• East Asian mathematical journal
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• v.16 no.2
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• pp.251-266
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• 2000

The problem of solution uniqueness to the task of determining unknown parameters of mathematical models from input-output observations is studied. This problem is known as structural identifiability problem. We offer a new approach for testing structural identifiability of linear state space models. The approach compares favorably with numerous methods proposed by other authors for two main reasons. First, it is formulated in obvious mathematical form. Secondly, the method does not involve unfeasible symbolic computations and thus allows to test identifiability of large-scale models. In case of non-identifiability, when there is a set of solutions to the task, we offer a method of computing functions of the unknown parameters which can be determined uniquely from input-output observations and later used as new parameters of the model. Such functions are called parametric functions capable of estimation. To develop the method of computation of these functions we use Lie group transformation theory. Illustrative example is given to demonstrate applicability of presented methods.

• Journal of Astronomy and Space Sciences
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• v.39 no.3
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• pp.99-108
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• 2022

There are two models that explain the rotation curves of galaxies: dark matter, which gives the missing contribution to the gravitational potential of the standard theory of gravity, and modified theories of gravity, according to which the gravitational potential is created by ordinary visible mass. Both models have some disadvantages. The article offers a new look at the problem of galactic rotation curves. The author suggests that the moment of inertia creates an additional gravitational potential along with the mass. The numerical simulation carried out on the example of fourteen galaxies confirms the validity of such an assumption. This approach makes it possible to explain the constancy of gas velocities outside the galactic disk without involving the hypothesis of the existence of dark matter. At the same time, the proposed approach lacks the disadvantages of modified theories of gravity, where the gravitational potential is created only by the mass of visible matter.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.32.2-32.2
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• 2011

State dependent Riccati equation (SDRE) control technique has been widely used in the control society. Although it solves nonlinear optimal control problems, which minimizes state error and control efforts simultaneously, it has drawbacks when it is to be applied to the real time systems in that it requires much computational efforts. So the real time system whose computational ability is limited (for example, satellites) cannot afford to use SDRE controller. To solve this problem, a hybrid controller which is based on MSDRE (Modified SDRE) and ANFIS (Adaptive Neuro-Fuzzy Inference System) has been proposed by Abdelrahman et al. (2010). We propose a hybrid controller based on SDRE and ANFIS, and apply the hybrid controller to the hardware attitude simulator to perform a HIL (Hardware-In-the-Loop) simulation. Through HIL simulation, it is demonstrated that the hybrid controller satisfies the control requirement and the computation load is reduced significantly. In addition, the effects of statistical properties of the ANFIS training data to the performance of the ANFIS controller have been analyzed.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.3
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• pp.206-220
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• 2010

This paper proposes optimal control techniques for determining translational and rotational maneuvers that facilitate proximity operations and docking. Two candidate controllers that provide translational motion are compared. A state-dependent Riccati equation controller is formulated from nonlinear relative motion dynamics, and a linear quadratic tracking controller is formulated from linearized relative motion. A linear quadratic Gaussian controller using star trackers to provide quaternion measurements is designed for precision attitude maneuvering. The attitude maneuvers are evaluated for different final axis alignment geometries that depend on the approach distance. A six degrees-of-freedom simulation demonstrates that the controllers successfully perform proximity operations that meet the conditions for docking.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.67.5-67
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• 2001

A closed loop system with a linear plant and nonlinearity in the feedback connection is analyzed for its quasi-static orbital stability by a state-space approach. First a periodic orbit is assumed to exist in the loop which is determined by describing function method for the given nonlinearity. This is possible by selecting a proper nonlinearity and a rigorous justification of the describing function method.[1-3, 18, 20]. Then by introducing residual operator, a linear perturbed model can be formulated. Using various transformations like a modified eigenstructure decomposition, periodic-averaging, charge of variables and coordinate transformation, the stability of the periodic orbit, as a solution of harmonic balance, can be shown by investigating a simple scalar function and result of linear algebra. This is ...

