• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.117-123
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• 2003

Rotational machines such as optical disk drives, hard disk drives, and so on are subject to periodic disturbances caused by their mechanical characteristics. In the meanwhile, it is well known that repetitive control rejects periodic disturbance effectively. This paper presents a practical application of repetitive control to the track-following servo of an optical disk drive. The repetitive control system is composed of two repetitive controllers which compensate for periodic disturbances generated by track geometry and eccentric rotation of disk and a feedback controller stabilizing the feedback loop. A robust stability for all plant uncertainties is proved using linear matrix inequalities (LMIs). In the controller design, a weighting function is introduced for the feedback controller to ensure a minimum loop gain and a sufficient phase margin. The repetitive controllers and the feedback controller are designed by solving an optimization problem which can consider the robust stability condition and the system performance. The developed repetitive control system is implemented in the digital control system with a 16-bit fixed-point digital signal processor (DSP). Through simulation and experiment. The feasibility of the proposed repetitive control system is verified.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1033-1038
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• 2014

Electric vehicles should be connected to power system for charge and discharge of battery. Besides vehicle's battery is charged for a power source, it is also reversibly possible to provide power source from battery to power system. Researches on battery usage for regulation resources have been progressed and could cause cost increase excessively because they distribute regulation capacity equally without considering the battery wear cost of SOC, temperature, voltage and so on. This causes increase of grid maintenance cost and aggravate economical efficiency. In this paper it is studied that the cost could be minimized according to the battery condition and characteristic. The equation is developed in this paper to calculate the possible number of charge and discharge cycle, according to SOC level and weighting factors representing the relation between battery life and temperature as well as voltage. Thereafter, the correlation is inferred between the battery condition and wear cost reflecting the battery price, and the expense of compensation is decided according to the condition on battery wear-out of vehicle. In addition, using realtime error between load and load expectation, it is calculated how much regulation capacity should be provided.

• Korean Journal of Computational Design and Engineering
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• v.11 no.2
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• pp.148-155
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• 2006

This paper presents a new method for assessing the efficiency of production process plans using tolerance chart to lower production cost. The tolerance chart is used to predict the accuracy of a part that is to be produced following the process plan, and to carry out the quantitative measurement on the efficiency of the process plan. By comparing the values of design tolerances and their corresponding resultant tolerances calculated using the tolerance chart, the process plan that is incapable of satisfying the design requirements and the faulty production operations can be identified. Similarly, the process plan that imposes unnecessarily high accuracy and wasteful production operations can also be identified. For the latter, a quantitative measure on the efficiency of the process plan is introduced. The higher the unnecessary cost of the production, the poor is the efficiency of the process plan. A coefficient is introduced for measuring the process plan efficiency. The coefficient also incorporates two weighting factors to reflect the difficulty of manufacturing operations and number of dimensional tolerances involved. To facilitate the identification of the machining operations and the machined surfaces, which are related to the unnecessarily tight resultant tolerances caused by the process plan, a rooted tree representation of the tolerance chart is introduced, and its use is demonstrated. An example is presented to illustrate the new method. This research introduces a new quantitative process plan evaluation method that may lead to the optimization of process plans.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.5
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• pp.233-241
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• 2000

This paper presents a systematic design procedure of $H_{\infty}$ controller of TCSC for damping low frequency inter-area oscillations in large power systems. Sensitivities of the inter-area mode for changes in line susceptance are computed using the eigen-sensitivity theory of augmented system matrix and TCSC locations are selected using the line sensitivities. The reduced model required for designing a manageable-size $H_{\infty}$ controller is obtained using the reduced frequency domain system identification method and the various weighting functions are tuned systematically to provide a robust performance. The proposed $H_{\infty}$ controller proved to be very effective for damping the inter-area mode of the large KEPCO power system.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.78-86
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• 1998

This paper presents a numerical method of the minimum-time trajectory planning for a robot manipulator amid obstacles. Each joint displacement is represented by the linear combination of the finite-term quintic B-splines which are the known functions of the path parameter. The time is represented by the linear function of the same path parameter. Since the geometric path is not fixed and the time is linear to the path parameter, the coefficients of the splines and the time-scale factor span a finite-dimensional vector space, a point in which uniquely represents the manipulator motion. The displacement, the velocity and the acceleration conditions at the starting and the goal positions are transformed into the linear equality constraints on the coefficients of the splines, which reduce the dimension of the vector space. The optimization is performed in the reduced vector space using nonlinear programming. The total moving time is the main performance index which should be minimized. The constraints on the actuator forces and that of the obstacle-avoidance, together with sufficiently large weighting coefficients, are included in the augmented performance index. In the numerical implementation, the minimum-time motion is obtained for a planar 3-1ink manipulator amid several rectangular obstacles without simplifying any dynamic or geometric models.

