2000

We propose a sliding mode controller tracking the states of a time-varying reference model. The reference model generates the desired trajectories of the states, and the sliding mode controller regulates robustly the errors between the desired states and the measured states. We apply this controller to the overhead crane. Its reference model generates the trajectories of the damped-out swing angle and the swing angular velocity to suppress the swinging motion caused by the acceleration and the deceleration of crane transportation. Also, this model generates the desired trajectories of the position and velocity of the crane. The crane model is identified from the experimental data using an orthogonal function. Kalman filtering is applied to estimate the crane states. The designed controller is simulated on a computer and is tested through a 2-ton industrial overhead crane using the vector-controlled servo motor system. It is verified that, from the simulated and experimental results, the sliding mode controller tracking a time-varying reference model works well.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.871-873
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• 1995

The purpose of this paper is to design and construct the compact type joint driver and controller of the biped robot. This biped robot will be designed to be suitable for the practical usages and applications in the work environment, which is not plat floor, like a stairs by taking the stand-alone style that equipped all the parts except power sources. Generally, highly nonlinear motion dynamics of the biped robot is realized to linear approximations by installing a high-ratio speed reducer at each joint and dividing motions into a several piecewise linear motions, which is realized by the digital controller design techniques. This biped robot has symmetrical structure to get the stable walking ability and also the hierachical structure to control each joint as well. That is, all of the joint controllers are connected to the main controller in the composition of overall controllers. The driver and controller of each joint uses PI controller that compensate the velocity and position errors by the data of the encoder. And the signal characteristics of each joint controller forms a trapezoid speed profile which is predefined by the values of direction, maximum velocity and position.

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.809-817
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• 2018

The model predictive controller performance of the mobile robot is set to an arbitrary value because it is difficult to select an accurate value with respect to the controller parameter. The general model predictive control uses a quadratic cost function to minimize the difference between the reference tracking error and the predicted trajectory error of the actual robot. In this study, we construct a predictive controller by transforming it into a quadratic programming problem considering velocity and acceleration constraints. The control parameters of the predictive controller, which determines the control performance of the mobile robot, are used a simple weighting matrix Q, R without the reference model matrix $A_r$ by applying a quadratic cost function from which the reference tracking error vector is removed. Therefore, we designed the predictive controller 1 and 2 of the mobile robot considering the constraints, and optimized the controller parameters of the predictive controller using a genetic algorithm with excellent optimization capability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.842-850
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• 2014

This paper presents a trajectory tracking controller for rotorcraft UAVs to improve the tracking performances in the presence of various uncertainties. The proposed tracking method consists of a velocity guidance law based on the relative distance and L1 adaptive augmentation loop for tracking the velocity commands. In the proposed structure, the desired velocity generated by the guidance law is the reference value of the adaptive controller for accurate path tracking. In the guidance law, the desired acceleration is generated based on the relative distance and its derivatives, and then the velocity command of the inner control loop is calculated by integrating the accelerations. $L_1$ augmentation loop supplements the linear controller to guarantee the flight performances such as a tracking accuracy in the presence of the uncertainties. The proposed controller was validated in actual flight tests to successfully demonstrate its capability using a quadrotor UAV.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.349-352
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• 1997

In this paper, we propose a new longitudinal controller of automated vehicles. The controller is designed based on a sliding control method, which is known to be robust to disturbances and modelling errors. Contrary to currently available sliding controller, a switching controller gain method is suggested. It is shown throughout simulations that the proposed controller reduces the amount of overshoot, which may derive smoother velocity tracking in a platoon.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.356-362
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• 2017

This paper presents a robust position controller for a one degree-of-freedom (DOF) mechanical system using only position measurement. In order to alleviate the performance degradation owing to various uncertainties, a two-stage design method is studied by employing a proportional integral observer (PIO). In the first stage, a baseline backstepping controller is designed for a nominal system without accounting for uncertainties. The PIO is developed for estimating both the velocity information for the backstepping controller and an equivalent input disturbance for a feedforward compensation using the estimated uncertainty. It is shown that the estimation errors with the proposed PIO can be made arbitrarily small in a finite time. If the system suffers from undesirable actuator nonlinearities, however, it might be necessary to estimate the velocity and the disturbance with different rates of convergence. The proposed method combines the predesigned backstepping controller and dual PIOs to reduce mechanical vibrations as well as steady-state errors. The performance of the proposed method is tested through comparative computer simulations and experiments using a laboratory prototype.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.3
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• pp.17-24
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• 2004

We present a P-type iterative learning control(ILC) scheme for uncertain robotic systems that perform the same tasks repetitively. The proposed ILC scheme comprises a linear feedback controller consisting of position error, and a feedforward and feedback teaming controller updated by current velocity error. As the learning iteration proceeds, the joint position and velocity mrs converge uniformly to zero. By adopting the learning gain dependent on the iteration number, we present joint position and velocity error bounds which converge at the arbitrarily tuned rate, and the joint position and velocity errors converge to zero in the iteration domain within the adopted error bounds. In contrast to other existing P-type ILC schemes, the proposed ILC scheme enables analysis and tuning of the convergence rate in the iteration domain by designing properly the learning gain.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1466-1474
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• 2003

This paper presents a system modeling, controller design and implementation for a rotational inverted pendulum system (RIPS), which is an under-actuated system and has the problem of unattainable velocity state. Two control strategies are applied to the RIPS. One is a sliding mode control method using the parameterization of both the hyperplane and the compensator for output feedback. The other is the disturbance observer which estimates disturbance and some modeling errors of RIPS with less computational effort. Some simulations and various kinds of experiments are performed in order to verify that the proposed controller has the ability to control RIPS whose velocity is assumed to be unavailable. The results of the simulations and experiments show that the proposed control system has superior performance for disturbance rejection and regulation at certain initial conditions as well as the robustness to model uncertainties.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.524-527
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• 1995

In most cases, a crane is controlled by an open-loop technique. That is, the controller tries to follow a given velocity profile that is designed to minimize the swing of rope and the transfer time. But such a system is not capable of handling various disturbances such as changing rope length and wind effect. In order to overcome this kind of difficulty, this research focuses on the design of a feedback controller using intelligent techniques such as fuzzy logic and neural network. These intelligent techniques has been emplyoyed in order to represent human knowledge and to imitate human learning. The deveped controllers have been evaluated via computer simulation

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.524-528
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• 2006

A controller built with the gyro effect for a balance-beam can freely control the attitude of an unstructured object by changing the position of an inner gimbal. In this paper, we propose a new balance-beam controller that can detect the inertia of the load to limit the velocity of the load commanded by a user. We found that when there was smaller load inertia, a larger restoration displacement occurred. Therefore, the load can be identified by issuing a predefined command to measure the restoration displacement, which enables us to construct a controller that can limit the angular velocity of the load by planning the motion. Experimental results show the performance of the controller with different loads.