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.644-650
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• 1998

In this paper , a state space model for flexible beam is presented using the assumed-modes approach. The state space equation is derived for a flexible beam in which one end is connected to a motor and is driven by a torque equation and the other end is free. Many of the transfer function proposed thus far use the torque to the flexible beam as the input and the tip deflection of the flexible beam as the output. The Technique for the analysis and synthesis of the dual-input describing function(DIDF) is introduced here and the construction of a non-linear compensator, based on this technique, is proposed. This non-linear compensator, properly connected in the direct path of a closed-loop linear or non-linear control system. The above non-linear network is used to compensate linear and non-linear systems for instability, limit cycles, low speed of response and static accuracy. The effectiveness of the proposed scheme is demonstrated through computer simulation and experimental results.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.482-489
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• 2006

This paper presents the generalized dynamic modeling of self-excited induction generator (SEIG) using state-space approach. The proposed dynamic model consists of induction generator; self-excitation capacitance and load model are expressed in stationary d-q reference frame with the actual saturation curve of the machine. An artificial neural network model is implemented to estimate the machine magnetizing inductance based on the knowledge of magnetizing current. The dynamic performance of SEIG is investigated under no load, with the load, perturbation of load, short circuit at stator terminals, and variation of prime mover speed, variation of capacitance value by considering the effect of main and cross-flux saturation. During voltage buildup the variation in magnetizing inductance is taken into consideration. The performance of SEIG system under various conditions as mentioned above is simulated using MATLAB/SIMULINK and the simulation results demonstrates the feasibility of the proposed system.

• Journal of Korea Technology Innovation Society
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• v.11 no.1
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• pp.72-90
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• 2008

What has been the contribution of industrial innovation to economic growth? Typically, the issue has been approached with growth-accounting methods augmented to include a "stock of knowledge". An independent estimate of the rate of return to R&D is found in order to impute patents granted to the accumulation of knowledge. Griliches(1973) then uses a regression approach to assess the effect of an R&D variable on the computed TFP growth rate. The regression coefficient on the R&D variable would provide an estimate of the social rate of return to R&D. The related studies tend to show high social rates of return to R&D, typically in a range of 20 to 40 % per year. We need to provide multiple equation dynamic system for productivity and innovation in Korean economy in state space form. A wide range of time series models, including the classical linear regression model, can be written and estimated as special cases of a state space specification. State space models have been applied in the econometrics literature to model unobserved variables like productivity. Estimation produces the following results. Considering the goodness of fit, we can see that the evidence is strongly in favor of the range $0.120{\sim}0.135$ for the elasticity of TFP to R&D stock in the period between 1970's and the early 2000's.

• Korean Institute of Interior Design Journal
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• v.14 no.3 s.50
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• pp.181-190
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• 2005

In accordance with the rapid growth of digital media in 1990s, the state of indetermination that is found in digital process has been emphasized in the field of natural science and philosophy. Digitalized space design has been dramatically developed and it raised heated debate and comment on 'folded space' The purpose of this thesis is to explore how the cognitive-ecological factors constitute fold structures in space design of the late 20th century. Syntax of space structure and geometric composition were analyzed to define what types of cognitive-ecological factors are contrived in the process of visual information. In particular, I put higher theoretical emphasis on what characteristics are ensued in the process of structuring spaces than any other subjects. Through theses analyses and discussions, I raised questions on what principles are operating to create new space design that counts on non-linear structure and its formational process. And I also observed what influences these structural principles of design could fundamentally bring to human beings. First, I proposed that we could overcome reductionist space design through cognitive-ecological approach. Some key concepts such as affordance, parallel processing, and redundancy were adopted as defining elements of non-linear structures. As a result of analyses, I found that the cognitive-ecological approach could substitute the reductionist space design of the past. What is also found is that the three variables are the ultimate ecological elements. In addition, as a methodological concept of fold structures, the form of 'topology' was highlighted because it could be a supporting idea to the cognitive-ecological factors. Second, I claimed that non-linear design is more experiential than rational linear design, and it is more efficiently correspondent to human being than any other forms. What is intended and implied in non-linear structure is also indicated.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.321-339
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• 2017

In this work, we are interested in the extraction of areas of interest from satellite images by introducing a MO-TRIBES/OC-SVM approach. The One-Class Support Vector Machine (OC-SVM) is based on the estimation of a support that includes training data. It identifies areas of interest without including other classes from the scene. We propose generating optimal training data using the Multi-Objective TRIBES (MO-TRIBES) to improve the performances of the OC-SVM. The MO-TRIBES is a parameter-free optimization technique that manages the search space in tribes composed of agents. It makes different behavioral and structural adaptations to minimize the false positive and false negative rates of the OC-SVM. We have applied our proposed approach for the extraction of earthquakes and urban areas. The experimental results and comparisons with different state-of-the-art classifiers confirm the efficiency and the robustness of the proposed approach.