• Journal of KSNVE
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• v.7 no.3
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• pp.439-447
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• 1997

In this study, the dynamic instabilities of a nonlinear elastic system subjected to follower forces are investigated. The two-degree-of-freedom double pendulum model with nonlinear geometry, cubic spring, and linear viscous damping is used for the study. The constant, the initial impact forces acting at the end of the model are considered. The chaotic nature of the system is identified using the standard methods, such as time histories, power density spectrum, and Poincare maps. The responses are chaotic and unpredictable due to the sensitivity to initial conditions. The sensitivities to parameters, such as geometric initial imperfections, magnitude of follower force, direction control constant, and viscous damping, etc., are analysed. Dynamic buckling loads are computed for various parameters, where the loads are changed drastically for the small change of parameters.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.251-256
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• 2000

This paper presents dynamic modeling and controller design of a tracked vehicle installed with the double-rod type ERSU(electro-rheological suspension unit). A 16 DOF(degree-of-freedom) model for the tracked vehicle is established by Lagrangian method. After showing the spring and damping characteristics of the proposed ERSU, equivalent 2 DOF 1/12 tracked vehicle model is then formulated by regarding the spring and viscous damping coefficients under the static state as constant values. A robust LSDP(loop-shaping design procedure) $H_{\infty}$ controller compensating spring and damping parameter variations is then designed in order to suppress unwanted vibration of the vehicle. The control responses such as vertical and pitch acceleration are presented in time domain.

• Journal of the Korea Safety Management & Science
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• v.9 no.1
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• pp.145-156
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• 2007

This paper is to propose model classification and evaluation of measurement uncertainty. In order to obtain type A and B uncertainty, variety of measurement mathematical models are illustrated by example. The four steps to evaluate expanded uncertainty are indicated as following; First, to get type A standard uncertainty, measurement mathematical models of single, double, multiple, design of experiment and serial autocorrelation are shown. Second, to solve type B standard uncertainty measurement mathematical models of empirical probability distributions and multivariate are presented. Third, type A and B combined uncertainty, considering sensitivity coefficient, linearity and correlation are discussed. Lastly, expanded uncertainty, considering degree of freedom for type A, B uncertainty and coverage factor are presented with uncertainty budget. SPC control chart to control expanded uncertainty is shown.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1197-1204
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• 2008

This paper presents an asymptotic formation control scheme for a group of underactuated autonomous underwater vehicles (AUVs) where only three control inputs - surge force, yaw moment and pitch moment are available for each vehicle's six degree of freedom (DOF) underwater motion. Usually, the dynamics agents applied in most of the formation algorithms presented so far have been modeled as particle systems, which is a simple double-integrator system. Therefore, these algorithms cannot be directly applicable to the practical systems, especially to the underwater vehicles whose dynamics are highly nonlinear. Moreover, the vehicles considered in this paper are underactuated. The formation control is derived using general potential function method, and the corresponding potential function consists of two parts: interactions between vehicles and virtual-leader following. Proposed formation scheme guarantees asymptotic local stability of closed-loop system. Numerical simulations are carried out to illustrate the effectiveness of proposed formation scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.153-156
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• 1999

The technique is reported of identifying parameters in off-line process. The technique demands that closed-loop system consists of a reference and two-degree-of-freedom controllers (TDFC) in real process. A model process is the same as the real process except their parameters. Deviations are differences between the reference and the output of the plant or the model. The technique is based on minimizing identification error between the two deviations. The parameter differences between the plant and the model are characterized of mean value and of variance which are derived from the identification error. Consequently, the algorithm which identifies the unknown plant parameters is shown by minimizing the mean value and the variance, respectively, within double convergence loops. The technique is applied to course change of a ship. The plant deviation at the first trial is shown to occur in replacing the nominal parameters by the default parameters. The plant deviation at the second trial is shown to not occur in replacing the nominal parameters by the identified parameters. Hence, the identification technique is confirmed to be feasible in the real field.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.3
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• pp.209-219
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• 1997

A fuzzy driver model based on a preview-predictor and yaw rate is developed. The model is used to investigate the handling performance of two wheel steering system(2WS) and four wheel steering system(4WS) vehicles. The two degree-of- freedom model which has yaw and lateral motion predicts the path of the vehicles. Based upon the yaw rate and lateral deviations, the fuzzy engine describes the human driver's complicated control behavior which is adjusted for the driving environment. Both typical single lane change maneuver and double lane change maneuver are adopted to demonstrate the feasibility of fuzzy driver model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.1960-1969
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• 1999

This paper presents dynamic modeling and controller design of a tracked vehicle installed with the double rod type ERSU(electro-rheological suspension unit). A 16 degree-of-freedom model for the tracked vehicle is established by Lagrangian method followed by the formulation of a new sky-ground hook controller. This controller takes account for both the ride quality and the steering stability. The weighting parameter between the two performance requirements is adopted to adjust required performance characteristics with respect to the operation conditions such as road excitation. The parameter is appropriately determined by employing a fuzzy algorithm associated with the vehicle motion. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control system. Acceleration values at the driver's seat are analyzed under bump road profile, while frequency responses of vertical acceleration are investigated under random road excitation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.5 s.248
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• pp.550-559
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• 2006

This paper presents designs and performance investigations of two bypass-type MR (magneto-rheological) shock dampers for high impulsive force systems, one of which is with single rod and the other with double rod. First of all, on the basis of the Bingham properties of the MR fluid and the magnetic field analysis of the magnetic circuit, the MR shock dampers are designed and manufactured. After experimental investigations on their magnetic field-dependent damping forces and responses characteristics, dynamic models of the proposed dampers are formulated and compared. Then, a simple 1 degree-of-freedom mass-drop system is constructed, and the effective and practical control algorithm is designed by considering dynamic characteristics of the shock control system. The shock control performances of the proposed MR shock dampers are verified through the comparison study of experiment results with simulation ones.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.8
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• pp.9-18
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• 2022

As the COVID-19 continues, the demand for robotic technology that can be applied in face-to-face tasks such as delivery and transportation, is increasing. Although these technologies have been developed and applied in various industries, the robots can only be operated in a tidy indoor environment and have limitations in terms of payload. To overcome these problems, we developed a 2 degree of freedom(DOF) environmental adaptive robot leg with a double 1-DOF counterbalance mechanism (CBM) based on wire roller. The double 1-DOF CBM is applied to the two revolute joints of the proposed robot leg to compensate for the weight of the mobile robot platform and part of the payload. In addition, the link of the robot leg is designed in a parallelogram structure based on a belt pulley to enable efficient control of the mobile platform. In this study, we propose the principle and structure of the CBM that is suitable for the robot leg, and design of the counterbalance robot leg module for the environment-adaptive control. Further, we verify the performance of the proposed counterbalance robot leg by using dynamic simulations and experiments.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.270-282
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• 2015

A submerged body moving near the free surface needs to maintain its attitude and position to accomplish missions. It is necessary to validate the performance of a designed controller before a sea trial. The hydrodynamic coefficients of maneuvering are generally obtained by experiments or computational fluid dynamics, but these coefficients have uncertainty. Environmental loads such as the wave exciting force and suction force act on the submerged body when it moves near the free surface. Thus, a controller for the submerged body should be robust to parameter uncertainty and environmental loads. In this paper, the six-degree-of-freedom equations of motions for the submerged body are constructed. The suction force is calculated using the double Rankine body method. An adaptive control method based on an artificial neural network and proportional-integral-derivative control are used for the depth controller. Simulations are performed under various depth and speed conditions, and the results show the effectiveness of the designed controller.