• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.727-732
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• 2008

In this paper, the state-space representation of generalized complimentary filter is proposed. Complementary filter has the suitable structure to merge information from sensors whose frequency regions are complementary. First, the basic concept and structure of complementary filter is introduced. And then the structure of the generalized filter and its state-space representation are proposed. The state-space representation of complementary filter is able to design the complementary filter by applying modern filtering techniques like Kalman filter and $H_{\infty}$ filter. To show the usability of the proposed state-space representation, the design of Inertial Navigation System(INS) vertical channel damping loop using Global Positioning System(GPS) is described. The proposed GPS/INS damping loop lends the structure of Baro/INS(Barometer/INS) vertical channel damping loop that is an application of complementary filter. GPS altitude error has the non-stationary statistics although GPS offers navigation information which is insensitive to time and place. Therefore, $H_{\infty}$ filtering technique is selected for adding robustness to the loop. First, the state-space representation of GPS/INS damping loop is acquired. And next the weighted $H_{\infty}$ norm proposed in order to suitably consider characteristics of sensor errors is used for getting filter gains. Simulation results show that the proposed filter provides better performance than the conventional vertical channel loop design schemes even when error statistics are unknown.

• Structural Engineering and Mechanics
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• v.46 no.6
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• pp.869-886
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• 2013

This work presents an experimental methodology specially developed for the nonlinear large-amplitude free vibration analysis of a clamped-free thin-walled metal column under self-weight. The main contribution of this paper is related to the developed experimental methodology which is based on a remote sensing technique using a computer vision system that integrates, on-line, the digital image acquisition and its treatment through special image processing routines. The main importance of this methodology is that it performs large deflections measurements without making contact with the structure and thus, not introducing undesirable changes in its behavior, for instance, appreciable changes in mass and stiffness properties. This structure presents, in most cases, highly non-linear responses, which cannot be reproduced by conventional finite-element softwares due, mainly, to the simultaneous influence of geometric and inertial non-linearities. To capture the non-linearities associated with large amplitude vibration and be able to describe the buckling process, the structure is discretized as a sequence of jointed coupled elastic pendulums. The obtained numerical results are favorably compared with the experimental ones, in the pre- and post-buckling regimes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.11
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• pp.1889-1896
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• 2003

In the microfluidic applications, viscous-driven pumping mechanism is a promising one since the viscous effect increases significantly as the size of device decreases, relative to the inertial effect. However, there exist a few drawbacks we have to improve such as low efficiency and small volume flow rate. In the present study, an optimum design synthesis is proposed to enhance the performance characteristics of the micropump with single rotating cylinder. First, the unstructured grid CFD method is described and validated by comparing its results to the previous results. Next, an automated optimum design synthesis tool is constructed by combining the aforementioned CFD analysis model with the mathematical optimization model. This technique is used to improve the performance characteristics of newly designed viscous-driven pump. The presented results show that the fluid dynamic optimization tool is robust and may be applied to other microfluidic device design applications.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.402-410
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• 2017

Acoustic based localization is essential to operate autonomous robotic systems in underwater environment where the use of sensorial data is limited. This paper proposes a localization method using artificial underwater acoustic sources. The proposed method acquires directional angles of acoustic sources using time difference of arrivals of two hydrophones. For this purpose, a probabilistic approach is used for accurate estimation of the time delay. Then, Gaussian sum filter based SLAM technique is used to localize both acoustic sources and underwater vehicle. It is performed by using bearing of acoustic sources as measurement and inertial sensors as prediction model. The proposed method can handle directional ambiguity of time difference based source localization by generating Gaussian models corresponding to possible locations of both front and back sides. Through these processes, the proposed method can provide reliable localization method for underwater vehicles without any prior information of source locations. The performance of the proposed method is verified by experimental results conducted in a real sea environment.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.2
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• pp.49-58
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• 2019

A number of techniques have been studied to estimate the position of pedestrians in indoor space. Among them, the technique of estimating the position using only the sensors attached to the body of the pedestrian without using the infrastructure is regarded as a very important technology for special purpose pedestrians such as the firefighters. In particular, it forms a research field under the name of Pedestrian Dead Reckoning (PDR). In this paper, we focus on a method for step detection which is essential when performing PDR using Inertial Measurement Unit (IMU) mounted on a shoe. Many researches have been done to detect the stance phase where the foot contacts the ground. Most of these methods, however, have a way to detect the specific size of the sensor signal and require thresholds for these methods. This has the difficulty of changing these thresholds if the user is different. To solve this problem, we propose a stance phase detection method that does not require any threshold value. It is expected that this result will make it easier to commercialize the technology because PDR can be implemented without user-dependent parameter setting.

