• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.693-698
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• 2004

In this paper, an iterative learning control method is applied to suppress a vibration of a 2-mass system which has a flexible coupling between a load and a motor. More specifically, conditions for the load speed without vibration are derived based on the steady-state condition. And the desired motor position trajectory is synthesized based on the relation between the load and motor speed. Finally, a PD-type iterative learning control law is applied for the desired motor position trajectory. Since the learning law applied for the desired trajectory guarantees the perfect tracking performance, the resulting load speed shows no vibration even when there exist model uncertainties. A modification to the learning law is also Presented to suppress undesired effects of an initial position error, The simulation results show the effectiveness of the proposed learning method.

• ETRI Journal
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• v.39 no.3
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• pp.353-363
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• 2017

Recently, sink mobility has been shown to be highly beneficial in improving network lifetime in wireless sensor networks (WSNs). Numerous studies have exploited mobile sinks (MSs) to collect sensed data in order to improve energy efficiency and reduce WSN operational costs. However, there have been few studies on the effectiveness of MS operation on WSN closed operating cycles. Therefore, it is important to investigate how data is collected and how to plan the trajectory of the MS in order to gather data in time, reduce energy consumption, and improve WSN network lifetime. In this study, we combine two methods, the cluster-head election algorithm and the MS trajectory optimization algorithm, to propose the optimal MS movement strategy. This study aims to provide a closed operating cycle for WSNs, by which the energy consumption and running time of a WSN is minimized during the cluster election and data gathering periods. Furthermore, our flexible MS movement scenarios achieve both a long network lifetime and an optimal MS schedule. The simulation results demonstrate that our proposed algorithm achieves better performance than other well-known algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3197-3218
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• 2012

Compared with traditional itinerary planning, intention-oriented itinerary recommendations can provide more flexible activity planning without requiring the user's predetermined destinations and is especially helpful for those in unfamiliar environments. The rank and classification of points of interest (POI) from location-based social networks (LBSN) are used to indicate different user intentions. The mining of vehicles' physical trajectories can provide exact civil traffic information for path planning. This paper proposes a POI category-based itinerary recommendation framework combining physical trajectories with LBSN. Specifically, a Voronoi graph-based GPS trajectory analysis method is utilized to build traffic information networks, and an ant colony algorithm for multi-object optimization is implemented to locate the most appropriate itineraries. We conduct experiments on datasets from the Foursquare and GeoLife projects. A test of users' satisfaction with the recommended items is also performed. Our results show that the satisfaction level reaches an average of 80%.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.9
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• pp.138-148
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• 1996

In moving structures such as robots and feeders of production lines, vibrations may not be ignored. Recently it becomes a big problem to control the vibration in a motion because moving structures are in higher speed, larger size and lighter weight. In this study a nonlinear system was model- led and identified by using neural networks and the vibration in motions was controlled actively by using a neural network controller. To investigate vilidity of this method, an experimental apparatus was made and tested. The model was composed of a DC servomotor, a carrier and a flexible plate. Its motion was measured by a gap sensor and an encoder. Trapezoidal, cycloid and trapecloid type trajectories were used in this exper- riment. Computer simulations and experiments weredone for each trajectory.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.539-541
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• 2006

Biped locomotion is a popular research area in robotics due to the high adaptability of a walking robot in an unstructured environment. When attempting to automate the motion planning process for a biped walking robot, one of the main issues is assurance of dynamic stability of motion. This can be categorized into three general groups: body stability, body path stability, and gait stability. A zero moment point (ZMP), a point where the total forces and moments acting on the robot are zero, is usually employed as a basic component for dynamically stable motion. In this rarer, learning based neuro-fuzzy systems have been developed and applied to model ZMP trajectory of a biped walking robot. As a result, we can provide more improved insight into physical walking mechanisms.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.546-551
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• 1993

A new robust sliding mode controller is formulated for the tip position control of a single-link flexible manipulator with parameter variations. After establishing the plant model characterized by a noncollocated uncertain control system, a sliding surface which guarantees stable sliding mode motion is synthesized in an optimal manner. The surface is then modified to adapt arbitrarily given initial conditions. A discontinuous control law associated with the modified surface is designed by restricting that velocity state variables are not available from direct sensor measurements. Using the proposed control law favorable system responses are accomplished through shortening the reaching phase of state trajectory without increasing maximum control torque as well as undesirable chattering. Furthermore, a low sensitiveness to uncertainties is obtained from inherent salient properties of the proposed control system. Computer simulations are undertaken in order to demonstrate these superior control performance characteristics to be accrued from the proposed methodology.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.152-155
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• 1994

The presence of joint elasticity or the arm flexibility causes low damped oscillatory position error along a desired trajectory. We utilize a stochastic model for describing the fast dynamics and the approximation error. A second order shaping filter is synthesized such that its spectrum matches that of the fast dynamics. Augmenting the state vector of slow part with that of shaping filter, we obtain a nonlinear dynamics to which a Gaussian white noise is injected. This modeling approach leads us to the design of an extended Kalman filter(KEF) and a linear quadratic Gaussian(LQG) control scheme. We present the simulation results of this control method. The simulation results show us that our Kalman filtering approach is one of prospective methods in controlling the flexible arms.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.21-24
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• 1999

There-have been many control strategies for the enact joint position tracking of flexible manipulators, but direct cartesian space tracking control methods an not developed well. In this paper, we propose a PD control method based on the cartesian error in the end point trajectory tracking. the proposed controller is composed of PD control combined with nonlinear saturation term hut has a very simple form. the effect of this term is continuous suppression of vibration which is induced by the coupling of rigid motion. This control works both on the regulation and on the tracking cases. The performance and validity of this control method is shown by simulation examples.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.309-314
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• 2004

A flexible disk grinding system process has been introduced that utilized varying disk orientation with respect to workpiece along with the applied feed speed. Various process conditions including cutting speed, maximum feed speed and orientation angles could applied to observe process outcomes. Even though continuous and constant feed speed has been applied to the process, the results from the trapezoidal input velocity profiles would be observed and compared. Based on the control strategies including neural network methodologies, several output results were compared to find the optimum process condition. Two axis control results were displayed showing better performance with higher trajectory error for larger training epoch.

• Smart Structures and Systems
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• v.9 no.6
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• pp.535-547
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• 2012

Controlling the balance of motion in a context involving a biped robot navigating a rugged surface or a step is a difficult task. In the present study, a $3{\times}5$ flexible piezoelectric tactile sensor array is developed to provide a foot pressure map and zero moment point for a biped robot. We introduce an innovative concept involving structural electrodes on a piezoelectric film in order to improve the sensitivity. The tactile sensor consists of a polymer piezoelectric film, PVDF, between two patterned flexible print circuit substrates (FPC). Additionally, a silicon rubber bump-like structure is attached to the FPC and covered by a polydimethylsiloxane (PDMS) layer. Experimental results show that the output signal of the sensor exhibits a linear behavior within 0.2 N ~ 9 N, while its sensitivity is approximately 42 mV/N. According to the characteristic of the tactile sensor, the readout module is designed for an in-situ display of the pressure magnitudes and distribution within $3{\times}5$ taxels. Furthermore, the trajectory of the zero moment point (ZMP) can also be calculated by this program. Consequently, our tactile sensor module can provide the pressure map and ZMP information to the in-situ feedback to control the balance of moment for a biped robot.