• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.37-44
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• 1999

In this paper, we present a new sliding surface with a time-varying repeated root for fast and robust tracking of higher-order uncertain systems. The repeated root is moved to target one with stabilizing the closed-loop time-varying system in sliding mode. This initial root is obtained so that shifting distance of the surface may be minimized with respect to an initial error, and the intercept is produced so that the surface may pass the initial error. Under the allowable input, fast shifting of the surface and movement of the repeated root enable the error convergence rate to be increased. The proposed sliding mode control makes the error always remain on the surface from the beginning, and therefore, the system is more insensitive to parameter uncertainties and external disturbances. In simulation, the effectiveness of the proposed method is proved by comparison with the conventional one.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.115-126
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• 1996

In the time optimal control problem, bang-bang control has been used becaese it is the theoretical time minimum solution. However, to improve tracking speed performance in the time optimal control, it is important to select a switching point accurately which makes the velocity zero near the target track. But it is not easy to select the swiching point accurately because of the damping coefficient variation and uncertainties of modeling an actual system. The Adaptive model following control(AMFC) is implemented to relieve the difficulty and inconvenience of this task. The AMFC and make the controlled plant follow as closely as possible to a desired reference model whose switching point can be calculated easily and accurately, assuring the error between the states of the reference model and those of the controlled plant appoaches zero. The hybrid control method composed of AMFC and PID is applied to a tracking actuator of the magneto optical disk drive(MODD) in random access devices to improve its slow tracking performance. According to the simulaion and experimental results, the average tracking time as small as 20ms is obtained for a 3.5 magneto-optical disk drive. The AMFC also can be applied for other random access devices to improve the average tracking performance.

• Radiation Oncology Journal
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• v.37 no.1
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• pp.43-50
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• 2019

Purpose: The aim of this retrospective study was to investigate the use of a radiopaque tissue fiducial marker (TFM) in the treatment of prostate cancer patients who undergo post-prostatectomy radiotherapy (PPRT). TFM safety, its role and benefit in quantifying the set-up uncertainties in patients undergoing PPRT image-guided radiotherapy were assessed. Materials and Methods: A total of 45 consecutive PPRT patients underwent transperineal implantation of TFM at the level of vesicourethral anastomosis in the retrovesical tissue prior to intensity-modulated radiotherapy. Prostate bed motion was calculated by measuring the position of the TFM relative to the pelvic bony anatomy on daily cone-beam computed tomography. The stability and visibility of the TFM were assessed in the initial 10 patients. Results: No postoperative complications were recorded. A total of 3,500 images were analysed. The calculated prostate bed motion for bony landmark matching relative to TFM were 2.25 mm in the left-right, 5.89 mm in the superior-inferior, and 6.59 mm in the anterior-posterior directions. A significant 36% reduction in the mean volume of rectum receiving 70 Gy (rV₇₀) was achieved for a uniform planning target volume (PTV) margin of 7 mm compared with the Australian and New Zealand Faculty of Radiation Oncology Genito-Urinary Group recommended PTV margin of 10 mm. Conclusion: The use of TFM was safe and can potentially eliminate set-up errors associated with bony landmark matching, thereby allowing for tighter PTV margins and a consequent favourable reduction in dose delivered to the bladder and rectum, with potential improvements in toxicities.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.5
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• pp.413-419
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• 2008

Deterministic design optimization (DO) does not explicitly deal with a variety of factors from inherent randomness and uncertainties. Reliability based design optimization(RBDO) is necessary to use in engineering systems in order to guarantee quality and performance of product. In this paper, design variables are considered as random variables. Standard deviation according to change of design variables have changed as much as coefficient of variation. And, if the standard deviation is error of manufacturing, standard deviation-mean relation is concave form. We obtain reliability index using advanced first order second moment method(AFOSM). This paper is examined by solving two examples and the results are compares with DO, RBDO and suggested RBDO.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1691-1696
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• 2010

The efforts of reflecting the system's uncertainties in design step have been made and robust optimization or reliabilitybased design optimization are examples of the most famous methodologies. The statistical moments of a performance function and the constraints corresponding to probability conditions are involved in the formulation of these methodologies. Therefore, it is essential to effectively and accurately calculate them. The sensitivities of these methodologies have to be determined when nonlinear programming is utilized during the optimization process. The sensitivity of statistical moments and probability constraints is expressed in the integral form and limited to the normal random variable; we aim to expand the sensitivity formulation to nonnormal variables. Additional functional calculation will not be required when statistical moments and failure or satisfaction probabilities are already obtained at a design point. On the other hand, the accuracy of the sensitivity results could be worse than that of the moments because the target function is expressed as a product of the performance function and the explicit functions derived from probability density functions.