• Journal of Mechanical Science and Technology
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• v.17 no.5
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• pp.654-667
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• 2003

This paper presents a consequence of the systematic approach to identify the aerodynamic parameters of an unmanned aerial vehicle (UAV) equipped with the automatic flight control system. A 3-2-1-1 excitation is applied for the longitudinal mode while a multi-step input is applied for lateral/directional excitation. Optimal time step for excitation is sought to provide the broad input bandwidth. A fully automated programmed flight test method provides high-quality flight data for system identification using the flight control computer with longitudinal and lateral/directional autopilots, which enable the separation of each motion during the flight test. The accuracy of the longitudinal system identification is improved by an additional use of the closed-loop flight test data. A constrained optimization scheme is applied to estimate the aerodynamic coefficients that best describe the time response of the vehicle. An appropriate weighting function is introduced to balance the flight modes. As a result, concurrent system models are obtained for a wide envelope of both longitudinal and lateral/directional flight maneuvers while maintaining the physical meanings of each parameter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2037-2051
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• 2012

Cognitive radio (CR) is envisioned as a promising paradigm of exploiting intelligence for enhancing efficiency of underutilized spectrum bands. In CR, the main concern is to reliably sense the presence of primary users (PUs) to attain protection against harmful interference caused by potential spectrum access of secondary users (SUs). In this paper, evolutionary algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA) are proposed to minimize the total sensing decision error at the common soft data fusion (SDF) centre of a structurally-centralized cognitive radio network (CRN). Using these techniques, evolutionary operations are invoked to optimize the weighting coefficients applied on the sensing measurement components received from multiple cooperative SUs. The proposed methods are compared with each other as well as with other conventional deterministic algorithms such as maximal ratio combining (MRC) and equal gain combining (EGC). Computer simulations confirm the superiority of the PSO-based scheme over the GA-based and other conventional MRC and EGC schemes in terms of detection performance. In addition, the PSO-based scheme also shows promising convergence performance as compared to the GA-based scheme. This makes PSO an adequate solution to meet real-time requirements.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, learning rates, and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.47-50
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• 2000

In this paper, an optimal identification method using Multi-FNN(Fuzzy-Neural Network) is proposed for model ins of nonlinear complex system. In order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM clustering algorithm which carry out the input-output data preprocessing function and Genetic Algorithm which carry out optimization of model. The proposed Multi-FNN is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. HCM clustering method which carry out the data preprocessing function for system modeling, is utilized to determine the structure of Multi-FNN by means of the divisions of input-output space. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model, To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• The Journal of the Korean dental association
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• v.53 no.8
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• pp.558-568
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• 2015

Objective: The objectives of this study were to measure pediatric organ and effective doses of cone-beam computed tomography (CBCT) for orthodontic analysis and to compare them to those of panoramic and lateral cephalometric radiography, the conventional radiography for orthodontic analysis. Materials and Methods: Alphard VEGA for CBCT, Planmeca Proline XC for panoramic radiography and Orthophos CD for cephalometric radiography were used for this study. Thermoluminescent dosimeter (TLD) chips were located at 24 anatomic sites of 10-year-old anthropomorphic phantom and exposed during CBCT (C-mode; $200{\times}179mm$ FOV), panoramic and lateral cephalometric radiographic procedures at the clinical exposure settings for 10-year-old patient. Pediatric organ and effective doses were measured and calculated using ICRP 2007 tissue weighting factors. Results: Effective doses of CBCT, panoramic radiography and lateral cephlometric radiography in pediatric clinical exposure settings were $292.5{\mu}Sv$, $19.3{\mu}Sv$, and $4.4{\mu}Sv$ respectively. The thyroid gland contributed most significantly to the effective dose in all the radiographic procedures. Conclusion: Effective dose of CBCT was about 12 times to conventional radiographic procedures for orthodontic analysis in pediatric patient. The use of CBCT for orthodontic analysis should be fully justified over conventional radiography and dose optimization to decrease thyroid dose is needed in pediatric patients.