• Advances in robotics research
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• v.2 no.3
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• pp.237-245
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• 2018

This study evaluates the efficacy of a class robust control scheme namely active force control in performing a joint based trajectory tracking of an upper limb exoskeleton in rehabilitating the elbow joint. The plant of the exoskeleton system is obtained via system identification method whilst the PD gains were tuned heuristically. The estimated inertial parameter that enables the AFC disturbance rejection effect is attained by means of a non-nature based metaheuristic optimisation technique known as simulated Kalman filter (SKF). It was demonstrated from the present investigation that the proposed PDAFC scheme outperformed the classical PD algorithm in tracking the prescribed trajectory both in the presence and without the presence of disturbance attributed by the mannequin limb weights (1 kg and 1.5 kg) that mimics the weight of actual human limb weight. Therefore, it is apparent from the results obtained from the present study that the proposed control scheme, i.e., PDAFC is suitable for the application of exoskeleton for stroke rehabilitation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.289-295
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• 2021

Recently, owing to the development of autonomous vehicles, research on precisely determining the position of a moving object has been actively conducted. Previous research mainly used the fusion of GNSS/IMU (Global Positioning System / Inertial Navigation System) and sensors attached to the vehicle through a Kalman filter. However, in recent years, new technologies have been used to determine the location of a moving object owing to the improvement in computing power and the advent of deep learning. Various techniques using RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), and NARX (Nonlinear Auto-Regressive eXogenous model) exist for such learning-based positioning methods. The purpose of this study is to compare the precision of existing filter-based sensor fusion technology and the NARX-based method in case of GNSS signal blockages using simulation data. When the filter-based sensor integration technology was used, an average horizontal position error of 112.8 m occurred during 60 seconds of GNSS signal outages. The same experiment was performed 100 times using the NARX. Among them, an improvement in precision was confirmed in approximately 20% of the experimental results. The horizontal position accuracy was 22.65 m, which was confirmed to be better than that of the filter-based fusion technique.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.8
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• pp.112-119
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• 1996

Among the various type of accelerometer, the servo rebalancing type accelermoter can be suitable for Inertial Navigation System, because of its high sensitivity and good response in low frequency. In this paper, we proposed a new technology to control inductive tuype accelerometer utilizing digital PWM method. The new developed digital PWM control has special design scheme for transmitting measurement value to outer device in its servo ollp. So it has no quantized error of transforming outputs of sensors to digital domain. The quantized error may make serious problem in INS system, because outputs of sensor are integrated once or twice by digital computer and it happens every sensor reading times. Therefore, in order to get the accurate information such as displacement, it is necessary to measure accurately the input current. In addition, Digital Signal Processing needs digital data transmission, digital PWM method is adaptive for this purpose. We realized a practical circuit for digital PWM control, analyzed the stability of the circuit, and designed the controller etc. In this study, we solved many practical problem for this application, and got out good results.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.112-119
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• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.559-566
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• 2001

The sway control problem of the pendulum motion of a container hanging on the trolly, which transports containers from a container ship to trucks, is considered in the paper. In the container crane control problem, suppressing the residual swing motion of the container at the end of acceleration, deceleration or the case of that the unexpected disturbance input exists is main issue. For this problem, in general, the trolley motion control strategy is introduced and applied. In this paper, we introduce and synthesize a new type of swing motion control system in which a small auxiliary mass is installed on the spreader. The actuator reacting against the auxiliary mall applies inertial control forces to the container to reduce the swing motion in the desired manner. In this paper, we apply the $H^{\infty}$ based gain-scheduling control technique to the anti-swing motion control system design problem of the controlled plant. In this control system, the controller dynamics are adjusted in real-time according to time-varying plant parameters. And the simulation result shows that the proposed control strategy is shown to be useful for the case of time-varying system and, robust to disturbances such as winds and initial sway motion.