• YAKHAK HOEJI
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• v.52 no.6
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• pp.480-487
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• 2008

We described an estimation of measurement uncertainty in quantitative analysis of 11-nor-9-carboxy-${\Delta}^9$-tetrahydrocannabinol (THCCOOH), the major metabolite of ${\Delta}^9$-tetrahydrocannabinol, in urine sample by solid-phase extraction (SPE) and GC/MS detection. The analytical results were compared and the different contributions to the uncertainty were evaluated. Inter-day and inter-person validation were performed using statistical analysis of several indicative factors. Measurement uncertainty associated with target analyte in real forensic samples was estimated using quality control (QC) data. Traceability of measurement was established through traceable standards, calibrated volumetric glassware and volume measuring device. The major factors of contribution to combined standard uncertainty, were calibration linearity, inter-day repeatability and inter-person reproducibility, while those associated with preparation of analytical standards and sampling volume were not so important considering the degree of contribution. Relative combined standard uncertainties associated with the described method was 12.05% for THCCOOH.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.761-766
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• 2011

A hedge is a linguistic device to express uncertainties. Hedges are used in a sentence when the writer is uncertain or has doubt about the contents of the sentence. Due to this uncertainty, sentences with hedges are considered to be non-factual. There are many applications which need to determine whether a sentence is factual or not. Detecting hedges has the advantage in information retrieval, and information extraction, and QnA systems, which make use of non-hedge sentences as target to get more accurate results. In this paper, we constructed Korean hedge corpus, and extracted generalized hedge cue-word patterns from the corpus, and then used them in detecting hedges. In our experiments, we achieved 78.6% in F1-measure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.10
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• pp.967-974
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• 2017

In this paper, a differential-braking-based yaw moment control system was developed to guarantee robust performance against road bank angle. A new target yaw rate model was established by combining the signal from a lateral acceleration sensor and 2-DOF single track model. In addition, a disturbance observer was utilized to take into account parameter uncertainties in yaw dynamics and to improve robust performance of the controller. CARSIM, which is a multi-DOF vehicle dynamic simulation tool, was used to verify the performance of the proposed controller in various driving scenarios. The simulation results indicate that the stability of the vehicle was robustly maintained by the controller, which is characterized by the reflection of the signal of a lateral acceleration sensor signal and by the compensation of the errors in the model parameters via the disturbance observer.

• Smart Structures and Systems
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• v.23 no.1
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• pp.1-14
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• 2019

Control algorithms are the most important aspects in successful control of structures against earthquakes. In recent years, intelligent control methods rather than classical control methods have been more considered by researchers, due to some specific capabilities such as handling nonlinear and complex systems, adaptability, and robustness to errors and uncertainties. However, due to lack of learning ability of fuzzy controller, it is used in combination with a genetic algorithm, which in turn suffers from some problems like premature convergence around an incorrect target. Therefore in this research, the introduction and design of the Fuzzy Cooperative Coevolution (Fuzzy CoCo) controller and Adaptive Neural-Fuzzy Inference System (ANFIS) have been innovatively presented for semi-active seismic control. In this research, in order to improve the seismic behavior of structures, a semi-active control of building using Magneto Rheological (MR) damper is proposed to determine input voltage of Magneto Rheological (MR) dampers using ANFIS and Fuzzy CoCo. Genetic Algorithm (GA) is used to optimize the performance of controllers. In this paper, the design of controllers is based on the reduction of the Park-Ang damage index. In order to assess the effectiveness of the designed control system, its function is numerically studied on a 9-story benchmark building, and is compared to those of a Wavelet Neural Network (WNN), fuzzy logic controller optimized by genetic algorithm (GAFLC), Linear Quadratic Gaussian (LQG) and Clipped Optimal Control (COC) systems in terms of seismic performance. The results showed desirable performance of the ANFIS and Fuzzy CoCo controllers in considerably reducing the structure responses under different earthquakes; for instance ANFIS and Fuzzy CoCo controllers showed respectively 38 and 46% reductions in peak inter-story drift ($J_1$) compared to the LQG controller; 30 and 39% reductions in $J_1$ compared to the COC controller and 3 and 16% reductions in $J_1$ compared to the GAFLC controller. When compared to other controllers, one can conclude that Fuzzy CoCo controller performs better.

• Journal of the Korean Geotechnical Society
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• v.24 no.1
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• pp.119-130
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• 2008

Uncertainties in physical and engineering parameters for the design of shallow foundations arise from various aspects such as inherent variability and measurement error. This paper aims at investigating and reducing uncertainty from deterministic method by using the reliability-based design of shallow foundations accounting for the variation of various design parameters. A probability distribution type and statistics of random variables such as unit weight, cohesion, infernal friction angle and Young's modulus in geotechnical engineering are suggested to calculate the ultimate bearing capacities and immediate settlements of foundations. Reliability index and probability of failure are estimated based on the distribution types of random variables. Widths of foundation are calculated at target reliability index and probability of failure. It is found that application and analysis of the best-fit distribution type for each random variables are more effective than adoption of the normal distribution type in optimizing the reliability-based design of shallow foundations.